May 2024 arXiv papers — page 142

CH Ramanjaneyulu, Dinesh Nayak, D K K Vamsi

Leprosy (Hansen's) is a disease caused by Mycobacterium leprae. This disease slowly leads to occurrence of leprae reactions which mainly damage peripheral nervous system which cause loss of organs. We can prevent occurring leprae reactions by monitoring the bio-markers involved in it. Motivated by these observations in this research work we do a exhaustive s

Qingcheng Fu, Alexander Kurganov, Mingye Na, Vladimir Zeitlin

New evidence of surprising robustness of solitary-wave solutions of the Serre-Green-Naghdi (SGN) equations is presented on the basis of high-resolution numerical simulations conducted using a novel well-balanced finite-volume method. SGN solitons exhibit a striking resemblance with their celebrated Korteweg-deVries (KdV) counterparts. Co-moving solitons are

Abhishek Vaibhav Pathak, Anukul Sachan, Raisa DSouza

In this paper, we investigate the Sombor index of the total graph and unit graph of $\mathbb{Z}_n$ which is denoted by $T_{\Gamma}(\mathbb{Z}_n)$ and $G(\mathbb{Z}_n)$ respectively for $n \in \{2k, p^{\alpha}, pq, p^2q\}$ where $p$ and $q$ are distinct odd prime numbers such that $p < q$. Moreover, we compute the Sombor index of any finite local ring.

Thi Xinh Dinh, Ba Thong Le, Son Hoang Dau, Serdar Boztas

We generalize the problem of recovering a lost/erased symbol in a Reed-Solomon code to the scenario in which some side information about the lost symbol is known. The side information is represented as a set $S$ of linearly independent combinations of the sub-symbols of the lost symbol. When $S = \varnothing$, this reduces to the standard problem of repairin

Jordan Orchard, Federico Frascoli, Lamberto Rondoni, Carlos Mejía-Monasterio

Polygonal billiards exhibit a rich and complex dynamical behavior. In recent years polygonal billiards have attracted great attention due to their application in the understanding of anomalous transport, but also at the fundamental level, due to its connections with diverse fields in mathematics. We explore this complexity and its consequences on the propert

Ekansh Agrawal

Guided by the hologram technology of the infamous Star Wars franchise, I present an application that creates real-time holographic overlays using LiDAR augmented 3D reconstruction. Prior attempts involve SLAM or NeRFs which either require highly calibrated scenes, incur steep computation costs, or fail to render dynamic scenes. I propose 3 high-fidelity reco

Arpit Kumar Shrivastav, Vaibhav Pant, Patrick Antolin

Decayless kink oscillations are ubiquitously observed in active region coronal loops with an almost constant amplitude for several cycles. Decayless kink oscillations of coronal loops triggered by coronal rain have been analysed, but the impact of coronal rain formation in an already oscillating loop is unclear. As kink oscillations can help diagnose the loc

Xiaoming Shi, Xiaodan Shao, Rui Zhang

Six-dimensional movable antenna (6DMA) is an effective solution for enhancing wireless network capacity through the adjustment of both 3D positions and 3D rotations of distributed antennas/antenna surfaces. Although freely positioning/rotating 6DMA surfaces offers the greatest flexibility and thus highest capacity improvement, its implementation may be chall

Mario Chahoud, Hani Sami, Azzam Mourad, Hadi Otrok

In Federated Learning (FL), the limited accessibility of data from diverse locations and user types poses a significant challenge due to restricted user participation. Expanding client access and diversifying data enhance models by incorporating diverse perspectives, thereby enhancing adaptability. However, challenges arise in dynamic and mobile environments

Mohamad Wazzeh, Mohamad Arafeh, Hani Sami, Hakima Ould-Slimane

In the ever-changing world of technology, continuous authentication and comprehensive access management are essential during user interactions with a device. Split Learning (SL) and Federated Learning (FL) have recently emerged as promising technologies for training a decentralized Machine Learning (ML) model. With the increasing use of smartphones and Inter

Leonardo Cella

Inferential models (IMs) represent a novel possibilistic approach for achieving provably valid statistical inference. This paper introduces a general framework for fusing independent IMs in a "black-box" manner, requiring no knowledge of the original IMs construction details. The underlying logic of this framework mirrors that of the IMs approach. First, a f

Lavi Ben-Shimol, Edita Grolman, Aviad Elyashar, Inbar Maimon

In a fully managed serverless environment, the cloud service provider is responsible for securing the cloud infrastructure, thereby reducing the operational and maintenance efforts of application developers. However, this environment limits the use of existing cybersecurity frameworks and tools, which reduces observability and situational awareness capabilit

WeiQin Chuah, Ruwan Tennakoon, Alireza Bab-Hadiashar

Online Test-Time Adaptation (OTTA) has emerged as an effective strategy to handle distributional shifts, allowing on-the-fly adaptation of pre-trained models to new target domains during inference, without the need for source data. We uncovered that the widely studied entropy minimization (EM) method for OTTA, suffers from noisy gradients due to ambiguity ne

Zhijun Li, Zhengyun You

Exotic physics typically encompasses two categories of exotic particles: ``dark" particles beyond the standard model and exotic hadrons within the extended standard model. We present a summary of the recent results on exotic particles at BESIII, which could play a crucial role in the study of exotic physics.

Fernando Cladera, Ian D. Miller, Zachary Ravichandran, Varun Murali

One common and desirable application of robots is exploring potentially hazardous and unstructured environments. Air-ground collaboration offers a synergistic approach to addressing such exploration challenges. In this paper, we demonstrate a system for large-scale exploration using a team of aerial and ground robots. Our system uses semantics as lingua fran

Ankit Barik, Regupathi Angappan

Long term observations and space missions have generated a wealth of data on the magnetic fields of the Earth and other solar system planets. planetMagfields is a Python package designed to have all the planetary magnetic field data currently available in one place and to provide an easy interface to access the data. planetMagfields focuses on planetary bodi

Haonan Li, Patrick P. K. Chen, Yitong Zhou

With the rapid advancement of technologies such as virtual reality, augmented reality, and gesture control, users expect interactions with computer interfaces to be more natural and intuitive. Existing visual algorithms often struggle to accomplish advanced human-computer interaction tasks, necessitating accurate and reliable absolute spatial prediction meth

A V Subramanyam, Niyati Singal, Vinay K Verma

Despite the rapid advancement in the field of image recognition, the processing of high-resolution imagery remains a computational challenge. However, this processing is pivotal for extracting detailed object insights in areas ranging from autonomous vehicle navigation to medical imaging analyses. Our study introduces a framework aimed at mitigating these ch

Labh Singh, Monal Kashav, Surender Verma

We present a Dirac mass model based on $A_{4}$ modular symmetry within Type-I seesaw framework. This extension of Standard Model requires three right-handed neutrinos and three heavy Dirac fermions superfields, all singlet under $SU(2)_{L}$ symmetry. The scalar sector is extended by the inclusion of a $SU(2)_{L}$ singlet superfield, $\chi$. Here, the modular

Yao Liu, Quan Z. Sheng, Lina Yao

Pedestrian trajectory prediction plays a pivotal role in the realms of autonomous driving and smart cities. Despite extensive prior research employing sequence and generative models, the unpredictable nature of pedestrians, influenced by their social interactions and individual preferences, presents challenges marked by uncertainty and multimodality. In resp

Gyeong-Geon Lee, Xiaoming Zhai

Educational scholars have analyzed various image data acquired from teaching and learning situations, such as photos that shows classroom dynamics, students' drawings with regard to the learning content, textbook illustrations, etc. Unquestioningly, most qualitative analysis of and explanation on image data have been conducted by human researchers, without m

Yuwei Zeng, Yao Mu, Lin Shao

Learning reward functions remains the bottleneck to equip a robot with a broad repertoire of skills. Large Language Models (LLM) contain valuable task-related knowledge that can potentially aid in the learning of reward functions. However, the proposed reward function can be imprecise, thus ineffective which requires to be further grounded with environment i

Xinchen Zhou, Ruzhu Wang, Xiaoping Ouyang, Jiping Huang

Improving the heat transfer coefficient is crucial across various energy utilization processes for maintaining device safety and stability with high energy efficiency. However, in scenarios with limited heat capacity flow rates, increasing the thermal conductivity of encapsulated internal heat source (IHS) packaging can paradoxically impede heat transfer. He

Yongsheng Han, Ji Li, Chaoqiang Tan, Zipeng Wang

In the field of harmonic analysis, geometric considerations are frequently crucial. Specially, group actions such as translations, dilations and rotations on Euclidean space are instrumental. The objective of this paper is to extend the study of singular integrals to include the effects of group reflections on Euclidean space, and to establish the T1 theorem

Itsuki Takagi, Yuma Konno, Yosuke Kayanuma, Kazutaka G. Nakamura

We present a novel and simple picture of the generation dynamics of coherent longitudinal optical (LO) phonons and LO-phonon-plasmon-coupled (LOPC) modes by the ultrafast infrared pump-pulses in gallium arsenide (GaAs) employing the low-temperature approximation. LO phonons exhibit a pronounced coupling with plasmons formed by the optically excited electrons

Desheng Fu, Seiji Sogen, Hisao Suzuki

An unresolved issue in the commonly used Pb(Zr1-xTix)O3 (PZT) ceramics is understanding the intrinsic piezoelectric behaviors of its crystal around the morphotropic phase boundary (MPB). Here, we demonstrate a novel approach to grow c-axis oriented PZT around MPB on stainless steel SUS430, allowing us to estimate the intrinsic piezoelectric and ferroelectric

Congbo Ma, Wei Emma Zhang, Hu Wang, Haojie Zhuang

Multi-document summarization (MDS) generates a summary from a document set. Each document in a set describes topic-relevant concepts, while per document also has its unique contents. However, the document specificity receives little attention from existing MDS approaches. Neglecting specific information for each document limits the comprehensiveness of the g

Alireza Ghanbari, Gholamhassan Shirdel, Farhad Maleki

Precision agriculture involves the application of advanced technologies to improve agricultural productivity, efficiency, and profitability while minimizing waste and environmental impact. Deep learning approaches enable automated decision-making for many visual tasks. However, in the agricultural domain, variability in growth stages and environmental condit

Jian Yuan, Haonan Wang, Xiaofei Hou, Binshuo Zhang

Impurity substitution is a general strategy to study the intrinsic properties of a quantum material. However, when the target element has more than one Wyckoff position in the lattice, it is a big challenge but with extreme necessity to know the exact position and order of the occupancy of impurity atoms. Via comprehensive experimental and theoretical invest

Hu Wang, Salma Hassan, Yuyuan Liu, Congbo Ma

In multi-modal learning, some modalities are more influential than others, and their absence can have a significant impact on classification/segmentation accuracy. Addressing this challenge, we propose a novel approach called Meta-learned Modality-weighted Knowledge Distillation (MetaKD), which enables multi-modal models to maintain high accuracy even when k

Hai-Jiang Tian, Yin-Long Yang, Dan-Dan Hu, Hai-Bing Fu

In this paper, we carry out an investigation into the semileptonic decays $D_s^+ \to K^0\ell^+\nu_\ell$ with $\ell=(e,\mu)$ by employing the QCD light-cone sum rules approach. The vector transition form factor (TFF) $f_+^{D_s^+ K^0}(q^2)$ for $D_s^+\to K^0$ decay is calculated while considering its next-to-leading order contribution. Subsequently, we briefly

Zhiwei Li, Guodong Long, Chunxu Zhang, Honglei Zhang

Federated Recommendation Systems (FRSs) offer a privacy-preserving alternative to traditional centralized approaches by decentralizing data storage. However, they face persistent challenges such as data sparsity and heterogeneity, largely due to isolated client environments. Recent advances in Foundation Models (FMs), particularly large language models like

Shuai Gao, Manish Chaudhary, Alexey N. Pyrkov, Ebubechukwu O. Ilo-Okeke

The theory of quantum information processing for macroscopic qubits is based on the fact that every macroscopic qubit has a conserved number of particles. However, from an experimental point of view, every such qubit experiences processes of decoherence that impact the possibilities for entanglement generation between such qubits and use in quantum informati

Wei-Yang Wang, Chen Zhang, Enping Zhou, Xiaohui Liu

With a growing sample of fast radio bursts (FRBs), we investigate the energy budget of different power sources within the framework of magnetar starquake triggering mechanism. During a starquake, the energy can be released in any form through strain, magnetic, rotational, and gravitational energies. The strain energy can be converted from other three kinds o

Sina Eghbal, Badri N. Vellambi, Lawrence Ong, Parastoo Sadeghi

This paper introduces a novel class of PICOD($t$) problems referred to as $g$-group complete-$S$ PICOD($t$) problems. It constructs a multi-stage achievability scheme to generate pliable index codes for group complete PICOD problems when $S = \{s\}$ is a singleton set. Using the maximum acyclic induced subgraph bound, lower bounds on the broadcast rate are d

Changping Xie, Shaomei Fang, Ming Mei, Yuming Qin

This paper is concerned with the weak solution for the fast diffusion equation with absorption and singularity in the form of $u_t=\triangle u^m -u^p$. We first prove the existence and decay estimate of weak solution when the fast diffusion index satisfies $0<m<1$ and the absorption index is $p>1$. Then we show the asymptotic convergence of weak solution to

Xiaonan Liu, Shiwang Ma, Yachen Wang

In this paper, we study asymptotic behavior of positive ground state solutions for the nonlinear Choquard equation: \begin{equation}\label{0.1} -\Delta u+\varepsilon u=\big(I_{\alpha}\ast F(u)\big)F'(u),\quad u\in H^1(\mathbb R^N), \end{equation} where $F(u)=|u|^{\frac{N+\alpha}{N-2}}+G(u)$, $N\geq3$ is an integer, $I_{\alpha}$ is the Riesz potential of orde

Dewen Liu, Shuai He, Haoran Cheng, Yadong Zeng

Adaptive mesh refinement (AMR) is a classical technique about local refinement in space where needed, thus effectively reducing computational costs for HPC-based physics simulations. Although AMR has been used for many years, little reproducible research discusses the impact of software-based parameters on block-structured AMR (BSAMR) efficiency and how to c

Maolin Che, Yimin Wei, Hong Yan

In this paper, we focus on the fixed TT-rank and precision problems of finding an approximation of the tensor train (TT) decomposition of a tensor. Note that the TT-SVD and TT-cross are two well-known algorithms for these two problems. Firstly, by combining the random projection technique with the power scheme, we obtain two types of randomized algorithms fo

Mitch Jacovetty, Joseph Oglio, Mikhail Nesterenko, Gokarna Sharma

We present TRAIL: an algorithm that uses a novel consensus procedure to tolerate failed or malicious shards within a blockchain-based cryptocurrency. Our algorithm takes a new approach of selecting validator shards for each transaction from those that previously held the assets being transferred. This approach ensures the algorithm's robustness and efficienc

Yuepeng Hu, Zhengyuan Jiang, Moyang Guo, Neil Gong

Watermark has been widely deployed by industry to detect AI-generated images. A recent watermarking framework called \emph{Stable Signature} (proposed by Meta) roots watermark into the parameters of a diffusion model's decoder such that its generated images are inherently watermarked. Stable Signature makes it possible to watermark images generated by \emph{

Chloe Clear, Sara Hosseini, Amirhossein AlizadehKhaledi, Nicholas Brunelle

The silicon T centre's narrow, telecommunications-band optical emission, long spin coherence, and direct photonic integration have spurred interest in this emitter as a spin-photon interface for distributed quantum computing and networking. However, key parameters of the T centre's spin-selective optical transitions remain undetermined or ambiguous in litera

Naoki Takeishi, Tomohiro Nishiyama, Kodai Nagaishi, Takeshi Nashima

The deformability of human red blood cells (RBCs), which comprise almost 99% of the cells in whole blood, is largely related not only to pathophysiological blood flow but also to the levels of intracellular compounds. Therefore, statistical estimates of the deformability of individual RBCs are of paramount importance in the clinical diagnosis of blood diseas

Weiwei Weng, Mahardhika Pratama, Jie Zhang, Chen Chen

Artificial neural networks, celebrated for their human-like cognitive learning abilities, often encounter the well-known catastrophic forgetting (CF) problem, where the neural networks lose the proficiency in previously acquired knowledge. Despite numerous efforts to mitigate CF, it remains the significant challenge particularly in complex changing environme

Chon Man Sou, Junqi Wang, Yi Wang

The inflationary universe creates particle pairs, which are entangled in their momenta due to momentum conservation. Operators involving the momenta of the fluctuations can be rewritten into pseudo-spin operators, such as the Gour-Khanna-Mann-Revzen (GKMR) pseudo-spin. Making use of these pseudo-spin operators, cosmological Bell inequalities can be formulate

Xinyuan Zhang, Jiang Liu, Zehui Xiong, Yudong Huang

Generative Artificial Intelligence (GAI) is taking the world by storm with its unparalleled content creation ability. Large Language Models (LLMs) are at the forefront of this movement. However, the significant resource demands of LLMs often require cloud hosting, which raises issues regarding privacy, latency, and usage limitations. Although edge intelligen

Yuwen Li, Ludmil T. Zikatanov, Cheng Zuo

This work is on a user-friendly reduced basis method for solving a family of parametric PDEs by preconditioned Krylov subspace methods including the conjugate gradient method, generalized minimum residual method, and bi-conjugate gradient method. The proposed methods use a preconditioned Krylov subspace method for a high-fidelity discretization of one parame

Yong He, Xiaoyang Ma, Xingheng Wang, Yalin Wang

In this paper, we focus on exploiting the group structure for large-dimensional factor models, which captures the homogeneous effects of common factors on individuals within the same group. In view of the fact that datasets in macroeconomics and finance are typically heavy-tailed, we propose to identify the unknown group structure using the agglomerative hie

Nai-Hui Chia, Min-Hsiu Hsieh, Shih-Han Hung, En-Jui Kuo

This work investigates the oracle separation between the physically motivated complexity class of noisy quantum circuits, inspired by definitions such as those presented by Chen, Cotler, Huang, and Li (2022). We establish that with a constant error rate, separation can be achieved in terms of NP. When the error rate is $\Omega(\log n/n)$, we can extend this

Zhonglin Li, Kangyu Gao, Yingying Wang, Ruitong Bie

Line-scan mode facilitates fast-speed and high-throughput imaging with developing a suitable optical transverse needle focus. Metasurface with periodic structures such as diffractive rings, ellipses, and gratings could enable discrete focus evolving into line focus under momentum conservation, but still face the challenge of extremely low light power utiliza

Sayeh Sharify, Utkarsh Saxena, Zifei Xu, Wanzin Yazar

Large Language Models (LLMs) have distinguished themselves with outstanding performance in complex language modeling tasks, yet they come with significant computational and storage challenges. This paper explores the potential of quantization to mitigate these challenges. We systematically study the combined application of three well-known post-training tech

Joaquín Sánchez García, Sebastian Gherghe

Recently, an indicator for stock market fragility and crash size in terms of the Ollivier-Ricci curvature has been proposed. We study analytical and empirical properties of such indicator, test its elasticity with respect to different parameters and provide heuristics for the parameters involved. We show when and how the indicator accurately describes a fina

Skyler Marks

Category theory is the language of homological algebra, allowing us to state broadly applicable theorems and results without needing to specify the details for every instance of analogous objects. However, authors often stray from the realm of pure abstract category theory in their development of the field, leveraging the Freyd-Mitchell embedding theorem or

Edwin E. Mozo Luis, Silvio C. Ferreira, Thiago A. de Assis

We introduce a multifractal optimal detrended fluctuation analysis to study the scaling properties of the one-dimensional Wolf-Villain (WV) model for surface growth. This model produces mounded surface morphologies for long time scales (up to $10^9$ monolayers) and its universality class remains controversial. Our results for the multifractal exponent $\tau(

Taiki Haga

It presents a significant challenge to elucidate the relationship between the phases of open quantum many-body systems and the spectral structure of their governing Liouvillian, which determines how the density matrix evolves. Previous studies have focused on the Liouvillian gap, defined as the decay rate of the most slowly-decaying mode, as a key indicator

Mingyue Yuan, Jieshan Chen, Aaron Quigley

In automated user interactive design, designers face key challenges, including accurate representation of user intent, crafting high-quality components, and ensuring both aesthetic and semantic consistency. Addressing these challenges, we introduce MAxPrototyper, our human-centered, multi-agent system for interactive design generation. The core of MAxPrototy

Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu

Artificial intelligence (AI) has a profound impact on traditional education. In recent years, large language models (LLMs) have been increasingly used in various applications such as natural language processing, computer vision, speech recognition, and autonomous driving. LLMs have also been applied in many fields, including recommendation, finance, governme

James D. Paramore, Brady G. Butler, Michael T. Hurst, Trevor Hastings

In this paper, a synergistic computational/experimental approach is presented for the rapid discovery and characterization of novel alloys within the compositionally complex (i.e., "medium/high entropy") refractory alloy space of Ti-V-Nb-Mo-Hf-Ta-W. This was demonstrated via a material design cycle aimed at simultaneously maximizing the objective properties

Rei Sato, Gordon Cui, Kazuhiro Saito, Hideyuki Kawashima

Quantum search algorithms, such as Grover's algorithm, are anticipated to efficiently solve constrained combinatorial optimization problems. However, applying these algorithms to the traveling salesman problem (TSP) on a quantum circuit presents a significant challenge. Existing quantum search algorithms for the TSP typically assume that an initial state --

Alexander Werner, William Melek

This paper presents an approach to teleoperate a manipulator using a mobile phone as a leader device. Using its IMU and camera, the phone estimates its Cartesian pose which is then used to to control the Cartesian pose of the robot's tool. The user receives visual feedback in the form of multi-view video - a point cloud rendered in a virtual reality environm

Shogo Miyamura, Masayuki Higaki, Shuji Taue, Yoshiaki Nakajima

Refractive-index (RI) sensing plays a pivotal role in various domains, encompassing applications like glucose sensing, biosensing, and gas detection. Despite the advantages of optical fiber sensors, such as their compact size, flexibility, and immunity to electromagnetic interference, they are often plagued by temperature-induced drift, which adversely impac

Diego Salazar

We determine when the irreducible modules $L(c_{p, q}, h_{m, n})$ over the simple Virasoro vertex algebras $\operatorname{Vir}_{p, q}$, where $p, q \ge 2$ are relatively prime with $0 < m < p$ and $0 < n < q$, are classically free. It turns out that this only happens with the boundary minimal models, i.e., with the irreducible modules over $\operatorname{Vir

Francisco Alegría, Gong Chen, Claudio Muñoz, Felipe Poblete

We consider the Kadomtsev-Petviashvili II (KP) model placed in $\mathbb R_t \times \mathbb R_{x,y}^2$, in the case of smooth data that are not necessarily in a Sobolev space. In this paper, the subclass of smooth solutions we study is of ``soliton type'', characterized by a phase $\Theta=\Theta(t,x,y)$ and a unidimensional profile $F$. In particular, every c

Dave Pagurek van Mossel

Domain warping is a technique commonly used in creative coding to distort graphics and add visual interest to a work. The approach has the potential to be used in 3D art as mesh vertices can be efficiently warped using a vertex shader in a WebGL pipeline. However, 3D models packaged for the web typically come with baked-in normal vectors, and these need to b

Zi-Ran Zhao, Shun-Cai Zhao, Yi-Meng Huang

Predicting future physical behavior from limited theoretical simulation data is an emerging research paradigm driven by the integration of artificial intelligence and quantum physics. In this work, charge transport (CT) behavior was predicted over extended time scales using a deep learning model-the long short-term memory (LSTM) network with an error-thresho

Austin M. Marcus, Jordan Rozum, Herbert Sizek, Luis M. Rocha

The biomolecular networks underpinning cell function exhibit canalization, or the buffering of fluctuations required to function in a noisy environment. One understudied putative mechanism for canalization is the functional equivalence of a biomolecular entity's regulators (e.g., among the transcription factors for a gene). In these discrete dynamical system

Atsuki Sato, Yusuke Matsui

Sorting is one of the most fundamental algorithms in computer science. Recently, Learned Sorts, which use machine learning to improve sorting speed, have attracted attention. While existing studies show that Learned Sort is empirically faster than classical sorting algorithms, they do not provide theoretical guarantees about its computational complexity. We

Akil Pathiranage, Chris Czarnecki, Yuhao Chen, Pengcheng Xi

Ellipse estimation is an important topic in food image processing because it can be leveraged to parameterize plates and bowls, which in turn can be used to estimate camera view angles and food portion sizes. Automatically detecting the elliptical rim of plates and bowls and estimating their ellipse parameters for data "in-the-wild" is challenging: diverse c

Fanhao Jia, Zhao Tang, Greis J. Cruz, Weiwei Gao

Metal monochalcogenide GaSe is a classic layered semiconductor that has received increasing research interest due to its highly tunable electronic and optical properties for ultrathin electronics applications. Despite intense research efforts, a systematic understanding of the layer-dependent electronic and optical properties of GaSe remains to be establishe

Sriram Sankaranarayanan

We evaluate the best-response (BR) algorithm for lattice convex-quadratic games, where the players have nonlinear objectives and unbounded feasible sets. We provide a sufficient condition that if certain interaction matrices (the product of the inverse of the positive definite matrix defining the convex-quadratic terms and the matrix that connects one player

Yi C. Huang

We provide in this Letter a two-point generalisation of the Agmon estimate for Schr\"odinger operators on graphs recently established by S. Steinerberger. It reduces to his estimate when the two points belong to different sets separated by the potential and the energy, i.e., the allowed and forbidden regions.

Abishek Sriramulu, Christoph Bergmeir, Slawek Smyl

Real-world time series often exhibit complex interdependencies that cannot be captured in isolation. Global models that model past data from multiple related time series globally while producing series-specific forecasts locally are now common. However, their forecasts for each individual series remain isolated, failing to account for the current state of it

Aaryam Sharma, Chris Czarnecki, Yuhao Chen, Pengcheng Xi

Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring through the use of images and depth cameras. However, the current state-of-the-art image-based food portion estimation algorithms assume that users take images of their meals one or two

Nazim Bendib

Data augmentation plays a critical role in generating high-quality positive and negative pairs necessary for effective contrastive learning. However, common practices involve using a single augmentation policy repeatedly to generate multiple views, potentially leading to inefficient training pairs due to a lack of cooperation between views. Furthermore, to f

Hao Luo, Ahmed Alkhateeb

Compressive sensing is a promising solution for the channel estimation in multiple-input multiple-output (MIMO) systems with large antenna arrays and constrained hardware. Utilizing site-specific channel data from real-world systems, deep learning can be employed to learn the compressive sensing measurement vectors with minimum redundancy, thereby focusing s

Pablo Andújar Guerrero

We show that separability and second-countability are first-order properties among topological spaces definable in o-minimal expansions of $(\mathbb{R},<)$. We do so by introducing first-order characterizations -- definable separability and definable second-countability -- which make sense in a wider model-theoretic context. We prove that, within o-minimalit

Kun Meng, Hongsheng Zhang, Xi-Long Fan, Yuan Yong

We produce the gravitational waveforms for the extreme mass ratio inspiral systems (EMRIs) of binary stars moving around central supermassive black hole (SBH), or called B-EMRIs. We calculate the external orbits of the binary stars via the commonly used Hamilton-Jacobi (HJ) approach, and calculate the internal orbits of the binary stars via Lagrangian approa

Pablo Andújar Guerrero

We characterize the notion of definable compactness for topological spaces definable in o-minimal structures, answering questions of Peterzil and Steinhorn (1999) and Johnson (2018). Specifically, we prove the equivalence of various definitions of definable compactness in the literature, including those in terms of definable curves, definable types, and defi

Ganbileg Bat-Ochir, Khongorzul Dorjgotov, Uuganbayar Zunderiya

We derive explicit solutions for time-fractional anomalous diffusion equations with diffusivity coefficients that depend on both space and time variables. These solutions are expressed in Fox-H and generalized Wright functions, which are commonly used in anomalous diffusion equations. Our study represents a significant advancement in our understanding of ano

Boyd Branch, Piotr Mirowski, Kory Mathewson, Sophia Ppali

Social robotics researchers are increasingly interested in multi-party trained conversational agents. With a growing demand for real-world evaluations, our study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. This case study investigates human improvisers co-creating with conversational agents in a

Karwan Mustafa Kareem

Onion routing networks, also known as darknets, are private networks that enable anonymous communication over the Internet. They are used by individuals and organizations to protect their privacy, but they also attract cybercriminals who exploit the anonymity provided by these networks for illegal activities. This paper comprehensively analyzes cybercrime th

Karwan Mustafa Kareem

Satellite internet networks have emerged as indispensable components of the modern digital landscape, promising to extend connectivity to even the most remote corners of the globe. Among these networks, Starlink, pioneered by SpaceX, has garnered significant attention for its ambitious mission to provide high-speed internet access on a global scale. However,

Cedric Chauve, Caroline Colijn, Louxin Zhang

Good representations for phylogenetic trees and networks are important for optimizing storage efficiency and implementation of scalable methods for the inference and analysis of evolutionary trees for genes, genomes and species. We introduce a new representation for rooted phylogenetic trees that encodes a binary tree on n taxa as a vector of length 2n in wh

Kaitlyn J. Lee, Alan Hubbard, Alejandro Schuler

The average treatment effect (ATE) is a common parameter estimated in causal inference literature, but it is only defined for binary exposures. Thus, despite concerns raised by some researchers, many studies seeking to estimate the causal effect of a continuous exposure create a new binary exposure variable by dichotomizing the continuous values into two cat

Milad Beikbabaei, Brady Alexander, Ashwin Venkataramanan, Ali Mehrizi-Sani

As the composition of the power grid evolves to integrate more renewable generation, its reliance on distributed energy resources (DER) is increasing. Existing DERs are often controlled with proportional integral (PI) controllers that, if not properly tuned or if system parameters change, exhibit sluggish performance or large overshoot. The use of set point

Cheuk Ting Li

Given a Bayesian network structure (directed acyclic graph), the celebrated d-separation algorithm efficiently determines whether the network structure implies a given conditional independence relation. We show that this changes drastically when we consider two Bayesian network structures instead. It is undecidable to determine whether two given network stru

Milad Beikbabaei, Ali Mehrizi-Sani

The number of installed remote terminal units (RTU) is on the rise, increasing the observability and control of the power system. RTUs enable sending data to and receiving data from a control center in the power system. A distribution grid control center runs distribution management system (DMS) algorithms, where the DMS takes control actions during transien

Bowen Deng, Yunyeong Choi, Peichen Zhong, Janosh Riebesell

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have seen the emergence of universal MLIPs (uMLIPs) that are pre-trained on diverse materials datasets, providing opportunities for both ready-to-use universal force fields and robust foundations for downstream machine learning refinemen

Alexander Schwarz, Arian Mehrfard, Golchehr Amirkhani, Henry Phalen

Continuum Dexterous Manipulators (CDMs) are well-suited tools for minimally invasive surgery due to their inherent dexterity and reachability. Nonetheless, their flexible structure and non-linear curvature pose significant challenges for shape-based feedback control. The use of Fiber Bragg Grating (FBG) sensors for shape sensing has shown great potential in

Jack Birner, Marco Mazzoli, Eleonora Priori, Pietro Terna

Traditional notions of production function do not consider the time dimension, appearing thus timeless and instantaneous. We propose an agent-based model accounting for the whole production side of the economy to unfold the production process from its very beginning, when firms receive production orders, to the delivery of the products to the market. In the

Rui Wang, Ying-Qi Zhao, Oliver Dukes, Bo Zhang

Instrumental variables (IVs) are widely used to estimate causal effects from non-randomized data. A canonical example is a randomized trial with noncompliance, in which the randomized treatment assignment serves as an IV for the non-ignorable treatment received. Under a monotonicity assumption, a valid IV nonparametrically identifies the average treatment ef

Marco Polignano, Pierpaolo Basile, Giovanni Semeraro

In the pursuit of advancing natural language processing for the Italian language, we introduce a state-of-the-art Large Language Model (LLM) based on the novel Meta LLaMA-3 model: LLaMAntino-3-ANITA-8B-Inst-DPO-ITA. We fine-tuned the original 8B parameters instruction tuned model using the Supervised Fine-tuning (SFT) technique on the English and Italian lan

Basil M. Idrees, Shivangi Dubey Sharma, Ketan Rajawat

This work considers the decentralized successive convex approximation (SCA) method for minimizing stochastic non-convex objectives subject to convex constraints, along with possibly non-smooth convex regularizers. Although SCA has been widely applied in decentralized settings, its stochastic first order (SFO) complexity is unknown, and it is thought to be sl

Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket, Moshe Koppel

Semitic morphologically-rich languages (MRLs) are characterized by extreme word ambiguity. Because most vowels are omitted in standard texts, many of the words are homographs with multiple possible analyses, each with a different pronunciation and different morphosyntactic properties. This ambiguity goes beyond word-sense disambiguation (WSD), and may includ

Katsiaryna Haitsiukevich, Onur Poyraz, Pekka Marttinen, Alexander Ilin

This paper explores the efficacy of diffusion-based generative models as neural operators for partial differential equations (PDEs). Neural operators are neural networks that learn a mapping from the parameter space to the solution space of PDEs from data, and they can also solve the inverse problem of estimating the parameter from the solution. Diffusion mo

Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You

Structural Entropy (SE) measures the structural information contained in a graph. Minimizing or maximizing SE helps to reveal or obscure the intrinsic structural patterns underlying graphs in an interpretable manner, finding applications in various tasks driven by networked data. However, SE ignores the heterogeneity inherent in the graph relations, which is

Raphaël Ruimy, Swann Tubach

Over qcqs finite-dimensional schemes, we prove that \'etale motives of geometric origin can be characterised by a constructibility property which is purely categorical, giving a full answer to the question "Do all constructible \'etale motives come from geometry?" which dates back to Cisinski and D\'eglise's work. We also show that they afford the continuity

Michael Stoltz

This informative report provides a comprehensive analysis of how executive federal report agencies implement the National Institute of Standards and Technology's (NIST) Risk Management Framework (RMF) to achieve cybersecurity compliance. By exploring the concept and evolution of the RMF, the report delves into the framework's importance for enhancing cyberse

Zhanar Berikkyzy, Pamela E. Harris, Anna Pun, Catherine Yan

A fundamental identity in the representation theory of the partition algebra is $n^k = \sum_{\lambda} f^\lambda m_k^\lambda$ for $n \geq 2k$, where $\lambda$ ranges over integer partitions of $n$, $f^\lambda$ is the number of standard Young tableaux of shape $\lambda$, and $m_k^\lambda$ is the number of vacillating tableaux of shape $\lambda$ and length $2k$

Natalia Amburg, Mariia Kovaleva

The icosahedron $I_4$ of genus 4 is a dessin d'enfant embedded in Bring's curve $\mathcal{B}$. The dessin $I_4$ is related in some sense to a regular icosahedron $I_0$ embedded in the complex Riemann sphere. In particular, decompositions of Belyi functions $\beta_{I_0}: \mathbb{CP}^1 \rightarrow \mathbb{CP}^1$ and $\beta_{I_4}: \mathcal{B} \rightarrow \mathb