April 2024 arXiv papers — page 130

Hao Liu, Yi Shen, Shuangjiang Yu, Zijun Gao

Path planning is an important problem with the the applications in many aspects, such as video games, robotics etc. This paper proposes a novel method to address the problem of Deep Reinforcement Learning (DRL) based path planning for a mobile robot. We design DRL-based algorithms, including reward functions, and parameter optimization, to avoid time-consumi

Zhe Li, Tianfang Zhao, Hongjun Zhu

The digital innovation accompanied by explicit economic incentives have fundamentally changed the process of innovation diffusion. As a representative of digital innovation, NFTs provide a decentralized and secure way to authenticate and trade digital assets, offering the potential for new revenue streams in the digital space. However, current researches abo

Konaté Mohamed Abbas, Anne-Françoise Yao, Thierry Chateau, Pierre Bouges

In this paper, we investigate continual learning performance metrics used in class incremental learning strategies for continual learning (CL) using some high performing methods. We investigate especially mean task accuracy. First, we show that it lacks of expressiveness through some simple experiments to capture performance. We show that monitoring average

Chen Zhou, Ghassan AlRegib, Armin Parchami, Kunjan Singh

Forecasting human trajectories in traffic scenes is critical for safety within mixed or fully autonomous systems. Human future trajectories are driven by two major stimuli, social interactions, and stochastic goals. Thus, reliable forecasting needs to capture these two stimuli. Edge-based relation modeling represents social interactions using pairwise correl

Congying Liu, Gaosheng Wang, Peipei Liu, Xingyuan Wei

Few-shot named entity recognition can identify new types of named entities based on a few labeled examples. Previous methods employing token-level or span-level metric learning suffer from the computational burden and a large number of negative sample spans. In this paper, we propose the Hybrid Multi-stage Decoding for Few-shot NER with Entity-aware Contrast

Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang

We propose a novel formalism for describing Structural Causal Models (SCMs) as fixed-point problems on causally ordered variables, eliminating the need for Directed Acyclic Graphs (DAGs), and establish the weakest known conditions for their unique recovery given the topological ordering (TO). Based on this, we design a two-stage causal generative model that

Joe Kramer-Miller

Let $E_p(x)$ denote the Artin-Hasse exponential and let $\overline{E}_p(x)$ denote its reduction modulo $p$ in $\mathbb{F}_p[[x]]$. In this article we study transcendence properties of $\overline{E}_p(x)$ over $\mathbb{F}_p[x]$. We give two proofs that $\overline{E}_p(x)$ is transcendental, affirmatively answering a question of Thakur. We also prove algebrai

Rushani Wijesuriya, Margarita Moreno-Betancur, John B Carlin, Ian R White

Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thus an analytic approach that accounts for this clustering by individual is required. While almost all research suffers from missing data, this can be particularly

Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal

As with most other data domains, EEG data analysis relies on rich domain-specific preprocessing. Beyond such preprocessing, machine learners would hope to deal with such data as with any other time series data. For EEG classification many models have been developed with layer types and architectures we typically do not see in time series classification. Furt

Daniel Rico, Yérali Gandica

Social media has dramatically influenced how individuals and groups express their demands, concerns and aspirations during social demonstrations. The study of X or Twitter hashtags during those events has revealed the presence of some temporal points characterised by high correlation among their participants. It has also been reported that the connectivity p

Martin Popel, Lucie Poláková, Michal Novák, Jindřich Helcl

We present Charles Translator, a machine translation system between Ukrainian and Czech, developed as part of a society-wide effort to mitigate the impact of the Russian-Ukrainian war on individuals and society. The system was developed in the spring of 2022 with the help of many language data providers in order to quickly meet the demand for such a service,

Guido Borghi, Annalisa Franco, Nicolò Di Domenico, Matteo Ferrara

In response to the rising threat of the face morphing attack, this paper introduces and explores the potential of Video-based Morphing Attack Detection (V-MAD) systems in real-world operational scenarios. While current morphing attack detection methods primarily focus on a single or a pair of images, V-MAD is based on video sequences, exploiting the video st

Hongru Du, Jianan Zhao, Yang Zhao, Shaochong Xu

Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables such as epidemiological time series data, viral biology, population demographics, and the intersection of public policy and human behavior. E

Jared Miller, Niklas Schmid, Matteo Tacchi, Didier Henrion

This paper develops a method to upper-bound extreme-values of time-windowed risks for stochastic processes. Examples of such risks include the maximum average or 90% quantile of the current along a transmission line in any 5-minute window. This work casts the time-windowed risk analysis problem as an infinite-dimensional linear program in occupation measures

Loïc Béthencourt, Rémi Catellier, Etienne Tanré

In this article, we study a finite horizon linear-quadratic stochastic control problem for Brownian particles, where the cost functions depend on the state and the occupation measure of the particles. To address this problem, we develop an It\^o formula for the flow of occupation measure, which enables us to derive the associated Hamilton-Jacobi-Bellman equa

Keshab Chandra Bakshi, Ved Prakash Gupta

We prove that an inclusion $\mathcal{B} \subset \mathcal{A}$ of simple unital $C^*$-algebras with a finite-index conditional expectation is regular if and only if there exists a finite group $G$ that admits a cocycle action $(\alpha,\sigma)$ on the intermediate $C^*$-subalgebra $\mathcal{C}$ generated by $\mathcal{B}$ and its centralizer $\mathcal{C}_\mathca

Thiago M. Santiago, Sarah G. A. Barbosa, Francisco J. Cavalcante, Daniel B. de Freitas

The stellar rotation has an essential role in modifying the structure of the star and, therefore, the way these different interplays arise. On the other hand, changes in orbits impact the star's rotation and its evolution. The evolution of the star's rotation accounts for the angular momentum exchange with the planet and follows the effects of the internal t

Aleksandr Gushchin, Anna Chistyakova, Vladislav Minashkin, Anastasia Antsiferova

Recently, the area of adversarial attacks on image quality metrics has begun to be explored, whereas the area of defences remains under-researched. In this study, we aim to cover that case and check the transferability of adversarial purification defences from image classifiers to IQA methods. In this paper, we apply several widespread attacks on IQA models

Riccardo Gianluigi Serio, Maria Michela Dickson, Thomas de Graaff, Eric H. Pels

Tourism consumption has grown into a major economic factor for modern societies. However, the environmental impact of tourism has become a significant concern, leading to an increased focus on sustainable tourism policies. While governments and institutions have introduced frameworks to promote ecological transition in the tourism sector, the effectiveness o

Surajit Biswas, Sourav Kanti Patra

Tootkaboni and Vahed introduced the notion of some large sets near idempotent along with some combinatorial properties. We characterize when the finite Cartesian product of central sets near idempotent is central near idempotent. Moreover, we provide a partial characterization for the infinite Cartesian product of the same. We then study the abundance of som

Antonette Shibani, Simon Knight, Kirsty Kitto, Ajanie Karunanayake

Artificial Intelligence (AI) has become a ubiquitous part of society, but a key challenge exists in ensuring that humans are equipped with the required critical thinking and AI literacy skills to interact with machines effectively by understanding their capabilities and limitations. These skills are particularly important for learners to develop in the age o

Yijin Liu, Fandong Meng, Jie Zhou

Recently, dynamic computation methods have shown notable acceleration for Large Language Models (LLMs) by skipping several layers of computations through elaborate heuristics or additional predictors. However, in the decoding process of existing approaches, different samples are assigned different computational budgets, which cannot guarantee a stable and pr

Manil T. Mohan, S. Pradeep, S. Sankar, S. Karthikeyan

The blow-up phenomena of stochastic semilinear parabolic equations with additive as well as linear multiplicative L\'evy noises are investigated in this work. By suitably modifying the concavity method in the stochastic context, we establish the blow-up phenomena of such systems defined on bounded domains.

Gerhard Wunder, Axel Flinth, Daniel Becker, Benedikt Groß

Secret key generation (SKG) between authenticated devices is a pivotal task for secure communications. Diffie-Hellman (DH) is de-facto standard but not post-quantum secure. In this paper, we shall invent and analyze a new security primitive that is specifically designed for WPAN. For WPAN, wireless channel-based SKG has been proposed but was not widely deplo

Keiju Sono

Let $p_{n}$ denote the $n$th prime and for any fixed positive integer $k$ and $X\geq 2$, put \[ G_{k}(X):=\max _{p _{n+k}\leq X} \min \{ p_{n+1}-p_{n}, \ldots , p_{n+k}-p_{n+k-1} \}. \] Ford, Maynard and Tao proved that there exists an effective absolute constant $c_{LG}>0$ such that \[ G_{k}(X)\geq \frac{c_{LG}}{k^{2}}\frac{\log X \log \log X \log \log \log

Zhiqiang Li, Xianghui Shi

Expanding Thurston maps were introduced by M. Bonk and D. Meyer with motivation from complex dynamics and Cannon's conjecture from geometric group theory via Sullivan's dictionary. In this paper, we study subsystems of expanding Thurston maps motivated via Sullivan's dictionary as analogs of some subgroups of Kleinian groups. We prove the uniqueness and vari

Yanbiao Zhang, Fanjie Zeng, Dehua Kong, Lian Lei

Scintillation detectors are essential tools for radiation measurement, but calibrating them accurately can be challenging, especially when full-energy peaks are not prominent. This is common in detectors like plastic scintillators. Current methods for calibrating these detectors often require manual adjustments. To address this, we propose a new method calle

Guillaume Thiran, François De Saint Moulin, Claude Oestges, Luc Vandendorpe

In this paper, performance bounds for the multi-antenna near-field range estimation of extended targets are provided. First, analytic expressions of the ambiguity functions are obtained, emphasising the cooperation between the waveform delay and the near-field phase shift information. The impact of estimating the range of an extended target with a point targ

Rahul Mehta, Andrew Hoblitzell, Jack O'Keefe, Hyeju Jang

Hallucinations in large language models (LLMs) have recently become a significant problem. A recent effort in this direction is a shared task at Semeval 2024 Task 6, SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes. This paper describes our winning solution ranked 1st and 2nd in the 2 sub-tasks of model agnostic and mode

Konstantinos Zinelis, Thomas Abadie, Gareth H. McKinley, Omar K. Matar

Extensional flows of complex fluids are pivotal in industrial applications like spraying, atomisation, and microfluidic drop deposition. The Dripping-on-Substrate (DoS) technique is a conceptually simple, but dynamically-complex, probe of the extensional rheology of low-viscosity, non-Newtonian fluids. DoS involves capillary-driven thinning of a liquid bridg

Athanasios Karapantelakis, Alexandros Nikou, Ajay Kattepur, Jean Martins

In the near future, mobile networks are expected to broaden their services and coverage to accommodate a larger user base and diverse user needs. Thus, they will increasingly rely on artificial intelligence (AI) to manage network operation and control costs, undertaking complex decision-making roles. This shift will necessitate the application of techniques

Matthieu Josuat-Vergès

It is proved that the generalized cluster complex defined by Fomin and Reading has a dihedral symmetry. Together with diagram symmetries, they generate its automorphism group. A consequence is a simple explicit formula for the order of this automorphism group.

J. Silverio Martinez-Baena, Salvador Villegas

In the regularity theory of solutions to elliptic partial differential equations often the concept of stability plays the role of a sufficient condition for smoothness. It is a natural question to ask if this holds true for nonstable but finite Morse index solutions. We provide a negative answer showing the existence of sequences of solutions with radial Mor

José Edson Sampaio

In this paper, we prove metric analogues, in any dimension and in any co-dimension, of the famous Theorem of Mumford on smoothness of normal surfaces and the beautiful Theorem of Ramanujam that gives a topological characterization of $\mathbb{C}^2$ as an algebraic surface. For instance, we prove that a complex analytic set that is log-Lipschitz regular at 0

J. R. Anglin

Recent work has studied fermion transport through a finite one-dimensional lattice of quantum dots, with localized particle loss from the central lattice site. The dots at each end of the lattice are connected to macroscopic leads, represented as zero-temperature reservoirs of free fermions with a given potential difference. Here we show how this model repre

Anam Hashmi, Julia Dietlmeier, Kathleen M. Curran, Noel E. O'Connor

Cine cardiac magnetic resonance (CMR) imaging is recognised as the benchmark modality for the comprehensive assessment of cardiac function. Nevertheless, the acquisition process of cine CMR is considered as an impediment due to its prolonged scanning time. One commonly used strategy to expedite the acquisition process is through k-space undersampling, though

Marija Popovic, Joshua Ott, Julius Rückin, Mykel J. Kochenderfer

Adaptive informative path planning (AIPP) is important to many robotics applications, enabling mobile robots to efficiently collect useful data about initially unknown environments. In addition, learning-based methods are increasingly used in robotics to enhance adaptability, versatility, and robustness across diverse and complex tasks. Our survey explores r

Tianliang Ma, Guangxi Fan, Xuguang Sun, Zhihui Deng

This paper proposes a fast system technology co-optimization (STCO) framework that optimizes power, performance, and area (PPA) for next-generation IC design, addressing the challenges and opportunities presented by novel materials and device architectures. We focus on accelerating the technology level of STCO using AI techniques, by employing graph neural n

K. G. S. H. Gunawardana, Kieran Mullen

Carbon nanotubes (CNTs) are promising candidates to improve the thermal conductivity of nano-composites. The main obstacle to these applications is the extremely high thermal boundary (Kapitza) resistance between the CNTs and their matrix. In this theoretical work our goal is to maximize the heat flux through the CNT by functionalizing the CNT ends. We use a

Yanhu Wang, Shuaishuai Guo, Anming Dong, Hui Zhao

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input

Kang You, Pan Gao, Zhan Ma

The past several years have witnessed the emergence of learned point cloud compression (PCC) techniques. However, current learning-based lossless point cloud attribute compression (PCAC) methods either suffer from high computational complexity or deteriorated compression performance. Moreover, the significant variations in point cloud scale and sparsity enco

James M. S. Donnellan, Seb J. Oliver, Matthieu Bethermin, Longji Bing

The PRobe far-Infrared Mission for Astrophysics (PRIMA) concept aims to perform mapping with spectral coverage and sensitivities inaccessible to previous FIR space telescopes. PRIMA's imaging instrument, PRIMAger, provides unique hyperspectral imaging simultaneously covering 25-235 $\mu$m. We synthesise images representing a deep, 1500 hr deg$^{-2}$ PRIMAger

Inyong Cho, Rajibul Shaikh

We study the homogeneous and anisotropic evolution of Bianchi type-I spacetime driven by perfect fluid with shear viscosity. We obtain exact solutions by considering the simplest form of the equation of state wherein the pressure and the shear stress are proportional to the energy density individually. A special case of our general solutions represent Bianch

F. F. Murzakhanov, M. A. Sadovnikova, G. V. Mamin, S. S. Nagalyuk

The nitrogen-vacancy (NV) centers (NCVSi) - in 4H silicon carbide (SiC) constitute an ensemble of spin S = 1 solid state qubits interacting with the surrounding 14N and 29Si nuclei. As quantum applications based on a polarization transfer from the electron spin to the nuclei require the knowledge of the electron-nuclear interaction parameters, we have used h

Wataru Yoshida, Kei Hirose

In a regression model, prediction is typically performed after model selection. The large variability in the model selection makes the prediction unstable. Thus, it is essential to reduce the variability in model selection and improve prediction accuracy. To achieve this goal, a parametric bootstrap smoothing can be applied. In this method, model selection i

Leticia F. Cugliandolo, Grégory Schehr, Marco Tarzia, Davide Venturelli

We study the spectral properties of the adjacency matrix in the giant connected component of Erd\"os-R\'enyi random graphs, with average connectivity $p$ and randomly distributed hopping amplitudes. By solving the self-consistent cavity equations satisfied by the matrix elements of the resolvent, we compute the probability distribution of the local density o

J. A. J. Mitchell, M. J. Ward, D. Kynoch, J. V. Hernández Santisteban

Near IR spectroscopic reverberation of Active Galactic Nuclei (AGN) potentially allows the infrared (IR) broad line region (BLR) to be reverberated alongside the disc and dust continua, while the spectra can also reveal details of dust astro-chemistry. Here, we describe results of a short pilot study (17 near-IR spectra over a 183 d period) for Mrk 509. The

Mingchen Zheng, Xin Zhang, Junpeng Cao, Wen-li Yang

An exactly solvable strongly correlated electron model with two independent parameters is constructed in the frame of the quantum inverse scattering method, which can be seen as a generalization of the Bariev model. Through the Bethe ansatz method, a set of Bethe ansatz equations is derived. In the thermodynamic limit, to study the ground state of the model,

Xenofon Karakonstantis, Efren Fernandez-Grande, Peter Gerstoft

In this study, we introduce a method for estimating sound fields in reverberant environments using a conditional invertible neural network (CINN). Sound field reconstruction can be hindered by experimental errors, limited spatial data, model mismatches, and long inference times, leading to potentially flawed and prolonged characterizations. Further, the comp

Lorenz Zwick, David O'Neill, Kai Hendriks, Philip Kirkeberg

Aims: To showcase and characterise the rich phenomenology of temperature fluctuation patterns that are imprinted on the CMB by the gravitational wave memory (GWM) of massive black hole (BH) mergers. Methods: We analyse both individual binaries as well as populations of binaries, distributed in local cosmological boxes at a given redshift. Results: The magnit

Xiaolei Lang, Laijian Li, Chenming Wu, Chen Zhao

In this paper, we present a real-time photo-realistic SLAM method based on marrying Gaussian Splatting with LiDAR-Inertial-Camera SLAM. Most existing radiance-field-based SLAM systems mainly focus on bounded indoor environments, equipped with RGB-D or RGB sensors. However, they are prone to decline when expanding to unbounded scenes or encountering adverse c

Nicolas Brughmans, Rony Keppens, Hans Goedbloed

Accretion disks are highly unstable to magnetic instabilities driven by shear flow, where classically, the axisymmetric, weak-field Magneto-Rotational Instability (MRI) has received much attention through local WKB approximations. In contrast, discrete non-axisymmetric counterparts require a more involved analysis through a full global approach to deal with

Xiaowei Chen, Hong Li, Yufan Lu, Rui Zhou

This paper explores the implications of using machine learning models in the pricing of catastrophe (CAT) bonds. By integrating advanced machine learning techniques, our approach uncovers nonlinear relationships and complex interactions between key risk factors and CAT bond spreads -- dynamics that are often overlooked by traditional linear regression models

A. Katsaris, I. A. Englezos, C. Weitenberg, F. K. Diakonos

We consider the emergence of edge states in a finite optical lattice and show that the boundaries of the lattice play a decisive role for their location in the corresponding energy spectrum. We introduce a simple parametrisation of the boundaries of the optical lattice and demonstrate the existence of an optimal choice of the values of the parameters which l

Hajime Ishikawa, Shusaku Imajo, Hikaru Takeda, Masafumi Kakegawa

We report the magnetic properties of a cobalt oxalate metal-organic-framework featuring the hyperoctagon lattice. Our thermodynamic measurements reveal the $J_{\rm{eff}}$ = 1/2 state of the high-spin Co$^{2+}$ (3$\textit{d}^{7}$) ion and the two successive magnetic transitions at zero field with two-stage entropy release. $^{13}$C-NMR measurements reveal the

Alexandre Fernandes, Zbigniew Jelonek, José Edson Sampaio

We show that two bi-Lipschitz equivalent Brieskorn-Pham hypersurfaces have the same multiplicities at $0$. Moreover we show that if two algebraic $(n-1)$-dimensional cones $P, R\subset\mathbb C^n$ with isolated singularities are homeomorphic, then they have the same degree.

Shishir G. Patil, Tianjun Zhang, Vivian Fang, Noppapon C.

Large Language Models (LLMs) are evolving beyond their classical role of providing information within dialogue systems to actively engaging with tools and performing actions on real-world applications and services. Today, humans verify the correctness and appropriateness of the LLM-generated outputs (e.g., code, functions, or actions) before putting them int

Juan Carlos Ruiz-Garcia, Ruben Tolosana, Ruben Vera-Rodriguez, Aythami Morales

This article provides a comprehensive overview of recent research in the area of Child-Computer Interaction (CCI). The main contributions of the present article are two-fold. First, we present a novel longitudinal CCI database named ChildCIdbLong, which comprises over 600 children aged 18 months to 8 years old, acquired continuously over 4 academic years (20

Chaohu Liu, Kun Yin, Haoyu Cao, Xinghua Jiang

Leveraging vast training data, multimodal large language models (MLLMs) have demonstrated formidable general visual comprehension capabilities and achieved remarkable performance across various tasks. However, their performance in visual document understanding still leaves much room for improvement. This discrepancy is primarily attributed to the fact that v

Federico Corberi, Salvatore dello Russo, Luca Smaldone

We study the ordering kinetics of a generalization of the voter model with long-range interactions, the $p$-voter model, in one dimension. It is defined in terms of boolean variables $S_{i}$, agents or spins, located on sites $i$ of a lattice, each of which takes in an elementary move the state of the majority of $p$ other agents at distances $r$ chosen with

Max Lonysa Muller, Erik Saaman, Jan Martijn E. M. van der Werf, Charles Jeurgens

In many fact-finding investigations, notably parliamentary inquiries, process chronologies are created to reconstruct how a controversial policy or decision came into existence. Current approaches, like timelines, lack the expressiveness to represent the variety of relations in which historic events may link to the overall chronology. This obfuscates the nat

Claude Cibils, Marcelo Lanzilotta, Eduardo N. Marcos, Andrea Solotar

In this paper we introduce, according to one of the main ideas of $\tau$-tilting theory, the $\tau$-Hochschild cohomology in degree one of a finite dimensional $k$-algebra $\Lambda$, where $k$ is a field. We define the excess of $\Lambda$ as the difference between the dimensions of the $\tau$-Hochschild cohomology in degree one and the dimension of the usual

Bang Liu, Li-Hua Zhang, Zong-Kai Liu, Qi-Feng Wang

Developing microwave electric field sensing based on Rydberg atom has received significant attention due to its unique advantages. However, achieving effective coupling between Rydberg atom and the microwave electric field in the sensing process is a challenging problem that greatly impacts the sensitivity. To address this, we propose the use of a microwave

Christopher Fuchs, Lena Fürst, Hartmut Buhmann, Johannes Kleinlein

We present overlapping top gate electrodes for the formation of gate defined lateral junctions in semiconducting layers as an alternative to the back gate/top gate combination and to the split gate configuration. The optical lithography microfabrication of the overlapping top gates is based on multiple layers of low-temperature atomic layer deposited hafnium

Chunxu Liu, Guozhen Zhang, Rui Zhao, Limin Wang

Large motion poses a critical challenge in Video Frame Interpolation (VFI) task. Existing methods are often constrained by limited receptive fields, resulting in sub-optimal performance when handling scenarios with large motion. In this paper, we introduce a new pipeline for VFI, which can effectively integrate global-level information to alleviate issues as

Ferdinand Schlatt, Maik Fröbe, Harrisen Scells, Shengyao Zhuang

Existing cross-encoder models can be categorized as pointwise, pairwise, or listwise. Pairwise and listwise models allow passage interactions, which typically makes them more effective than pointwise models but less efficient and less robust to input passage order permutations. To enable efficient permutation-invariant passage interactions during re-ranking,

Shuzhou Yuan, Michael Färber

Pretrained Language Models (PLMs) benefit from external knowledge stored in graph structures for various downstream tasks. However, bridging the modality gap between graph structures and text remains a significant challenge. Traditional methods like linearizing graphs for PLMs lose vital graph connectivity, whereas Graph Neural Networks (GNNs) require cumber

Thomas Merth, Qichen Fu, Mohammad Rastegari, Mahyar Najibi

Despite the successes of large language models (LLMs), they exhibit significant drawbacks, particularly when processing long contexts. Their inference cost scales quadratically with respect to sequence length, making it expensive for deployment in some real-world text processing applications, such as retrieval-augmented generation (RAG). Additionally, LLMs a

Subarna Bhattacharjee, S. M. Sunoj, Sabana Anwar

In this paper, we define weighted failure rate and their different means from the stand point of an application. We begin by emphasizing that the formation of n independent component series system having weighted failure rates with sum of weight functions being unity is same as a mixture of n distributions. We derive some parametric and non-parametric charac

Dan Popovici

Given a complex manifold $X$ and a smooth positive function $\eta$ thereon, we perturb the standard differential operator $d=\partial + \bar\partial$ acting on differential forms to a first-order differential operator $D_\eta$ whose principal part is $\eta\partial + \bar\partial$. The role of the zero-th order part is to force the integrability property $D_\

Lyu-Hang Liu, Yu Zheng, Yuan Tian, Long Wang

Accurate measurement of pressure with a wide dynamic range holds significant importance for various applications. This issue can be realized with a mechanical nano-oscillator, where the pressure-related collisions with surrounding molecules induce its energy dissipation. However, this energy dissipation of the nano-oscillator may be overshadowed by other pro

Enkeleda Thaqi, Mohamed Mantawy, Enkelejda Kasneci

SARA integrates Eye Tracking and state-of-the-art large language models in a mixed reality framework to enhance the reading experience by providing personalized assistance in real-time. By tracking eye movements, SARA identifies the text segments that attract the user's attention the most and potentially indicate uncertain areas and comprehension issues. The

H. Jung

The role of soft gluons in inclusive collinear parton densities as well as in Transverse Momentum Dependent (TMD) parton densities is discussed. Applying the Parton-Branching (PBM) method, the so-called non-perturbative Sudakov form factor could be identified with the integration range $z \to 1$, which is neglected in collinear parton shower approaches. The

Wenqiang Lai, Yuan Gao, Tin Lun Lam

There is a growing interest in applying large language models (LLMs) in robotic tasks, due to their remarkable reasoning ability and extensive knowledge learned from vast training corpora. Grounding LLMs in the physical world remains an open challenge as they can only process textual input. Recent advancements in large vision-language models (LVLMs) have ena

Shijie Zhou, Zhiwen Fan, Dejia Xu, Haoran Chang

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive 360$^{\circ}$ scenes for in-the-wild environments in a matter of minutes. Our approach utilizes the generative power of a 2D dif

Seungmo Kim

Shared situation awareness (SSA) has been garnering explosive interest in various applications for intelligent transportation systems (ITS). In addition, the delay-constrained nature of supporting vehicular networks makes it critical to precisely analyze the performance of a SSA procedure. Extending the relevant literature, this paper provides an analysis fr

Licheng Lou, Kang Yin, Jinlin Wang, Yuan Li

With the rapid development of Kesterite Cu2ZnSn(S, Se)4 solar cells in the past few years, how to achieve higher cost-performance ratio has become an important topic in the future development and industrialization of this technology. Herein, we demonstrate an all-solution route for the cell fabrication, in particular targeting at the solution processed windo

Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki

Graph neural network (GNN)-based models have been extensively studied for recommendations, as they can extract high-order collaborative signals accurately which is required for high-quality recommender systems. However, they neglect the valuable information gained through negative feedback in two aspects: (1) different users might hold opposite feedback on t

Yichun Gao, Wenyu Song, Zehao Yu, Shuai Yang

Network structures by semiconductor nanowires hold great promise for advanced quantum devices, especially for applications in topological quantum computing. In this study, we created networks of PbTe nanowires arranged in loop configurations. Using shadow-wall epitaxy, we defined superconducting quantum interference devices (SQUIDs) using the superconductor

Ye Shen, Bin Chen

It has been observed that many relativistic jets display a kind of cork-screw-like precession. Numerical simulations has suggested that such kind of precession may originate from the precession of the disk. In this work, we introduce an analytical model to describe the precession and split of a tilted, geometrically thin disk. We consider the Lense-Thirring

Diana Benea, Viorel Pop, Jan Minár

The present study focuses on the intrinsic properties of the SmFe10Co2-xVx (x = 0-2) alloys, which includes the SmFe10Co2 alloy, one of the most promising permanent magnets with the ThMn12 type of structure due to its large saturation magnetization (1.78 T), high Curie temperature (Tc = 859 K), and anisotropy field (12 T) experimentally obtained. Unfortunate

Paolo D'Agosta, Simona Achilli, Francesco Tumino, Alessio Orbelli Biroli

Graphdiyne-based carbon systems generate intriguing layered sp-sp$^2$ organometallic lattices, characterized by flexible acetylenic groups connecting planar carbon units through metal centers. At their thinnest limit, they can result in two-dimensional (2D) organometallic networks exhibiting unique quantum properties and even confining the surface states of

Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki

Recommender models aimed at mining users' behavioral patterns have raised great attention as one of the essential applications in daily life. Recent work on graph neural networks (GNNs) or debiasing methods has attained remarkable gains. However, they still suffer from (1) over-smoothing node embeddings caused by recursive convolutions with GNNs, and (2) the

Feihu Jiang, Chuan Qin, Kaichun Yao, Chuyu Fang

Efficient knowledge management plays a pivotal role in augmenting both the operational efficiency and the innovative capacity of businesses and organizations. By indexing knowledge through vectorization, a variety of knowledge retrieval methods have emerged, significantly enhancing the efficacy of knowledge management systems. Recently, the rapid advancement

Matthew Kent Myers, Nick Wright, A. Stephen McGough, Nicholas Martin

Online temporal action segmentation shows a strong potential to facilitate many HRI tasks where extended human action sequences must be tracked and understood in real time. Traditional action segmentation approaches, however, operate in an offline two stage approach, relying on computationally expensive video wide features for segmentation, rendering them un

Songcheng Li, Honghui Liu, Cosimo Bambi, James F. Steiner

Within the disk-corona model, it is natural to expect that a fraction of reflection photons from the disk are Compton scattered by the hot corona (reflection Comptonization), even if this effect is usually ignored in X-ray reflection spectroscopy studies. We study the effect by using NICER and NuSTAR data of the Galactic black hole EXO 1846-031 in the hard-i

Diankun Zhang, Guoan Wang, Runwen Zhu, Jianbo Zhao

End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system. Despite simplicity and clarity, the performance of end-to-end autonomous driving methods on sub-tasks is still far behind the single-task methods. Meanwhile, the widely used dense BEV features in previous end-to-end methods make it costly to extend to more

Zhengru Fang, Senkang Hu, Haonan An, Yuang Zhang

Surrounding perceptions are quintessential for safe driving for connected and autonomous vehicles (CAVs), where the Bird's Eye View has been employed to accurately capture spatial relationships among vehicles. However, severe inherent limitations of BEV, like blind spots, have been identified. Collaborative perception has emerged as an effective solution to

Bandita Das, Noufal Jaseem, Victor Mukherjee

We study discrete time crystals (DTCs) in periodically driven quantum systems, in the presence of non-Markovian dissipation. In contrast to DTCs observed in earlier works in the presence of Markovian dynamics, using the open Dicke model in presence of Jaynes-Cummings-like dissipation, we show that non-Markovian regime can be highly beneficial for stabilizing

Syed Emad Uddin Shubha, Mir Muzahedul Islam, Tanvir Ahahmed Sadi, Md. Hasibul Hasan Miraz

Quantum image processing is a research field that explores the use of quantum computing and algorithms for image processing tasks such as image encoding and edge detection. Although classical edge detection algorithms perform reasonably well and are quite efficient, they become outright slower when it comes to large datasets with high-resolution images. Quan

Emil Jeřábek

We axiomatize the first-order theories of exponential integer parts of real-closed exponential fields in a language with $2^x$, in a language with a predicate for powers of 2, and in the basic language of ordered rings. In particular, the last theory extends IOpen by sentences expressing the existence of winning strategies in a certain game on integers; we s

Vsevolod F. Lev

We show that for a finite, nonempty subset $A$ of a group, the quotient set $A^{-1}A:=\{a_1^{-1}a_2\colon a_1,a_2\in A\}$ has size $|A^{-1}A|\ge\frac53\,|A|$, unless $A$ is densely contained in a coset, or in a union of two cosets of a finite subgroup.

Jing-Run Lin, Linxi Lv, Zheng-Wei Zuo

The topological states of the two-leg and three-leg ladders formed by two trivial quantum wires with different lattice constants are theoretically investigated. Firstly, we take two trivial quantum wires with a lattice constant ratio of 1:2 as an example. For the symmetric nearest-neighbor intra-chain hopping two-leg ladder, the inversion symmetry protected

Atsushi Iwaki, Soshun Ozaki

Recent experiments have established negative energetic elasticity, the negative contribution of energy to the elastic modulus, as a universal property of polymer gels. To reveal the microscopic origin of this phenomenon, Shirai and Sakumichi investigated a polymer model on a cubic lattice with the energy effect from the solvent in finite-size calculations [P

Qinyi Lu, Nan Liu, Wei Kang

We investigate the demand private coded caching problem, which is an $(N,K)$ coded caching problem with $N$ files, $K$ users, each equipped with a cache of size $M$, and an additional privacy constraint on user demands. We first present a new virtual-user-based achievable scheme for arbitrary number of users and files. Then, for the case of 2 files and arbit

Jingyu Zhang, Ao Xiang, Yu Cheng, Qin Yang

With the rapid advancement of artificial intelligence technology, AI-enabled image recognition has emerged as a potent tool for addressing challenges in traditional environmental monitoring. This study focuses on the detection of floating objects in river and lake environments, exploring an innovative approach based on deep learning. By intricately analyzing

Shan Li, Sang-Sung Lee, Whee Yeon Cheong

In this paper, we conduct a multi-frequency analysis of the gamma-ray bright blazar 1308+326 from February 2013 to March 2020, using the Korean VLBI Network at 22 and 43 GHz and gamma-ray data from the Fermi Large Area Telescope (LAT). Our findings reveal spectral variations around the 2014 gamma-ray flare, aligning with the shock-in-jet model. A strong corr

Oleksandr Gamayun

For a one-dimensional system of free fermions, we derive a connection between the full counting statistics of domain-wall and alternating occupancy (N\'eel) states. This allows us to demonstrate asymptotic linear growth with time of the even cumulants in the N\'eel state

Reem Alhabib, Poonam Yadav

Autonomous systems are becoming increasingly prevalent in new vehicles. Due to their environmental friendliness and their remarkable capability to significantly enhance road safety, these vehicles have gained widespread recognition and acceptance in recent years. Automated Driving Systems (ADS) are intricate systems that incorporate a multitude of sensors an

Chaoying Huang, Wen Chen, Qingqing Wu, Nan Cheng

Unlike previous works that focused solely on passive intelligent reflecting surface (PIRS) or active IRS (AIRS), a novel joint AIRS and PIRS architecture has been developed to flexibly utilize their combined advantages in mitigating multiplicative path loss cost-effectively. In this paper, we consider the AIRS-PIRS jointly aided wireless point-to-point commu