April 2024 arXiv papers — page 110

Navid Imran, Myounggyu Won

The vehicle routing problem with drones (VRP-D) is to determine the optimal routes of trucks and drones such that the total operational cost is minimized in a scenario where the trucks work in tandem with the drones to deliver parcels to customers. While various heuristic algorithms have been developed to address the problem, existing solutions are built bas

Jose Blanchet, Wei Cai, Shaswat Mohanty, Zhenyuan Zhang

We study the first passage times of discrete-time branching random walks in ${\mathbb R}^d$ where $d\geq 1$. Here, the genealogy of the particles follows a supercritical Galton-Watson process. We provide asymptotics of the first passage times to a ball of radius one with a distance $x$ from the origin, conditioned upon survival. We provide explicitly the lin

R. A. Konoplya, A. Zhidenko

Recently, in [arXiv:2403.04827], it was demonstrated that various regular black hole metrics can be derived within a theory featuring an infinite number of higher curvature corrections to General Relativity. Moreover, truncating this infinite series at the first few orders already yields a reliable approximation of the observable characteristics of such blac

Jyotish Robin, Elza Erkip

Efficient and low-latency wireless connectivity between the base station (BS) and a sparse set of sporadically active devices from a massive number of devices is crucial for random access in emerging massive machine-type communications (mMTC). This paper addresses the challenge of identifying active devices while meeting stringent access delay and reliabilit

Navid Mohammad Imran, Myounggyu Won

The Vehicle Routing Problem with Drones (VRPD) seeks to optimize the routing paths for both trucks and drones, where the trucks are responsible for delivering parcels to customer locations, and the drones are dispatched from these trucks for parcel delivery, subsequently being retrieved by the trucks. Given the NP-Hard complexity of VRPD, numerous heuristic

Leonardo F. Toso, Han Wang, James Anderson

We address the problem of designing an LQR controller in a distributed setting, where M similar but not identical systems share their locally computed policy gradient (PG) estimates with a server that aggregates the estimates and computes a controller that, on average, performs well on all systems. Learning in a distributed setting has the potential to offer

Kshiteej J. Deshmukh

Space-time metamaterials, or materials with properties changing in space and time, have gained a wide-spread interest due to their exotic properties. In this Letter, we propose a novel temporal metasurface of phononic crystals in one and two-dimensions, that combines the use of nonlocal interactions in phononic crystals to customize dispersion relations, and

Murat Ozer, Halil Akbas, Ismail Onat, Mehmet Bastug

This study examines racial disparities in violent arrest outcomes, challenging conventional methods through a nuanced analysis of Cincinnati Police Department data. Acknowledging the intricate nature of racial disparity, the study categorizes explanations into types of place, types of person, and a combination of both, emphasizing the impact of neighborhood

Prajakta Bedekar, Rayanne A. Luke, Anthony J. Kearsley

Immune events such as infection, vaccination, and a combination of the two result in distinct time-dependent antibody responses in affected individuals. These responses and event prevalences combine non-trivially to govern antibody levels sampled from a population. Time-dependence and disease prevalence pose considerable modeling challenges that need to be a

Raul Zaharia, Dragoş Gavriluţ, Gheorghiţă Mutu, Dorel Lucanu

Cyber security attacks have become increasingly complex over time, with various phases of their kill chain, involving binaries, scripts, documents, executed commands, vulnerabilities, or network traffic. We propose a tool, GView, that is designed to investigate possible attacks by providing guided analysis for various file types using automatic artifact iden

Amir Fakhim Babaei, Thidapat Chantem

Deep Neural Networks (DNNs) are useful in many applications, including transportation, healthcare, and speech recognition. Despite various efforts to improve accuracy, few works have studied DNN in the context of real-time requirements. Coarse resource allocation and sequential execution in existing frameworks result in underutilization. In this work, we con

Yi-Lin Lee

We study the enumeration of off-diagonally symmetric domino tilings of odd-order Aztec diamonds in two directions: (1) with one boundary defect, and (2) with maximally-many zeroes on the diagonal. In the first direction, we prove a symmetry property which states that the numbers of off-diagonally symmetric domino tilings of the Aztec diamond of order $2n-1$

A. V. Nikulov

Jorge Berger shows theoretically in the paper Phys. Rev. B 109, 024501 (2024) that according to the Ginzburg-Landau theory the persistent current can create the persistent voltage, i.e. a dc voltage at thermodynamic equilibrium, on segments of nonuniform superconducting loop. A similar result was published early and was collaborated experimentally. The persi

Hossein Nemati, Joost de Graaf

The Cellular Potts model, also known as the Glazier-Graner-Hogeweg model, is a lattice-based approach by which biological tissues at the level of individual cells can be numerically studied. Traditionally, a square or hexagonal underlying lattice structure is assumed for two-dimensional systems, and this is known to introduce artifacts in the structure and d

Karen Yagdjian, Anahit Galstian

In this paper, we consider the propagation of waves in the space-time of a single black hole with a static Schwarzschild radius in the expanding universe, namely, the solutions of the linear and semilinear Klein-Gordon equations.

Bachana Anasashvili, Vahidin Jeleskovic

This paper presents a new Python library called Automated Learning for Insightful Comparison and Evaluation (ALICE), which merges conventional feature selection and the concept of inter-rater agreeability in a simple, user-friendly manner to seek insights into black box Machine Learning models. The framework is proposed following an overview of the key conce

Yussuf Ahmed, Micheal Ezealor, Haitham Mahmoud, MohamedAjmal Azad

With the advent of smart grid (SG) systems, electricity networks have been able to ensure greater efficiency and utility by interconnecting their grids through cloud-based technology. As SGs become increasingly complex, a wide range of security challenges arise, threatening the grid's reliability, safety, efficiency, and stability. The security challenges in

Yuguang Shi

Recently, iteration-based stereo matching has shown great potential. However, these models optimize the disparity map using RNN variants. The discrete optimization process poses a challenge of information loss, which restricts the level of detail that can be expressed in the generated disparity map. In order to address these issues, we propose a novel traini

Gustav Eriksson

Highly accurate simulations of problems including second derivatives on complex geometries are of primary interest in academia and industry. Consider for example the Navier-Stokes equations or wave propagation problems of acoustic or elastic waves. Current finite difference discretization methods are accurate and efficient on modern hardware, but they lack f

Gaurav Bhandari, S. D. Pathak, Manabendra Sharma, Anzhong Wang

Quantum gravity has been baffling the theoretical physicist for decades now: both for its mathematical obscurity and phenomenological testing. Nevertheless, the new era of precision cosmology presents a promising avenue to test the effects of quantum gravity. In this study, we consider a bottom-up approach. Without resorting to any candidate quantum gravity,

Wadid Foudhaili, Anouar Nechi, Celine Thermann, Mohammad Al Johmani

Intrusion detection systems (IDS) are crucial security measures nowadays to enforce network security. Their task is to detect anomalies in network communication and identify, if not thwart, possibly malicious behavior. Recently, machine learning has been deployed to construct intelligent IDS. This approach, however, is quite challenging particularly in distr

Lei Wang, Jieming Bian, Jie Xu

Distributed quantum computing (DQC) holds immense promise in harnessing the potential of quantum computing by interconnecting multiple small quantum computers (QCs) through a quantum data network (QDN). Establishing long-distance quantum entanglement between two QCs for quantum teleportation within the QDN is a critical aspect, and it involves entanglement r

Sharvi Endait, Srushti Sonavane, Ridhima Sinare, Pritika Rohera

The explosive growth of online content demands robust Natural Language Processing (NLP) techniques that can capture nuanced meanings and cultural context across diverse languages. Semantic Textual Relatedness (STR) goes beyond superficial word overlap, considering linguistic elements and non-linguistic factors like topic, sentiment, and perspective. Despite

Alberto Pérez-Cervera, Benjamin Lindner, Peter J. Thomas

The parameterization method (PM) provides a broad theoretical and numerical foundation for computing invariant manifolds of dynamical systems. PM implements a change of variables in order to represent trajectories of a system of ordinary differential equations ``as simply as possible." In this paper we pursue a similar goal for stochastic oscillator systems.

Zita Lifelo, Huansheng Ning, Sahraoui Dhelim

Timely identification is essential for the efficient handling of mental health illnesses such as depression. However, the current research fails to adequately address the prediction of mental health conditions from social media data in low-resource African languages like Swahili. This study introduces two distinct approaches utilising model-agnostic meta-lea

Rajesh Dutta, Biman Bagchi

Fluctuations in the energy gap and coupling constants in and between chromophores can play important role in the absorption and energy transfer across a collection of two level systems. In a noisy environment, fluctuations can control efficiency of energy transfer through several factors, including quantum coherence. Several recent studies have investigated

Stefan Grisard, Artur V. Trifonov, Thilo Hahn, Tilmann Kuhn

We investigate the two-pulse photon echo response of excitons in the mixed lead halide perovskite crystal \sample in dependence on the excitation intensity and polarization of the incident laser pulses. Using spectrally narrow picosecond laser pulses, we address localized excitons with long coherence times $T_2 \approx 100\,$ps. This approach offers high sen

Jia Gu, Liang Pang, Huawei Shen, Xueqi Cheng

With the rapid advancement of large language models (LLMs) for handling complex language tasks, an increasing number of studies are employing LLMs as agents to emulate the sequential decision-making processes of humans often represented as Markov decision-making processes (MDPs). The actions in MDPs adhere to specific probability distributions and require it

Munachiso Nwadike, Jialin Li, Hanan Salam

In the field of emotion recognition and Human-Machine Interaction (HMI), personalised approaches have exhibited their efficacy in capturing individual-specific characteristics and enhancing affective prediction accuracy. However, personalisation techniques often face the challenge of limited data for target individuals. This paper presents our work on an enh

Won Ik Cho, Eunjung Cho, Hyeonji Shin

Generative artificial intelligence (AI) and large language models (LLMs) are increasingly being used in the academic writing process. This is despite the current lack of unified framework for reporting the use of machine assistance. In this work, we propose "Cardwriter", an intuitive interface that produces a short report for authors to declare their use of

Guillermo Nuñez Ponasso

This doctoral thesis covers several topics related to the construction and study of maximal determinant matrices with complex entries. The first three chapters are devoted to number-theoretic tools to prove the non-solvability of Gram matrix equations over certain fields, with a focus on combinatorial applications. Chapter 4 gives a survey on Butson-type Had

Dorota Celinska-Kopczynska, Eryk Kopczynski

Hyperbolic geometry has recently found applications in social networks, machine learning and computational biology. With the increasing popularity, questions about the best representations of hyperbolic spaces arise, as each representation comes with some numerical instability. This paper compares various 2D and 3D hyperbolic geometry representations. To thi

Tekwam Geremew, Maedeh Taheri, Nicholas Sesing, Subhajit Ghosh

We report on the solution processing and testing of electronic ink comprised of quasi-one-dimensional NbS$_3$ charge-density-wave fillers. The ink was prepared by liquid-phase exfoliation of NbS$_3$ crystals into high-aspect ratio quasi-1D fillers dispersed in a mixture of isopropyl alcohol and ethylene glycol solution. The results of the electrical measurem

Zengjie Zhang, Zhiyong Sun, Sofie Haesaert

This paper develops a correct-by-design controller for an autonomous vehicle interacting with opponent vehicles with unknown intentions. We define an intention-aware control problem incorporating epistemic uncertainties of the opponent vehicles and model their intentions as discrete-valued random variables. Then, we focus on a control objective specified as

Abdelmalek Bouzenada, Abdelamlek Boumali, Faizuddin Ahmed

In this paper, we employ the Generalized Feshbach-Villars transformation (GFVT) to investigate the relativistic quantum dynamics of spin-0 scalar particles within the backdrop of a magnetic universe characterized by the Bonnor-Melvin cosmological space-time, which exhibits a geometrical topology resulting in an angular deficit. We derive the radial equation

Andreas Ringwald

This proceedings' contribution explores the rationale behind the axion as a resolution to the strong CP puzzle. It outlines various benchmark axion models and examines their implications, focusing on two key aspects: (i) the axion's interactions with the Standard Model particles, and (ii) its potential role as dark matter. Additionally, it provides an overvi

Jérémie Pierard de Maujouy

We study the Hessian geometry associated with an ideal gas in a spherical centrifuge. According to Souriau, a spherically confined ideal gas admit states of thermal and rotational equilibrium. These states, called Gibbs states, form an exponential family with an action of the Euclidean rotation group. We investigate its Hessian (Fisher-Rao) geometry and show

Gabriel D. Weymouth, Marin Lauber

We introduce a novel boundary condition for incompressible Eulerian simulations formulated using a Biot-Savart vorticity integral that maintains high-accuracy results even when the domain boundary is within a body-length of immersed solid boundaries. The key prerequisite to accurately couple the Biot-Savart condition to the Eulerian velocity and pressure fie

Richard Zach

Logic has pride of place in mathematics and its 20th century offshoot, computer science. Modern symbolic logic was developed, in part, as a way to provide a formal framework for mathematics: Frege, Peano, Whitehead and Russell, as well as Hilbert developed systems of logic to formalize mathematics. These systems were meant to serve either as themselves found

Maria Manuel Clementino, Dirk Hofmann, Walter Tholen

Building on the notion of normed category as suggested by Lawvere, we introduce notions of Cauchy convergence and cocompleteness which differ from proposals in previous works. Key to our approach is to treat them consequentially as categories enriched in the monoidal-closed category of normed sets. Our notions largely lead to the anticipated outcomes when co

Maxim Vavilin, Carsten Rockstuhl, Ivan Fernandez-Corbaton

Many physically interesting quantities of the electromagnetic field can be computed using the electromagnetic scalar product. However, none of the existing expressions for such scalar product are directly applicable when the fields are only known in a spatially-bounded domain, as is the case for many numerical Maxwell solvers. In here, we derive an expressio

Meghana Velegar, Christoph Keller, J. Nathan Kutz

We introduce the optimized dynamic mode decomposition algorithm for constructing an adaptive and computationally efficient reduced order model and forecasting tool for global atmospheric chemistry dynamics. By exploiting a low-dimensional set of global spatio-temporal modes, interpretable characterizations of the underlying spatial and temporal scales can be

Bruce D. Lee, Ingvar Ziemann, George J. Pappas, Nikolai Matni

Model-based reinforcement learning is an effective approach for controlling an unknown system. It is based on a longstanding pipeline familiar to the control community in which one performs experiments on the environment to collect a dataset, uses the resulting dataset to identify a model of the system, and finally performs control synthesis using the identi

Maedeh Jamali, Nader Karimi, Shadrokh Samavi, Shahram Shirani

Over the past two decades, the surge in video streaming applications has been fueled by the increasing accessibility of the internet and the growing demand for network video. As users with varying internet speeds and devices seek high-quality video, transcoding becomes essential for service providers. In this paper, we introduce a parametric rate-distortion

Weishan Zhu, Tian-Rui Wang, Fupeng Zhang, Yi Zheng

Large-scale cosmic filaments may have played an important role in shaping the properties of galaxies. Meanwhile, cosmic filaments are believed to harbor a substantial portion of the missing baryons at redshift z < 2. To inspect the role of filaments in these issues, many properties of filaments need to be examined, including their lengths, thicknesses, and d

Yusheng Liao, Shuyang Jiang, Yu Wang, Yanfeng Wang

Large language models like ChatGPT have shown substantial progress in natural language understanding and generation, proving valuable across various disciplines, including the medical field. Despite advancements, challenges persist due to the complexity and diversity inherent in medical tasks which often require multi-task learning capabilities. Previous app

Farzin Renan, Péter Kutas

Adaptor signatures can be viewed as a generalized form of standard digital signature schemes by linking message authentication to the disclosure of a secret value. As a recent cryptographic primitive, they have become essential for blockchain applications, including cryptocurrencies, by reducing on-chain costs, improving fungibility, and enabling off-chain p

Livia Corsi, Guido Gentile, Michela Procesi

We study the existence of infinite-dimensional invariant tori in a mechanical system of infinitely many rotators weakly interacting with each other. We consider explicitly interactions depending only on the angles, with the aim of discussing in a simple case the analyticity properties to be required on the perturbation of the integrable system in order to en

Anjali Purathekandy, Meera Anna Oommen, Martin Wikelski, Deepak N Subramani

Human-wildlife conflict challenges conservation worldwide, which requires innovative management solutions. We developed a prototype Agent-Based Model (ABM) to simulate interactions between humans and solitary bull Asian elephants in the Periyar-Agasthyamalai complex of the Western Ghats in Kerala, India. The main challenges were the complex behavior of eleph

Shayan Zahedi

A novel result in $\mathbb Z_2$-equivariant homotopy theory is stated, proven, and applied to the topological classification of classically frustrated magnets in the presence of canonical time-reversal symmetry. This result generalizes a lemma that had been key to the homotopical derivation of the renowned Bott-Kitaev periodic table for topological insulator

Benjue Weng

With the surge of ChatGPT,the use of large models has significantly increased,rapidly rising to prominence across the industry and sweeping across the internet. This article is a comprehensive review of fine-tuning methods for large models. This paper investigates the latest technological advancements and the application of advanced methods in aspects such a

Ilja Doršner, Shaikh Saad

We demonstrate that it is not necessary to substantially break the mass degeneracy between the Standard Model Higgs boson doublet and the corresponding scalar leptoquark, where these two fields comprise a single five-dimensional $SU(5)$ representation. More precisely, we show that the experimental data on partial proton decay lifetimes cannot place any meani

Zhenbin Cao, Changxing Miao, Yixuan Pang

The Fourier restriction conjecture is a fundamental problem in harmonic analysis. In this paper, we investigate restriction estimates for degenerate higher codimensional quadratic surfaces and obtain sharp results for some types of degenerate cases. A major obstacle in establishing sharp restriction estimates is the failure of rescaling invariance, which is

Yuming Chen, Vitali Vougalter

In this paper, we consider an integro-differential equation in L^2(R), which involves the logarithmic Laplacian in the presence of a drift term. The linear operator associated with the problem has the Fredholm property. By using a fixed point technique, we establish the existence of solutions.

Branislav Boričić

The traditional Arrow--Sen Social Choice Theory $\bf{TSCT}$ is a mathematical theory built apparently on higher--order formal language. In this paper, we propose a reformulation and reclassification of the $\bf{TSCT}$ axioms in order to obtain a simpler theory based on the first--order language axioms, keeping the spirit of original ideas. This new theory, c

Feihu Jiang, Chuan Qin, Jingshuai Zhang, Kaichun Yao

In the contemporary era of widespread online recruitment, resume understanding has been widely acknowledged as a fundamental and crucial task, which aims to extract structured information from resume documents automatically. Compared to the traditional rule-based approaches, the utilization of recently proposed pre-trained document understanding models can g

Yaakov Malinovsky, Isaac M. Sonin

We present a variation of the water puzzle, which is related to a simple model of marginal utility. The problem has an intriguing solution and can be extended in several directions.

Hamidreza Esmaielpour, Nabi Isaev, Jonathan J. Finley, Gregor Koblmüller

Understanding the origin of hot carrier relaxation in nanowires (NWs) with one-dimensional (1D) geometry is significant for designing efficient hot carrier solar cells with such nanostructures. Here, we study the influence of Auger heating and Shockley-Read-Hall recombination on hot carrier dynamics of catalyst-free InGaAs-InAlAs core-shell NWs. Using steady

Melike Nur Yeğin, Mehmet Fatih Amasyalı

Generative diffusion models showed high success in many fields with a powerful theoretical background. They convert the data distribution to noise and remove the noise back to obtain a similar distribution. Many existing reviews focused on the specific application areas without concentrating on the research about the algorithm. Unlike them we investigated th

C. Scarlata, M. Hayes, N. Panagia, V. Mehta

In an ongoing search for low-mass extreme emission line galaxies, we identified a galaxy with a Ha/Hb Balmer line ratio of 2.620 +- 0.078. Ha/Hb Balmer ratios lower than the dust-free Case~B value appear relatively frequently in extreme emission line galaxies. These low values suggest that the Case~B assumption may not be valid in these objects. After ruling

Cheng-Yang Lee

In the Lounesto classification, there are three types of regular spinors. They are classified by the condition that at least one of the scalar or pseudo scalar norms are non-vanishing. The Dirac spinors are regular spinors because their scalar and pseudo scalar norms are non-zero and zero respectively. We construct local and Lorentz-covariant fermionic field

Khoi Le Nguyen Nguyen, Xavier Buffat, Peter Kicsiny, Tatiana Pieloni

An analytical investigation of beamstrahlung-induced blow-up in Gaussian beams with arbitrary dimensions is presented, using various approximations for the strength of the hourglass effect and crab waist scheme. The results, applied to the FCC-ee resonances, are compared with simulations and previous calculations, and relative luminosity values are also calc

Zining Chen, Weiqiu Wang, Zhicheng Zhao, Fei Su

Domain Generalization (DG) aims to resolve distribution shifts between source and target domains, and current DG methods are default to the setting that data from source and target domains share identical categories. Nevertheless, there exists unseen classes from target domains in practical scenarios. To address this issue, Open Set Domain Generalization (OS

Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj

Dynamic Facial Expression Recognition (DFER) has received significant interest in the recent years dictated by its pivotal role in enabling empathic and human-compatible technologies. Achieving robustness towards in-the-wild data in DFER is particularly important for real-world applications. One of the directions aimed at improving such models is multimodal

Anwesh Ray

Given a prime $p\geq 5$, a conjecture of Greenberg predicts that the $\mu$-invariant of the $p$-primary Selmer group should vanish for most elliptic curves with good ordinary reduction at $p$. In support of this conjecture, I show that the $5$-primary Iwasawa $\mu$- and $\lambda$-invariants simultaneously vanish for an explicit positive density of elliptic c

Qiang Jiang, Stephanie Atampugre, Yipu Du, Lingyu Yang

Heterogeneous multilayered solid-state electrolyte (HMSSE) has been widely explored for their broadened working voltage range and compatibility with electrodes. However, due to the limitations of traditional manufacturing methods such as casting, the interface between electrolyte layers in HMSSE can decrease the ionic conductivity severely. Here, a novel com

Taoran Wu, Yiqing Yu, Bican Xia, Ji Wang

Ensuring safety through set invariance has proven to be a valuable method in various robotics and control applications. This paper introduces a comprehensive framework for the safe probabilistic invariance verification of both discrete- and continuous-time stochastic dynamical systems over an infinite time horizon. The objective is to ascertain the lower and

Tetsuo Nishikawa, Yoshihiko Kondo, Yoshiko Kanada-En'yo

QCD sum rules for positive and negative parity heavy baryons in the heavy quark limit are formulated. We apply the method to $\Lambda$ and $\Sigma$ channels. We include the next-to-leading order corrections in $\alpha_s$-expansion to dimension 0 and 3 terms in the operator product expansion. The corrections lead to the considerable reduction of the predicted

Zishuo Zhao, Zhixuan Fang, Xuechao Wang, Xi Chen

Most concurrent blockchain systems rely heavily on the Proof-of-Work (PoW) or Proof-of-Stake (PoS) mechanisms for decentralized consensus and security assurance. However, the substantial energy expenditure stemming from computationally intensive yet meaningless tasks has raised considerable concerns surrounding traditional PoW approaches, The PoS mechanism,

Serhii Bardyla, Peter Nyikos, Lyubomyr Zdomskyy

In this paper, we show that the existence of certain first-countable compact-like extensions is equivalent to the equality between corresponding cardinal characteristics of the continuum. For instance, $\mathfrak b=\mathfrak s=\mathfrak c$ if and only if every regular first-countable space of weight $< \mathfrak c$ can be densely embedded into a regular firs

Yingjie Zhou, Zicheng Zhang, Wei Sun, Xiaohong Liu

In the realm of media technology, digital humans have gained prominence due to rapid advancements in computer technology. However, the manual modeling and control required for the majority of digital humans pose significant obstacles to efficient development. The speech-driven methods offer a novel avenue for manipulating the mouth shape and expressions of d

Hayato Tsukagoshi, Tsutomu Hirao, Makoto Morishita, Katsuki Chousa

The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstream tasks in natural language processing (NLP). However, while Split and Rephrase can be improved using a text-to-text generation approach that applies encoder-decoder models fine-tu

Zhihao Cao, Zidong Wang, Siwen Xie, Anji Liu

Despite the significant demand for assistive technology among vulnerable groups (e.g., the elderly, children, and the disabled) in daily tasks, research into advanced AI-driven assistive solutions that genuinely accommodate their diverse needs remains sparse. Traditional human-machine interaction tasks often require machines to simply help without nuanced co

Yingjie Xi, Boyuan Cheng, Jingyao Cai, Jian Jun Zhang

The human whole-body X-rays could offer a valuable reference for various applications, including medical diagnostics, digital animation modeling, and ergonomic design. The traditional method of obtaining X-ray information requires the use of CT (Computed Tomography) scan machines, which emit potentially harmful radiation. Thus it faces a significant limitati

Paul H. Frampton

To describe the dark side of the Universe, we adopt a novel approach where dark energy is explained as an electrically charged majority of dark matter. Dark energy, as such, does not exist. The Friedmann equation at the present time coincides with that in a conventional approach, although the cosmological "constant" in the Electromagnetic Accelerating Univer

Ruixin Tang, Ziyu Luo, Pengfei Li, Pengrun Ying

Dual-comb spectroscopy typically requires the utilization of two independent and phase-locked femtosecond lasers, resulting in a complex and expensive system that hinders its industrial applications. Single-cavity dual-comb lasers are considered as one of the primary solution to simplify the system. However, controlling the crucial parameter of difference in

Ryan Cotterell, Thomas Müller, Alexander Fraser, Hinrich Schütze

We present labeled morphological segmentation, an alternative view of morphological processing that unifies several tasks. From an annotation standpoint, we additionally introduce a new hierarchy of morphotactic tagsets. Finally, we develop \modelname, a discriminative morphological segmentation system that, contrary to previous work, explicitly models morph

Shokhzod Kurokboev

The aim of this elaborate is presenting the classical symmetric tensors completion problem to an audience of graduate students. As main studying tool, we will introduce the theory of hypergraph rigidity which naturally mirrors the problem itself. This has already appeared in literature: in 2023, Cruicksand, Mohammadi, Nixon, and Tanigawa introduced organical

Ye Wang, Yaxiong Wang, Yujiao Wu, Bingchen Zhao

Generalized Class Discovery (GCD) aims to dynamically assign labels to unlabelled data partially based on knowledge learned from labelled data, where the unlabelled data may come from known or novel classes. The prevailing approach generally involves clustering across all data and learning conceptions by prototypical contrastive learning. However, existing m

William J. Crilly

Extraterrestrial communication signals are hypothesized to be present in an extensive search space. Using principles of communication theory and system design, methods are studied and implemented to reduce the signal search space, while considering intentional transmitter detectability. The design and observational work reported in this paper adds material t

Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis, Avishek Nag

This work focuses on optimizing the hybrid quantum noise model to improve the capacity of Gaussian quantum channels using Machine Learning (ML) generated clusters. The work specifically leverages Gaussian Mixture Model (GMM) and the Expectation-Maximization (EM) algorithm to model the complex noise characteristics of quantum channels. Hybrid quantum noise, w

Nicolás A. Loubet, Alejandro R. Verde, Gustavo A. Appignanesi

In a recent work we have briefly introduced a new structural index for water that, unlike previous indicators, was devised specifically for generic contexts beyond bulk conditions, making it suitable for hydration and nanoconfinement settings. In this work we shall study this metric in detail, demonstrating its ability to reveal the existence of a fine-tuned

Evangelos Katsamakas

The simulation hypothesis suggests that we live in a computer simulation. That notion has attracted significant scholarly and popular interest. This article explores the simulation hypothesis from a business perspective. Due to the lack of a name for a universe consistent with the simulation hypothesis, we propose the term simuverse. We argue that if we live

Zezhao Guo, Yanzhong Guo, Zhanfang Zhao

Navigation for thoracoabdominal puncture surgery is used to locate the needle entry point on the patient's body surface. The traditional reflective ball navigation method is difficult to position the needle entry point on the soft, irregular, smooth chest and abdomen. Due to the lack of clear characteristic points on the body surface using structured light t

Dmitrii Mints

We prove that in the space of $C^r$ maps $(r=2,\ldots,\infty,\omega)$ of a smooth manifold of dimension at least 4 there exist open regions where maps with infinitely many corank-2 homoclinic tangencies of all orders are dense. The result is applied to show the existence of maps with universal two-dimensional dynamics, i.e. maps whose iterations approximate

Jiangyu Zhao, Yangyang Feng, Ying Dai, Baibiao Huang

Engineering valley index is essential and highly sought for valley physics, but currently it is exclusively based on the paradigm of the challenging ferrovalley with spin-orientation reversal under magnetic field. Here, an alternative strategy, i.e., the so-called ferroelectrovalley, is proposed to tackle the insurmountable spin-orientation reversal, which r

Mario Lins, René Mayrhofer, Michael Roland, Daniel Hofer

An emerging supply-chain attack due to a backdoor in XZ Utils has been identified. The backdoor allows an attacker to run commands remotely on vulnerable servers utilizing SSH without prior authentication. We have started to collect available information with regards to this attack to discuss current mitigation strategies for such kinds of supply-chain attac

Eric Price, Aamir Ahmad

Using UAVs for wildlife observation and motion capture offers manifold advantages for studying animals in the wild, especially grazing herds in open terrain. The aerial perspective allows observation at a scale and depth that is not possible on the ground, offering new insights into group behavior. However, the very nature of wildlife field-studies puts trad

Rongyu Zhang, Yijiang Liu, Huanrui Yang, Shenli Zheng

Large language models (LLMs) encounter significant adaptation challenges in diverse multitask finetuning. Mixture-of-experts (MoE) provides a promising solution with a dynamic architecture, enabling effective task decoupling. However, scaling up the number of MoE experts incurs substantial parameter and computational overheads and suffers from limited perfor

Xuanye Wang

We study the theoretical consequence of p-hacking on the accumulation of knowledge under the framework of mis-specified Bayesian learning. A sequence of researchers, in turn, choose projects that generate noisy information in a field. In choosing projects, researchers need to carefully balance as projects generates big information are less likely to succeed.

Matteo Casarosa

The derived functors $\lim^n$ of the inverse limit are widely studied for their topological applications, among which are some repercussions on the additivity of strong homology. Set theory has proven useful in dealing with these functors, for instance in the case of the inverse system $\mathbf{A}$ of abelian groups indexed by ${}^\omega \omega$. So far, con

Xiao-Rong Ma, Shuai Sun, Rong An, Li-Gang Cao

A correlation between the charge radii difference of mirror partner nuclei $\Delta{R_{\mathrm{ch}}}$ and the slope parameter $L$ of symmetry energy has been built to ascertain the equation of state of isospin asymmetric nuclear matter. In this work, the influences of pairing correlations and isoscalar compression modulus on the $\Delta{R_{\mathrm{ch}}}$ are

Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch

Deep active learning (AL) seeks to minimize the annotation costs for training deep neural networks. BAIT, a recently proposed AL strategy based on the Fisher Information, has demonstrated impressive performance across various datasets. However, BAIT's high computational and memory requirements hinder its applicability on large-scale classification tasks, res

Xiwei Cheng, Kexin Fu, Farzan Farnia

While adversarial training methods have significantly improved the robustness of deep neural networks against norm-bounded adversarial perturbations, the generalization gap between their performance on training and test data is considerably greater than that of standard empirical risk minimization. Recent studies have aimed to connect the generalization prop

Jian Zhang, Ruiteng Zhang, Xinyue Yan, Xiting Zhuang

Degraded underwater images decrease the accuracy of underwater object detection. However, existing methods for underwater image enhancement mainly focus on improving the indicators in visual aspects, which may not benefit the tasks of underwater image detection, and may lead to serious degradation in performance. To alleviate this problem, we proposed a bidi

Chenming Shang, Shiji Zhou, Hengyuan Zhang, Xinzhe Ni

Concept Bottleneck Models (CBMs) map the black-box visual representations extracted by deep neural networks onto a set of interpretable concepts and use the concepts to make predictions, enhancing the transparency of the decision-making process. Multimodal pre-trained models can match visual representations with textual concept embeddings, allowing for obtai

Shun Zhang, Chaoran Yan, Jian Yang, Changyu Ren

New Intent Discovery (NID) strives to identify known and reasonably deduce novel intent groups in the open-world scenario. But current methods face issues with inaccurate pseudo-labels and poor representation learning, creating a negative feedback loop that degrades overall model performance, including accuracy and the adjusted rand index. To address the afo

Mats Gustafsson

Electromagnetic degrees of freedom are instrumental in antenna design, wireless communications, imaging, and scattering. Larger number of degrees of freedom enhances control in antenna design, influencing radiation patterns and directivity, while in communication systems, it links to spatial channels for increased data rates and reliability, and resolution i

Teruo Nagase, Akiko Shima

Charts are oriented labeled graphs in a disk. Any simple surface braid (2-dimensional braid) can be described by using a chart. Also, a chart represents an oriented closed surface embedded in 4-space. In this paper, we investigate embedded surfaces in 4-space by using charts. In this paper, we shall show that there is no minimal chart with exactly seven whit

Yanjun Sheng, Yuan-Sen Ting, Xiang-Xiang Xue, Jiang Chang

The gravitational interactions between the LMC and the Milky Way cause dynamical perturbations in the MW halo, leading to biased distributions of stellar density and kinematics. We run 50 high-resolution N-body simulations exploring varying masses and halo shapes of the MW and LMC to study the evolution of LMC-induced perturbations. By measuring mean velocit