July 2023 arXiv papers — page 51

Abdulrahman A. Ahmed, M. Amin Rahimian, Mark S. Roberts

Computational models help decision makers understand epidemic dynamics to optimize public health interventions. Agent-based simulation of disease spread in synthetic populations allows us to compare and contrast different effects across identical populations or to investigate the effect of interventions keeping every other factor constant between ``digital t

Alexei Lisitsa, Mateo Salles, Alexei Vernitski

We use machine learning to classify examples of braids (or flat braids) as trivial or non-trivial. Our ML takes form of supervised learning using neural networks (multilayer perceptrons). When they achieve good results in classification, we are able to interpret their structure as mathematical conjectures and then prove these conjectures as theorems. As a re

Shuwa Miura

We consider the expressivity of Markov rewards in sequential decision making under uncertainty. We view reward functions in Markov Decision Processes (MDPs) as a means to characterize desired behaviors of agents. Assuming desired behaviors are specified as a set of acceptable policies, we investigate if there exists a scalar or multidimensional Markov reward

David Freire-Obregón, Javier Lorenzo-Navarro, Oliverio J. Santana, Daniel Hernández-Sosa

We present a transfer learning analysis on a sporting environment of the expanded 3D (X3D) neural networks. Inspired by action quality assessment methods in the literature, our method uses an action recognition network to estimate athletes' cumulative race time (CRT) during an ultra-distance competition. We evaluate the performance considering the X3D, a fam

Andrei M. Beloborodov

We investigate how a fast radio burst (FRB) emitted near a magnetar would propagate through its surrounding dipole magnetosphere at radii $r=10^7$-$10^9$ cm. First, we show that a GHz burst emitted in the O-mode with luminosity $L\gg 10^{40}$ erg/s is immediately damped for all propagation directions except a narrow cone along the magnetic axis. Then we exam

Steven Rose

This paper aims to provide an explanatory edition of Bolyai's 'Appendix Demonstrating the Absolute Science of Space', first published in 1832. In this treatise Bolyai began by extending neutral (or 'absolute') geometry by deriving a number of theorems which are independent of Euclid's parallel postulate. Then, while retaining Euclid first four postulates, he

Jahid Hasan

Federated Learning (FL) has emerged as a promising approach to address data privacy and confidentiality concerns by allowing multiple participants to construct a shared model without centralizing sensitive data. However, this decentralized paradigm introduces new security challenges, necessitating a comprehensive identification and classification of potentia

Yafei Zhang, Zhiyuan Li, Huafeng Li, Dapeng Tao

For multi-modal magnetic resonance (MR) brain tumor image segmentation, current methods usually directly extract the discriminative features from input images for tumor sub-region category determination and localization. However, the impact of information aliasing caused by the mutual inclusion of tumor sub-regions is often ignored. Moreover, existing method

Filipos Gouidis, Konstantinos Papoutsakis, Theodore Patkos, Antonis Argyros

We investigate the problem of Object State Classification (OSC) as a zero-shot learning problem. Specifically, we propose the first Object-agnostic State Classification (OaSC) method that infers the state of a certain object without relying on the knowledge or the estimation of the object class. In that direction, we capitalize on Knowledge Graphs (KGs) for

Juan Carlos Sampedro

The present article describes the precise structure of the $L^{p}$-spaces of projective limit measures by introducing a category theoretical perspective. This analysis is applied to measures on vector spaces and in particular to Gaussian measures on nuclear topological vector spaces. A simple application to constructive Quantum Field Theory (QFT) is given th

Zhiqian Gui, Zhenming Zhang, Jin Su, Hao Lyu

In a trapped spin-1/2 Bose-Einstein condensate with miscible interactions, a two-dimensional spin-orbit coupling can introduce an unconventional spatial separation between the two components. We reveal the physical mechanism of such a spin-orbit-coupling-induced phase separation. Detailed features of the phase separation are identified in a trapped Bose-Eins

Steven Kelk, Ruben Meuwese

Given a set $X$ of species, a phylogenetic tree is an unrooted binary tree whose leaves are bijectively labelled by $X$. Such trees can be used to show the way species evolve over time. One way of understanding how topologically different two phylogenetic trees are, is to construct a minimum-size agreement forest: a partition of $X$ into the smallest number

Subham De

The study of \textit{Dedekind Zeta Functions} over a number field extension uses different aspects of both \textit{Algebraic} and \textit{Analytic Number Theory}. In this paper, we shall learn about the structure and different analytic aspects of such functions, namely the domain of its convregence and analyticity at different points of $\mathbb{C}$ when the

Joshua A Kable, Giampaolo Benevento, Graeme E Addison, Charles L Bennett

In this followup analysis, we update previous constraints on the Transitional Planck Mass (TPM) modified gravity model using the latest version of EFTCAMB and provide new constraints using SPT and Planck anisotropy data along with Planck CMB lensing, BAO, SNe Ia, and an $H_0$ prior from local measurements. We find that large shifts in the Planck mass lead to

Mayank Kejriwal

Entity Resolution (ER) is the problem of determining when two entities refer to the same underlying entity. The problem has been studied for over 50 years, and most recently, has taken on new importance in an era of large, heterogeneous 'knowledge graphs' published on the Web and used widely in domains as wide ranging as social media, e-commerce and search.

Stefan Thalhammer, Dominik Bauer, Peter Hönig, Jean-Baptiste Weibel

Object pose estimation is a core perception task that enables, for example, object grasping and scene understanding. The widely available, inexpensive and high-resolution RGB sensors and CNNs that allow for fast inference based on this modality make monocular approaches especially well suited for robotics applications. We observe that previous surveys on obj

Quazi Mishkatul Alam, Israat Haque, Nael Abu-Ghazaleh

Video analytics are often performed as cloud services in edge settings, mainly to offload computation, and also in situations where the results are not directly consumed at the video sensors. Sending high-quality video data from the edge devices can be expensive both in terms of bandwidth and power use. In order to build a streaming video analytics pipeline

Jayanth Mokkapati

In recent years, electronic nose devices have become a popular approach for identifying respiratory disorders including lung cancer. Traditional e-nose systems have had very consistent principles and patterns of sensor responses. After coming to the realization that detecting cancer at early stages can save 99 percent of lives, it has become imperative to de

Weiyang Wang, Manya Ghobadi, Kayvon Shakeri, Ying Zhang

This paper presents a low-cost network architecture for training large language models (LLMs) at hyperscale. We study the optimal parallelization strategy of LLMs and propose a novel datacenter network design tailored to LLM's unique communication pattern. We show that LLM training generates sparse communication patterns in the network and, therefore, does n

Jing Wu, Jennifer Hobbs, Naira Hovakimyan

Contrastive learning models based on Siamese structure have demonstrated remarkable performance in self-supervised learning. Such a success of contrastive learning relies on two conditions, a sufficient number of positive pairs and adequate variations between them. If the conditions are not met, these frameworks will lack semantic contrast and be fragile on

Mengdi Sun, Marko Lončar, Vassilios Kovanis, Zin Lin

We propose an on-chip all-optical gyroscope based on nonlinear multi-resonant cavity quantum photonics in thin film $\chi^{(2)}$ resonators -- Quantum-Optic Nonlinear Gyro or QONG in short. The key feature of our gyroscope is co-arisal and co-accumulation of quantum correlations, nonlinear wave mixing and non-inertial signals, all inside the same sensor-reso

Kadhim Hayawi, Sakib Shahriar, Sujith Samuel Mathew

The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become a significant task. This paper presents a comparative study, introducing a novel dataset of human-written and LLM-gener

Dongming Li, James Kestyn, Eric Polizzi

We introduce a practical and efficient approach for calculating the all-electron full potential bandstructure in real space, employing a finite element basis. As an alternative to the k-space method, the method involves the self-consistent solution of the Kohn-Sham equation within a larger finite system that encloses the unit-cell. It is based on the fact th

Fritz Gesztesy, Lance L. Littlejohn, Mateusz Piorkowski, Jonathan Stanfill

We offer a detailed treatment of spectral and Weyl-Titchmarsh-Kodaira theory for all self-adjoint Jacobi operator realizations of the differential expression \begin{align*} \tau_{\alpha,\beta} = - (1-x)^{-\alpha} (1+x)^{-\beta}(d/dx) \big((1-x)^{\alpha+1}(1+x)^{\beta+1}\big) (d/dx),& \\ \alpha, \beta \in \mathbb{R}, \; x \in (-1,1),& \end{align*} in $L^2\big

F. Matuszewski, N. Nettelmann, J. Cabrera, A. Börner

The PLATO mission is scheduled for launch in 2026. This study aims to estimate the number of exoplanets that PLATO can detect as a function of planetary size and period, stellar brightness, and observing strategy options. Deviations from these estimates will be informative of the true occurrence rates of planets, which helps constraining planet formation mod

Giuseppe Cocco, Albert Guillén i Fàbregas, Josep Font-Segura

We show that for a wide range of channels and code ensembles with pairwise-independent codewords, with probability tending to 1 with the code length, expurgating an arbitrarily small fraction of codewords from a randomly selected code results in a code attaining the expurgated exponent.

Marcos Escobar-Anel, Yiyao Jiao

This paper proposes an expected multivariate utility analysis for ESG investors in which green stocks, brown stocks, and a market index are modeled in a one-factor, CAPM-type structure. This setting allows investors to accommodate their preferences for green investments according to proper risk aversion levels. We find closed-form solutions for optimal alloc

Kelvin F Long

The Breakthrough Initiatives Project Starshot proposes to send a gram-scale laser driven spacecraft to the Alpha Centauri system in a 20 year mission travelling at v=0.2c. One of the challenges of this mission as the spacecraft moves through the interstellar medium is the presence of dust and gas (mostly hydrogen). The dust has a typical matter-density of 2.

Nícolas Barbosa Gomes, Arissa Yoshida, Mateus Roder, Guilherme Camargo de Oliveira

Identifying Amyotrophic Lateral Sclerosis (ALS) in its early stages is essential for establishing the beginning of treatment, enriching the outlook, and enhancing the overall well-being of those affected individuals. However, early diagnosis and detecting the disease's signs is not straightforward. A simpler and cheaper way arises by analyzing the patient's

Ellen Novoseller, Vinicius G. Goecks, David Watkins, Josh Miller

In machine learning for sequential decision-making, an algorithmic agent learns to interact with an environment while receiving feedback in the form of a reward signal. However, in many unstructured real-world settings, such a reward signal is unknown and humans cannot reliably craft a reward signal that correctly captures desired behavior. To solve tasks in

Stefan Schoepf, Jack Foster, Alexandra Brintrup

Organisations often struggle to identify the causes of change in metrics such as product quality and delivery duration. This task becomes increasingly challenging when the cause lies outside of company borders in multi-echelon supply chains that are only partially observable. Although traditional supply chain management has advocated for data sharing to gain

Christos Christodoulou, Nikos Salamanos, Pantelitsa Leonidou, Michail Papadakis

Misinformation on YouTube is a significant concern, necessitating robust detection strategies. In this paper, we introduce a novel methodology for video classification, focusing on the veracity of the content. We convert the conventional video classification task into a text classification task by leveraging the textual content derived from the video transcr

Guo-yuan Huang

The in-ice or in-water Cherenkov neutrino telescope such as IceCube has already proved its power in measuring the Glashow resonance by searching for the bump around $E^{}_{\rm \nu} = 6.3~{\rm PeV}$ arising from the $W$-boson production. In the next few decades, there are many proposals that observe cosmic tau neutrinos with extensive air showers, also known

Zhaoyuan He, Yifan Yang, Lili Qiu, Kyoungjun Park

As mobile devices become increasingly popular for video streaming, it's crucial to optimize the streaming experience for these devices. Although deep learning-based video enhancement techniques are gaining attention, most of them cannot support real-time enhancement on mobile devices. Additionally, many of these techniques are focused solely on super-resolut

Abbas Zohrevand, Zahra Imani, Javad Sadri, Ching Y. Suen

Most of the methods on handwritten recognition in the literature are focused and evaluated on Black and White (BW) image databases. In this paper we try to answer a fundamental question in document recognition. Using Convolutional Neural Networks (CNNs), as eye simulator, we investigate to see whether color modalities of handwritten digits and words affect t

Putri A. van der Linden, David W. Romero, Erik J. Bekkers

Neural operations that rely on neighborhood information are much more expensive when deployed on point clouds than on grid data due to the irregular distances between points in a point cloud. In a grid, on the other hand, we can compute the kernel only once and reuse it for all query positions. As a result, operations that rely on neighborhood information sc

Ibrahim Shaer, Abdallah Shami

The Federated Learning (FL) paradigm faces several challenges that limit its application in real-world environments. These challenges include the local models' architecture heterogeneity and the unavailability of distributed Internet of Things (IoT) nodes due to connectivity problems. These factors posit the question of "how can the available models fill the

Avijit Lahiri

We look into the ontology of quantum theory as distinct from that of the classical theory in the sciences, following a broadly Kantian tradition and distinguishing between the noumenal and phenomenal realities where the former is independent of our perception while the latter is assembled from the former by means of fragmentary bits of interpretation. Within

Ansrey Katts, Vladimir Kulinskii

In this paper we apply fluid-lattice gas global isomorphism approach to liquid-vapor equilibrium of Yukawa attractive fluid in the two dimensions. The construction of tangent to the binodal of the fluid in the low-temperature region is performed based on the Zeno-element. The dependence of Zeno-element and Boyle parameters on interaction parameters is also s

Vedanta Thapar

We explore the use of Physics Informed Neural Networks to analyse nonlinear Hamiltonian Dynamical Systems with a first integral of motion. In this work, we propose an architecture which combines existing Hamiltonian Neural Network structures into Adaptable Symplectic Recurrent Neural Networks which preserve Hamilton's equations as well as the symplectic stru

Raj Narendra Shah, Sameer Ahmed Mohamed, Asif Imran, Tevfik Kosar

The low cost and rapid provisioning capabilities have made open-source cloud a desirable platform to launch industrial applications. However, as open-source cloud moves towards maturity, it still suffers from quality issues like code smells. Although, a great emphasis has been provided on the economic benefits of deploying open-source cloud, low importance h

Nathaniel Hanson, Ahmet Demirkaya, Deniz Erdoğmuş, Aron Stubbins

Plastic waste entering the riverine harms local ecosystems leading to negative ecological and economic impacts. Large parcels of plastic waste are transported from inland to oceans leading to a global scale problem of floating debris fields. In this context, efficient and automatized monitoring of mismanaged plastic waste is paramount. To address this proble

Sangita Chatterjee, Soumen Mondal, Prasad Basu

Real extreme/intermediate mass ratio inspiral(E/IMRI) systems are likely to contain large accretion disks which could be as massive as the central supermassive black hole. Therefore, contrary to its ideal model, a real E/IMRI system contains a third important component: the accretion disk. We study the influence of these disks on the emitted GW profile and i

Tamás Varga

We introduce the quantum-house effect, a non-local quantum phenomenon which goes against classical intuition. We show how the effect can be achieved with any bipartite quantum state where neither subsystem is in a pure state. Besides its theoretical description, the quantum-house effect is also demonstrated on SpinQ Gemini, a 2-qubit liquid-state NMR desktop

Aqeel Labash, Florian Fletzer, Daniel Majoral, Raul Vicente

Adapting to regularities of the environment is critical for biological organisms to anticipate events and plan. A prominent example is the circadian rhythm corresponding to the internalization by organisms of the $24$-hour period of the Earth's rotation. In this work, we study the emergence of circadian-like rhythms in deep reinforcement learning agents. In

Mehmet Cem Güçlü, Melek Yılmaz Şengül

The STAR collaboration has observed an excess production of electron-positron pairs which have transverse momenta pperp < 150 MeV/c in peripheral gold-gold and uranium-uranium collisions. ALICE has also reported on an excess of mu mu pairs at low pperp in very peripheral lead-lead collisions at a center-of-mass energy of 2.76 TeV/nucleon pair. In literature,

Yujia Yang, Jan-Wilke Henke, Arslan S. Raja, F. Jasmin Kappert

The short de Broglie wavelength and strong interaction empower free electrons to probe scattering and excitations in materials and resolve the structure of biomolecules. Recent advances in using nanophotonic structures to mediate bilinear electron-photon interaction have brought novel optical manipulation schemes to electron beams, enabling high space-time-e

Salem Ben Saïd, Jean-Louis Clerc, Khalid Koufany

This is an overview on the {source operator method} which leads to the construction of symmetry breaking differential operators (SBDO) in the context of tensor product of two principals series representations for the conformal group of a simple real Jordan algebra. This method can be applied to other geometric contexts: in the construction of SBDO for differ

Mark Hughes, Seungwon Kim, Maggie Miller

We show that there exist split, orientable, 2-component surface-links in $S^4$ with non-isotopic splitting spheres in their complements. In particular, for non-negative integers $m,n$ with $m\ge 4$, the unlink $L_{m,n}$ consisting of one component of genus $m$ and one component of genus $n$ contains in its complement two smooth splitting spheres that are not

Sachin Kumar, Sourabh Manna, John Rex Mohan, Utkarsh Shashank

The impurity incorporation in host high-spin orbit coupling materials like platinum has shown improved charge-to-spin conversion by modifying the up-spin and down-spin electron trajectories by bending or skewing them in opposite directions. This enables efficient generation, manipulation, and transport of spin currents. In this study, we irradiate the platin

Xueshen Li, Hongshan Liu, Xiaoyu Song, Brigitta C. Brott

There is a significant need for the generation of virtual histological information from coronary optical coherence tomography (OCT) images to better guide the treatment of coronary artery disease. However, existing methods either require a large pixel-wisely paired training dataset or have limited capability to map pathological regions. To address these issu

Sanna Soomro, Keming Yu

Hypertension is a highly prevalent chronic medical condition and a strong risk factor for cardiovascular disease (CVD), as it accounts for more than $45\%$ of CVD. The relation between blood pressure (BP) and its risk factors cannot be explored clearly by standard linear models. Although the fractional polynomials (FPs) can act as a concise and accurate form

Stefan Schoepf, Stephen Mak, Julian Senoner, Liming Xu

Heavy goods vehicles are vital backbones of the supply chain delivery system but also contribute significantly to carbon emissions with only 60% loading efficiency in the United Kingdom. Collaborative vehicle routing has been proposed as a solution to increase efficiency, but challenges remain to make this a possibility. One key challenge is the efficient co

Pranjal Awasthi, Nika Haghtalab, Eric Zhao

Multi-distribution learning is a natural generalization of PAC learning to settings with multiple data distributions. There remains a significant gap between the known upper and lower bounds for PAC-learnable classes. In particular, though we understand the sample complexity of learning a VC dimension d class on $k$ distributions to be $O(\epsilon^{-2} \ln(k

Suyoun Kim, Akshat Shrivastava, Duc Le, Ju Lin

End-to-end (E2E) spoken language understanding (SLU) systems that generate a semantic parse from speech have become more promising recently. This approach uses a single model that utilizes audio and text representations from pre-trained speech recognition models (ASR), and outperforms traditional pipeline SLU systems in on-device streaming scenarios. However

Priyansh Saxena, Raahat Gupta, Akshat Maheshwari

There are many different heuristic algorithms for solving combinatorial optimization problems that are commonly described as Nature-Inspired Algorithms (NIAs). Generally, they are inspired by some natural phenomenon, and due to their inherent converging and stochastic nature, they are known to give optimal results when compared to classical approaches. There

Yijing Huang, José D. Querales-Flores, Samuel W. Teitelbaum, Jiang Cao

Quantifying electron-phonon interactions for the surface states of topological materials can provide key insights into surface-state transport, topological superconductivity, and potentially how to manipulate the surface state using a structural degree of freedom. We perform time-resolved x-ray diffraction (XRD) and angle-resolved photoemission (ARPES) measu

Jiasheng Si, Yingjie Zhu, Xingyu Shi, Deyu Zhou

Given a controversial target such as ``nuclear energy'', argument mining aims to identify the argumentative text from heterogeneous sources. Current approaches focus on exploring better ways of integrating the target-associated semantic information with the argumentative text. Despite their empirical successes, two issues remain unsolved: (i) a target is rep

Navot Oz, Nir Sochen, David Mendelovich, Iftach Klapp

Low-cost thermal cameras are inaccurate (usually $\pm 3^\circ C$) and have space-variant nonuniformity across their detector. Both inaccuracy and nonuniformity are dependent on the ambient temperature of the camera. The goal of this work was to estimate temperatures with low-cost infrared cameras, and rectify the nonuniformity. A nonuniformity simulator that

Pranav Barot, Katja Mombaur, Ewen MacDonald

To achieve human-like behaviour during speech interactions, it is necessary for a humanoid robot to estimate the location of a human talker. Here, we present a method to optimize the parameters used for the direction of arrival (DOA) estimation, while also considering real-time applications for human-robot interaction scenarios. This method is applied to bin

Victor Adewopo, Nelly Elsayed, Zag Elsayed, Murat Ozer

Accident detection and traffic analysis is a critical component of smart city and autonomous transportation systems that can reduce accident frequency, severity and improve overall traffic management. This paper presents a comprehensive analysis of traffic accidents in different regions across the United States using data from the National Highway Traffic Sa

Luca Capizzi, Michele Mazzoni

Global symmetries of quantum many-body systems can be spontaneously broken. Whenever this mechanism happens, the ground state is degenerate and one encounters an ordered phase. In this study, our objective is to investigate this phenomenon by examining the entanglement asymmetry of a specific region. This quantity, which has recently been introduced in the c

Vishnu V. Ratnam, Hao Chen, Hao Hsuan Chang, Abhishek Sehgal

Due to its ubiquitous and contact-free nature, the use of WiFi infrastructure for performing sensing tasks has tremendous potential. However, the channel state information (CSI) measured by a WiFi receiver suffers from errors in both its gain and phase, which can significantly hinder sensing tasks. By analyzing these errors from different WiFi receivers, a m

Anant Khandelwal

Large text-to-image diffusion models have achieved remarkable success in generating diverse, high-quality images. Additionally, these models have been successfully leveraged to edit input images by just changing the text prompt. But when these models are applied to videos, the main challenge is to ensure temporal consistency and coherence across frames. In t

Dan Cristofaro-Gardiner, Richard Hind

A theorem of Gutt-Hutchings-Ramos asserts that all normalized symplectic capacities give the same value for monotone four-dimensional toric domains. We generalize this theorem to arbitrary dimension. The new ingredient in our proof is the construction of symplectic embeddings of "$L$-shaped" domains in any dimension into corresponding infinite cylinders; thi

Emerson Abreu, Rodrigo Clemente, João Marcos Do Ó, Everaldo Medeiros

This paper investigates the existence, nonexistence, and qualitative properties of p-harmonic functions in the upper half-space $\mathbb{R}^N_+ \, (N \geq 3)$ satisfying nonlinear boundary conditions for $1<p<N$. Moreover, the symmetry of positive solutions is shown by using the method of moving planes.

Sanna Soomro, Keming Yu, Yan Yu

Robust regression has attracted a great amount of attention in the literature recently, particularly for taking asymmetricity into account simultaneously and for high-dimensional analysis. However, the majority of research on the topics falls in frequentist approaches, which are not capable of full probabilistic uncertainty quantification. This paper first p

One Octadion, Novanto Yudistira, Diva Kurnianingtyas

Batik, a unique blend of art and craftsmanship, is a distinct artistic and technological creation for Indonesian society. Research on batik motifs is primarily focused on classification. However, further studies may extend to the synthesis of batik patterns. Generative Adversarial Networks (GANs) have been an important deep learning model for generating synt

Hanshuai Cui, Zhiqing Tang, Jiong Lou, Weijia Jia

In Mobile Edge Computing (MEC), Internet of Things (IoT) devices offload computationally-intensive tasks to edge nodes, where they are executed within containers, reducing the reliance on centralized cloud infrastructure. Frequent upgrades are essential to maintain the efficient and secure operation of edge clusters. However, traditional cloud cluster upgrad

Mark Zhandry

We give a construction of public key quantum money, and even a strengthened version called quantum lightning, from abelian group actions, which can in turn be constructed from suitable isogenies over elliptic curves. We prove security in the generic group model for group actions under a plausible computational assumption, and develop a general toolkit for pr

Hameedah Sultan, Smruti R. Sarangi

Despite temperature rise being a first-order design constraint, traditional thermal estimation techniques have severe limitations in modeling critical aspects affecting the temperature in modern-day chips. Existing thermal modeling techniques often ignore the effects of parameter variation, which can lead to significant errors. Such methods also ignore the d

Dominik Hellmann, Heinrich Päs

We investigate the cosmological consequences of light sterile neutrinos with altered dispersion relations (ADRs) and couplings to an ultra-light, axion-like scalar field. In particular we study the impact on the number of additional, light, fermionic degrees of freedom and primordial nucleosynthesis. While the ADR leads to a new potential term in the Hamilto

Yong Yao

In this paper, the dynamics of a Leslie-Gower type predator-prey system with herd behavior and constant harvesting in prey are investigated. Earlier work has shown that the herd behavior in prey merely induces a supercritical Hopf bifurcation in the classic Leslie-Gower predator-prey system in the absence of harvesting. However, the work in this paper shows

Zhijian Qiao, Zehuan Yu, Huan Yin, Shaojie Shen

Global point cloud registration is essential in many robotics tasks like loop closing and relocalization. Unfortunately, the registration often suffers from the low overlap between point clouds, a frequent occurrence in practical applications due to occlusion and viewpoint change. In this paper, we propose a graph-theoretic framework to address the problem o

Jiayuan Chen, Changyan Yi, Hongyang Du, Dusit Niyato

Mobile Artificial Intelligence-Generated Content (AIGC) technology refers to the adoption of AI algorithms deployed at mobile edge networks to automate the information creation process while fulfilling the requirements of end users. Mobile AIGC has recently attracted phenomenal attentions and can be a key enabling technology for an emerging application, call

Yanis Labrak, Mickael Rouvier, Richard Dufour

We evaluate four state-of-the-art instruction-tuned large language models (LLMs) -- ChatGPT, Flan-T5 UL2, Tk-Instruct, and Alpaca -- on a set of 13 real-world clinical and biomedical natural language processing (NLP) tasks in English, such as named-entity recognition (NER), question-answering (QA), relation extraction (RE), etc. Our overall results demonstra

Aleksandar Tošić

This paper presents an empirical study on the feasibility of using Checkpoint/Restore In Userspace (CRIU) for run-time application migration between hosts, with a particular focus on edge computing and cloud infrastructures. The paper provides experimental support for CRIU in Docker and offers insights into the impact of application memory usage on checkpoin

Mohammad Joubat, Claudelle Capasia Madjuogang Sandeu, Alex Prygarin

We consider the powers of leading order eigenvalue of the Balitsky-Fadin-Kuraev-Lipatov~(BFKL) equation at zero conformal spin. Using reflection identities of harmonic sums we demonstrate how involved generalized polygamma functions are introduced by pole separation of a rather simple digamma function. This generates higher weight generalized polygamma funct

János Gergő Fehérvári, Zoltán Balogh, Tímea Nóra Török, András Halbritter

The commercial introduction of a novel electronic device is often preceded by a lengthy material optimization phase devoted to the suppression of device noise as much as possible. The emergence of novel computing architectures, however, triggers a paradigm change in noise engineering, demonstrating that a non-suppressed, but properly tailored noise can be ha

Romeo Mestrovic, Branislav Dragovic

So far, many researchers have investigated the following question: Given total number of citations, what is the estimated range of the h index? Here we consider the converse question. Namely, the aim of this paper is to estimate the total number of citations of a researcher using only his h index, his h core and perhaps a relatively small number of his citat

Pasquale Bosso, Giuseppe Fabiano, Domenico Frattulillo, Fabian Wagner

A number of arguments at the interplay of general relativity and quantum theory suggest an operational limit to spatial resolution, conventionally modelled as a generalized uncertainty principle (GUP). Recently, it has been demonstrated that the dynamics postulated as a part of these models are only loosely related to the existence of the minimal-length scal

Andrew Searles, Yoshimichi Nakatsuka, Ercan Ozturk, Andrew Paverd

For nearly two decades, CAPTCHAs have been widely used as a means of protection against bots. Throughout the years, as their use grew, techniques to defeat or bypass CAPTCHAs have continued to improve. Meanwhile, CAPTCHAs have also evolved in terms of sophistication and diversity, becoming increasingly difficult to solve for both bots (machines) and humans.

Károly J. Böröczky, Pengfei Guan

We provide a natural simple argument using anistropic flows to prove the existence of weak solutions to Lutwak's $L^p$-Minkowski problem on $S^n$ which were obtained by other methods.

Yang Tian, Jiyao Zhang, Zekai Yin, Hao Dong

In this work, we tackle the problem of online camera-to-robot pose estimation from single-view successive frames of an image sequence, a crucial task for robots to interact with the world.

JiaJun Wu, Chao-Qiang Geng, Da Huang

In light of the recently discovered $W$-boson mass anomaly by the CDF Collaboration, we discuss two distinct mechanisms that could possibly explain this anomaly through the introduction of high-dimensional $SU(2)_L$ scalar multiplets. The first mechanism is the tree-level $W$-boson mass correction induced by the vacuum expectation values of one or more $SU(2

Nicholas Wu

How can one efficiently share payoffs with collaborators when participating in risky research? First, I show that efficiency can be achieved by allocating payoffs asymmetrically between the researcher who makes a breakthrough ("winner") and the others, even if agents cannot observe others' effort. When the winner's identity is non-contractible, allocating cr

Zhuoran Fang, Rui Chen, Johannes E. Fröch, Quentin A. A. Tanguy

Free-space modulation of light is crucial for many applications, from light detection and ranging to virtual or augmented reality. Traditional means of modulating free-space light involves spatial light modulators based on liquid crystals and microelectromechanical systems, which are bulky, have large pixel areas (~10 micron x 10 micron), and require high dr

R. I. Ayala Oña, M. B. Kalmykov, D. P. Kislyakova, T. P. Shestakova

The question about the appearance of time in the semiclassical limit of quantum gravity continues to be discussed in the literature. It is believed that a temporal Schrodinger equation for matter fields on the background of a classical gravitational field must be true. To obtain this equation, the Born - Oppenheimer approximation for gravity is used. However

Di Wu, Pengfei Chen, Xuehui Yu, Guorong Li

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects). The previous works usually utilize multiple instance learning (MIL), which highly depends on category information, to select and refine a low-qu

Erik Fransson, J. Magnus Rahm, Julia Wiktor, Paul Erhart

Halide perovskites have emerged as a promising class of materials for photovoltaic applications. A challenge in these applications is how to prevent the crystal structure from degradation to photovoltaically inactive phases, which requires an understanding of the free energy landscape of these materials. Here, we uncover the free energy landscape of two prot

Peter Lalor, Areg Danagoulian

Dual energy cargo inspection systems are sensitive to both the area density and the atomic number of an imaged container due to the $Z$ dependence of photon attenuation. The ability to identify cargo contents by their atomic number enables improved detection capabilities of illicit materials. This work introduces a novel method for atomic number reconstructi

Adrián Rebola-Pardo

Proof formats for SAT solvers have diversified over the last decade, enabling new features such as extended resolution-like capabilities, very general extension-free rules, inclusion of proof hints, and pseudo-boolean reasoning. Interference-based methods have been proven effective, and some theoretical work has been undertaken to better explain their limits

Hector Pasten, Joseph H. Silverman

Let $X/K$ be a smooth projective variety defined over a number field, and let $f:X\to{X}$ be a morphism defined over $K$. We formulate a number of statements of varying strengths asserting, roughly, that if there is at least one point $P_0\in{X(K)}$ whose $f$-orbit $\mathcal{O}_f(P_0):=\bigl\{f^n(P):n\in\mathbb{N}\bigr\}$ is Zariski dense, then there are man

Ramon Torres

General Relativity provides us with some solutions for rotating black holes. However, there are some problems associated with them: the appearance of singularities, the possibility of violations of the cosmic censorship conjecture, the existence of regions where the mass acts repulsively and the violation of causality. Many authors consider that these proble

David Jesus, Yannick Sire

We derive $C^{1,\alpha}$ estimates for viscosity solutions of fully nonlinear equations degenerating on a hypersurface.

Abhishek Dhawan

Let $G$ be a multigraph and $L\,:\,E(G) \to 2^\mathbb{N}$ be a list assignment on the edges of $G$. Suppose additionally, for every vertex $x$, the edges incident to $x$ have at least $f(x)$ colors in common. We consider a variant of local edge-colorings wherein the color received by an edge $e$ must be contained in $L(e)$. The locality appears in the functi

Shang Gao, Ling-Fang Lin, Pontus Laurell, Qiang Chen

Magnetic excitations in the spin chain candidate Sr$_2$V$_3$O$_9$ have been investigated by inelastic neutron scattering on a single crystal sample. A spinon continuum with a bandwidth of $\sim22$ meV is observed along the chain formed by alternating magnetic V$^{4+}$ and nonmagnetic V$^{5+}$ ions. Incipient magnetic Bragg peaks due to weak ferromagnetic int

Jam Sadiq, Thomas Dent, Mark Gieles

Binary black hole (BBH) systems detected via gravitational-wave (GW) emission are a recently opened astrophysical frontier with many unknowns and uncertainties. Accurate reconstruction of the binary distribution with as few assumptions as possible is desirable for inference on formation channels and environments. Most population analyses have, though, assume

Marzieh Peyravi, Nematollah Riazi, Kurosh Javidan

This paper examines the effects of a thin layer of inhomogeneity on periodic solutions of the Multiple-sine-Gordon (MsG) model. We investigate the dynamics of the perturbed Double-sine-Gordon (DsG) system as a significant and more practical case of such configurations. The thin barrier acts as a potential well (potential barrier) and causes critical deformat

Michael Brocidiacono, Konstantin I. Popov, David Ryan Koes, Alexander Tropsha

Molecular docking aims to predict the 3D pose of a small molecule in a protein binding site. Traditional docking methods predict ligand poses by minimizing a physics-inspired scoring function. Recently, a diffusion model has been proposed that iteratively refines a ligand pose. We combine these two approaches by training a pose scoring function in a diffusio