February 2024 arXiv papers — page 125

Wei Yang Tham, Joseph Staudt, Elisabeth Ruth Perlman, Stephanie D. Cheng

We study how delays in NIH grant funding affect the career outcomes of research personnel. Using comprehensive earnings and tax records linked to university transaction data along with a difference-in-differences design, we find that a funding interruption of more than 30 days has a substantial effect on job placements for personnel who work in labs with a s

Xin Tong, Bo Jin, Zhi Lin, Binjun Wang

Large Language Models (LLMs) have demonstrated significant potential and effectiveness across multiple application domains. To assess the performance of mainstream LLMs in public security tasks, this study aims to construct a specialized evaluation benchmark tailored to the Chinese public security domain--CPSDbench. CPSDbench integrates datasets related to p

Peng Wang, Xiang Wei, Fangxu Hu, Wenjuan Han

Natural language processing (NLP) is a key component of intelligent transportation systems (ITS), but it faces many challenges in the transportation domain, such as domain-specific knowledge and data, and multi-modal inputs and outputs. This paper presents TransGPT, a novel (multi-modal) large language model for the transportation domain, which consists of t

Yan Lin, Jilin Hu, Shengnan Guo, Bin Yang

Vehicle movement is frequently captured in the form of GPS trajectories, i.e., sequences of timestamped GPS locations. Such data is widely used for various tasks such as travel-time estimation, trajectory recovery, and trajectory prediction. A universal vehicle trajectory model could be applied to different tasks, removing the need to maintain multiple speci

Yunuo Xiong, Hongwei Xiong

Fictitious identical particle thermodynamics has emerged as a powerful tool to overcome the fermion sign problem, enabling highly accurate simulations of one thousand fermions in warm dense matter (T. Dornheim et al., J. Phys. Chem. Lett. 15, 1305 (2024)). However, inferring the thermodynamic properties of Fermi systems from a large number of exact numerical

Furio Honsell, Marina Lenisa, Ivan Scagnetto

We show that the principal types of the closed terms of the affine fragment of $\lambda$-calculus, with respect to a simple type discipline, are structurally isomorphic to their interpretations, as partial involutions, in a natural Geometry of Interaction model \`a la Abramsky. This permits to explain in elementary terms the somewhat awkward notion of linear

Homa Esfahanizadeh, Alejandro Cohen, Shlomo Shamai, Muriel Medard

Modern computationally-intensive applications often operate under time constraints, necessitating acceleration methods and distribution of computational workloads across multiple entities. However, the outcome is either achieved within the desired timeline or not, and in the latter case, valuable resources are wasted. In this paper, we introduce solutions fo

Dotan Gazith, Aaron B. Pearlman, Barak Zackay

The strict periodicity of pulsars is the primary source of information we have to learn about their nature and environment, it allows us to challenge general relativity and measure gravitational waves. Identifying such a periodicity from a discrete set of arrival times is a difficult algorithmic problem, particularly when the pulsar is in a binary system. Th

Mingyang Li, Han Pengsihua, Fujiao Meng, Zejun Wang

This academic paper examines the strategic interactions between Japan, other nations, and the International Atomic Energy Agency (IAEA) regarding Japan's decision to release treated nuclear wastewater from the Fukushima Daiichi Nuclear Power Plant into the sea. It introduces a payoff matrix and time-delay elements in replicator dynamic equations to mirror re

Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim

Offline Goal-Conditioned Reinforcement Learning (Offline GCRL) is an important problem in RL that focuses on acquiring diverse goal-oriented skills solely from pre-collected behavior datasets. In this setting, the reward feedback is typically absent except when the goal is achieved, which makes it difficult to learn policies especially from a finite dataset

Liang Wang, Xiang Tao, Qiang Liu, Shu Wu

Self-supervised learning on graphs can be bifurcated into contrastive and generative methods. Contrastive methods, also known as graph contrastive learning (GCL), have dominated graph self-supervised learning in the past few years, but the recent advent of graph masked autoencoder (GraphMAE) rekindles the momentum behind generative methods. Despite the empir

Kai Bai, Jia-Zheng Li, Tian-Rui Liu, Liang Fang

Topological modes (TMs) are typically localized at boundaries, interfaces and dislocations, and exponentially decay into the bulk of a large enough lattice. Recently, the non-Hermitian skin effect has been leveraged to delocalize the wavefunctions of TMs from the boundary and thus to increase the capacity of TMs dramatically. Here, we explore the capability

Mirosław Marszałek, Lukas Affolter, Oguzhan Kara, Klaus Kirch

In applications of optical multipass cells in photochemical reactors and laser excitation of weak transitions, estimation of the radiation dose in a volume of interest allows to assess the performance and optimize the design of the cell. We adopt radiant fluence as the figure of merit and employ the radiative transfer equation to derive analytical expression

Leonardo Tonetto, Pauline Kister, Nitinder Mohan, Jörg Ott

Networking research, especially focusing on human mobility, has evolved significantly in the last two decades and now relies on collection and analyzing larger datasets. The increasing sizes of datasets are enabled by larger automated efforts to collect data as well as by scalable methods to analyze and unveil insights, which was not possible many years ago.

Sira Vegas, Patricia Riofrio, Esperanza Marcos, Natalia Juristo

A recurring problem in software development is incorrect decision making on the techniques, methods and tools to be used. Mostly, these decisions are based on developers' perceptions about them. A factor influencing people's perceptions is past experience, but it is not the only one. In this research, we aim to discover how well the perceptions of the defect

Francis Rhys Ward, Matt MacDermott, Francesco Belardinelli, Francesca Toni

Intention is an important and challenging concept in AI. It is important because it underlies many other concepts we care about, such as agency, manipulation, legal responsibility, and blame. However, ascribing intent to AI systems is contentious, and there is no universally accepted theory of intention applicable to AI agents. We operationalise the intentio

Yiting Lu, Xin Li, Yajing Pei, Kun Yuan

Short-form UGC video platforms, like Kwai and TikTok, have been an emerging and irreplaceable mainstream media form, thriving on user-friendly engagement, and kaleidoscope creation, etc. However, the advancing content-generation modes, e.g., special effects, and sophisticated processing workflows, e.g., de-artifacts, have introduced significant challenges to

Zheng Li Bin Guo

In this paper, we mainly discuss the local regularity of the solution to the following problem \begin{align*} \begin{cases} -\dive({\bf{A}}(x)\nabla u(x))=f(x),&~x\in\Omega,\\ u(x)=0,&~x\in\partial\Omega, \end{cases} \end{align*} where $\Omega$ is a bounded domain in $\mathbb{R}^{n}$. In particular, we are concerned with the connection between the regularity

Bingbing Zhang, Shuo Liu, Shanmin Zhou, Daxiong Ji

We present a sensor misalignment-tolerant AUV navigation method that leverages measurements from an acoustic array and dead reckoned information. Recent studies have demonstrated the potential use of passive acoustic Direction of Arrival (DoA) measurements for AUV navigation without requiring ranging measurements. However, the sensor misalignment between the

Martín Solari, Sira Vegas, Natalia Juristo

Context: Experiment replications play a central role in the scientific method. Although software engineering experimentation has matured a great deal, the number of experiment replications is still relatively small. Software engineering experiments are composed of complex concepts, procedures and artefacts. Laboratory packages are a means of transfer-ring kn

Jie Ren, Yang Zhao, Weichuan Zhang, Changming Sun

Zero-shot incremental learning aims to enable the model to generalize to new classes without forgetting previously learned classes. However, the semantic gap between old and new sample classes can lead to catastrophic forgetting. Additionally, existing algorithms lack capturing significant information from each sample image domain, impairing models' classifi

V. V. Zavjalov, A. Savin, E. Sergeicheva, P. J. Hakonen

We study Homogeneously Precessing Domain (HPD) in superfluid $^3$He-B in a regular continuous-wave nuclear magnetic resonance (CW NMR) experiment. Using Fourier analysis of CW NMR time traces, we identify several oscillation modes with frequency monotonically increasing with the frequency shift of the HPD. Some of these modes are localized near the cell wall

Shanshan Xu, T. Y. S. S Santosh, Oana Ichim, Barbara Plank

In legal decisions, split votes (SV) occur when judges cannot reach a unanimous decision, posing a difficulty for lawyers who must navigate diverse legal arguments and opinions. In high-stakes domains, understanding the alignment of perceived difficulty between humans and AI systems is crucial to build trust. However, existing NLP calibration methods focus o

Omar Nemoul, Hichem Guergouri, Jamal Mimouni

This paper presents an in-depth exploration of timelike free geodesics in spatially curved Friedmann-Lema\^itre-Robertson-Walker (FLRW) spacetime. A unified approach for these geodesics encompassing both radial and non-radial trajectories across Euclidean, spherical, and hyperbolic geometries is employed. Using the symmetry properties of the system, two cons

Xin Chen, Takashi Kumagai, Jian Wang

We establish the quenched local limit theorem for reversible random walk on $\Z^d$ (with $d\ge 2$) among stationary ergodic random conductances that permit jumps of arbitrary length. The proof is based on the weak parabolic Harnack inequalities and on-diagonal heat-kernel estimates for long-range random walks on general ergodic environments. In particular, t

Kushagra Pandey, Maja Rudolph, Stephan Mandt

Diffusion models suffer from slow sample generation at inference time. Despite recent efforts, improving the sampling efficiency of stochastic samplers for diffusion models remains a promising direction. We propose Splitting Integrators for fast stochastic sampling in pre-trained diffusion models in augmented spaces. Commonly used in molecular dynamics, spli

Mingyang Li, Han Pengsihua, Songqing Zhao, Zejun Wang

On August 24, 2023, Japan controversially decided to discharge nuclear wastewater from the Fukushima Daiichi Nuclear Power Plant into the ocean, sparking intense domestic and global debates. This study uses evolutionary game theory to analyze the strategic dynamics between Japan, other countries, and the Japan Fisheries Association. By incorporating economic

Hajime Fujita, Kimiko Hasegawa, Yukie Inaba, Takefumi Kondo

We derive two formulas for the weighted sums of rooted spanning forests of particular sequence of graphs by using the matrix tree theorem. We consider cycle graphs with edges so called the pendant edges. One of our formula can be described as a variable transformation of the Chebyshev polynomial. They have particular algebraic properties.

Navid Keshtiarast, Marina Petrova

Adaptivity, reconfigurability and intelligence are key features of the next-generation wireless networks to meet the increasingly diverse quality of service (QoS) requirements of the future applications. Conventional protocol designs, however, struggle to provide flexibility and agility to changing radio environments, traffic types and different user service

Gonzalo Martínez, José Alberto Hernández, Javier Conde, Pedro Reviriego

The performance of conversational Large Language Models (LLMs) in general, and of ChatGPT in particular, is currently being evaluated on many different tasks, from logical reasoning or maths to answering questions on a myriad of topics. Instead, much less attention is being devoted to the study of the linguistic features of the texts generated by these LLMs.

Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong, Jinlin He

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation. We first utilize large language models (LLMs) to generate the initial layout and introduce a layout-guided 3D Gaussian representation for 3D content generation with adaptive geometric constraints. We then propose an instance-scene composi

Konstadinos H. Kiritsis

In this paper explicit necessary and sufficient conditions for the constrained Sylvester-observer equation are established, in order to have a solution over the field of real numbers. Furthermore, a procedure is given for the computation of the solution. Our approach is based on properties of real and polynomial matrices. Applications of the main results of

Rong-Jia Yang, Yong-Ben Shi

We consider baryogenesis in quantum fluctuation modified gravity. We explore three forms (two are newly proposed here) of baryogenesis interaction and discuss the effect of these interaction terms on the baryon-to-entropy ratio during the radiation era of the expanding universe. We constrain the model parameters with the current observational data, implying

Yihong Tang, Zhaokai Wang, Ao Qu, Yihao Yan

Citywalk, a recently popular form of urban travel, requires genuine personalization and understanding of fine-grained requests compared to traditional itinerary planning. In this paper, we introduce the novel task of Open-domain Urban Itinerary Planning (OUIP), which generates personalized urban itineraries from user requests in natural language. We then pre

Ji-Hwan Jung, Suh-Ryung Kim, Hyesun Yoon

Given a positive integer $m$, the $m$-step competition graph of a digraph $D$, denoted by $C^m(D)$, has the same vertex set as $D$ and has an edge between vertices $u$ and $v$ if and only if there exists a vertex $w$ such that there exist directed walks of length $m$ from $u$ to $w$ and from $v$ to $w$, respectively. In this paper, we completely characterize

Jonathan Breuer, Eyal Seelig

We study bounds on eigenvalue gaps for finite quotients of periodic Jacobi matrices on trees. We prove an Alon-Boppana type bound for the spectral gap and a comparison result for other eigenvalue gaps.

Fei Jiang, Yajie Zhang, Zhipeng Zhang

Bresch--Desjardins--Gisclon--Sart had derived that the capillarity slows down the growth rate of Rayleigh--Taylor (RT) instability in an inhomogeneous incompressible fluid endowed with internal capillarity based on a linearized incompressible Navier--Stokes--Korteweg (NSK) equations in 2008. Later Li--Zhang further obtained another result that the capillarit

Muqun Niu, Yuan Ren, Boyu Li, Chenchen Ding

Lightweight design of Convolutional Neural Networks (CNNs) requires co-design efforts in the model architectures and compression techniques. As a novel design paradigm that separates training and inference, a structural re-parameterized (SR) network such as the representative RepVGG revitalizes the simple VGG-like network with a high accuracy comparable to a

Bingqing Liu, Xikun Huang

A temporal graph can be considered as a stream of links, each of which represents an interaction between two nodes at a certain time. On temporal graphs, link prediction is a common task, which aims to answer whether the query link is true or not. To do this task, previous methods usually focus on the learning of representations of the two nodes in the query

Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus

In this paper, we prove that Distributional Reinforcement Learning (DistRL), which learns the return distribution, can obtain second-order bounds in both online and offline RL in general settings with function approximation. Second-order bounds are instance-dependent bounds that scale with the variance of return, which we prove are tighter than the previousl

Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan

Large language models (LLMs) like ChatGPT, exhibit powerful zero-shot and instruction-following capabilities, have catalyzed a revolutionary transformation across diverse fields, especially for open-ended tasks. While the idea is less explored in the graph domain, despite the availability of numerous powerful graph models (GMs), they are restricted to tasks

Cui-Qun Chen, Zhihui Luo, Meng Wang, Wéi Wú

Recently, the discovery of superconductivity in Ruddlesden-Popper (RP) $\mathrm{La_4Ni_3O_{10}}$ under pressure has further expanded the realm of nickelate-based superconductor family. In this paper, we performed a first-principle study of $\mathrm{La_4Ni_3O_{10}}$ for both $P2_1/a$ phase at ambient pressure and $I4/mmm$ phase at high pressure, with $U$=0, 3

Bao-Jun Lai, Fu-Lai Wang, Xiang Liu

In this work, we systematically study the electromagnetic properties including the M1 radiative decay widths and the magnetic moments of the isoscalar $\Xi_{c c} D^{(*)}$, $\Xi_{cc}D_{1}$, and $\Xi_{cc}D_{2}^{*}$ triple-charm molecular-type pentaquark candidates, where we adopt the constituent quark model and consider both the $S$-$D$ wave mixing effect and

Cong X. Kang, Aleksander Kelenc, Iztok Peterin, Eunjeong Yi

The modular product $G\diamond H$ of graphs $G$ and $H$ is a graph on vertex set $V(G)\times V(H)$. Two vertices $(g,h)$ and $(g',h')$ of $G\diamond H$ are adjacent if $g=g'$ and $hh'\in E(H)$, or $gg'\in E(G)$ and $h=h'$, or $gg'\in E(G)$ and $hh'\in E(H)$, or (for $g\neq g'$ and $h\neq h'$) $gg'\notin E(G)$ and $hh'\notin E(H)$. We derive the distance form

Liu Ziyin, Mingze Wang, Hongchao Li, Lei Wu

Symmetries are prevalent in deep learning and can significantly influence the learning dynamics of neural networks. In this paper, we examine how exponential symmetries -- a broad subclass of continuous symmetries present in the model architecture or loss function -- interplay with stochastic gradient descent (SGD). We first prove that gradient noise creates

H. Fabelo, S. Ortega, D. Ravi, B. R. Kiran

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the i

Junchi Yan, Fangyu Ding, Jiawei Sun, Zhaoping Hu

Graph invariant learning (GIL) seeks invariant relations between graphs and labels under distribution shifts. Recent works try to extract an invariant subgraph to improve out-of-distribution (OOD) generalization, yet existing approaches either lack explicit control over compactness or rely on hard top-$k$ selection that shrinks the solution space and is only

Alessandro V. M. Oliveira

This book, written in Portuguese, presents a comprehensive analysis of the air transport industry in Brazil, highlighting its vital importance to the country's economy. It explores the sector's complexity, from economic characteristics to interaction with the national aeronautical industry, through the specialization of the workforce and market demand analys

Bhisham Dev Verma, Rameshwar Pratap

Locality sensitive hashing (LSH) is a fundamental algorithmic toolkit used by data scientists for approximate nearest neighbour search problems that have been used extensively in many large scale data processing applications such as near duplicate detection, nearest neighbour search, clustering, etc. In this work, we aim to propose faster and space efficient

Rashid Ummer N. T., B. Sundar Rajan

Coded caching scheme originally proposed by Maddah-Ali and Niesen (MN) achieves an optimal transmission rate $R$ under uncoded placement but requires a subpacketization level $F$ which increases exponentially with the number of users $K$ where the number of files $N \geq K$. Placement delivery array (PDA) was proposed as a tool to design coded caching scheme

Karol Palka

We generalize Miyanishi's theory of almost minimal models of log smooth surfaces with reduced boundary to the case of arbitrary log surfaces defined over an algebraically closed field. Given an MMP run of a log surface $(X,D)$ we define and construct its almost minimal model, whose underlying surface has singularities not worse than $X$ and which differs fro

Mahdi Eskandari, Huiling Zhu, Jiangzhou Wang

A cell-free network merged with active reconfigurable reflecting surfaces (RIS) is investigated in this paper. Based on the imperfect channel state information (CSI), the aggregated channel from the user to the access point (AP) is initially estimated using the linear minimum mean square error (LMMSE) technique. The central processing unit (CPU) then detects

Patrice Tchofo-Dinda, Alix Malfondet, Philippe Grelu, Guy Millot

Important ongoing research on mode-locked fiber lasers aims at developing new types of multi-soliton regimes, such as soliton molecules, molecular complexes or soliton crystals. The on-demand generation of such multi-pulse structures is a major challenge, whereas experiments generally involve a tedious trial-and-error adjustment of the laser parameters. Here

Paolo Guasoni, Kasper Larsen, Giovanni Leoni

For constants $\gamma \in (0,1)$ and $A\in (1,\infty)$, we prove existence and uniqueness of a solution to the singular and path-dependent Riccati-type ODE \begin{align*} \begin{cases} h'(y) = \frac{1+\gamma}{y}\big( \gamma - h(y)\big)+h(y)\frac{\gamma + \big((A-\gamma)e^{\int_y^1 \frac{1-h(q)}{1-q}dq}-A\big)h(y)}{1-y},\quad y\in(0,1), h(0) = \gamma, \quad h

Chen-How Huang, Anastasiia Skurativska, F. Sebastian Bergeret, Miguel A. Cazalilla

A superconductor (SC) in proximity to a ferromagnetic insulator (FMI) is predicted to exhibit mixed singlet and triplet pair correlations. The magnetic proximity effect of FMI spin-splits the energy of Bogoliubov excitations and leads to a spin polarization at the surface for superconducting films thinner than the superconducting coherence length. In this wo

Ryota Iijima, Sayaka Shiota, Hitoshi Kiya

Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In previous studies, the use of models encrypted with a secret key was demonstrated to be robust against white-box attacks, but not against black-box ones. In this paper, we propose a novel method using the vision transformer (ViT) that is a random ensemble of encrypte

Willem Röpke, Mathieu Reymond, Patrick Mannion, Diederik M. Roijers

An important challenge in multi-objective reinforcement learning is obtaining a Pareto front of policies to attain optimal performance under different preferences. We introduce Iterated Pareto Referent Optimisation (IPRO), which decomposes finding the Pareto front into a sequence of constrained single-objective problems. This enables us to guarantee converge

Juan C. King, Roberto Dale, José M. Amigó

The objective of this paper is the construction of new indicators that can be useful to operate in the cryptocurrency market. These indicators are based on public data obtained from the blockchain network, specifically from the nodes that make up Bitcoin mining. Therefore, our analysis is unique to that network. The results obtained with numerical simulation

Ben Fei, Jingyi Xu, Rui Zhang, Qingyuan Zhou

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance Fields (NeRF). This technique has found diverse applications in areas such as robotics, urban mapping, autonomous navigation,

Jingwei Zuo, George Arvanitakis, Mthandazo Ndhlovu, Hakim Hacid

Human activity recognition (HAR) is a well-established field, significantly advanced by modern machine learning (ML) techniques. While companies have successfully integrated HAR into consumer products, they typically rely on a predefined activity set, which limits personalizations at the user level (edge devices). Despite advancements in Incremental Learning

Xiao-Jing Wei, Shun-Cai Zhao

Left-handedness signifies negative permittivity ($\varepsilon_r$) and permeability ((\mu_r)) in the same frequency band. The $\varepsilon_r$ and $\mu_r$ are evaluated in a quantized composite right-left handed transmission line (CRLH-TL), and the frequency band for left-handedness is also valuated in the balanced resonance ($ L_r C_l = L_l C_r $) and unbalan

Zhibo Hu, Chen Wang, Yanfeng Shu, Helen

The robustness of large language models (LLMs) becomes increasingly important as their use rapidly grows in a wide range of domains. Retrieval-Augmented Generation (RAG) is considered as a means to improve the trustworthiness of text generation from LLMs. However, how the outputs from RAG-based LLMs are affected by slightly different inputs is not well studi

Thibault Roch, Efim A. Brener, Jean-François Molinari, Eran Bouchbinder

The emergence of statistical complexity in frictional systems, manifested in broad distributions of various observables, is not yet understood. We study this problem in velocity-driven, homogeneous (no quenched disorder) unstable frictional systems of height $H$. The latter are described at the continuum scale within a realistic rate-and-state friction inter

Jingwei Zuo, Hakim Hacid

Human Activity Recognition (HAR) has been studied for decades, from data collection, learning models, to post-processing and result interpretations. However, the inherent hierarchy in the activities remains relatively under-explored, despite its significant impact on model performance and interpretation. In this paper, we propose H-HAR, by rethinking the HAR

Di Wang

The origin of the quasi-periodic eruptions (QPEs) is possibly mass loss at the periastron of a body moving around the supermassive black hole (SMBH) in a high eccentric orbit. Such a tidally stripped star is expected to radiate gravitational wave thereby leading to shrinkage of the periastron distance, and thus will eventually be disrupted by the SMBH in the

Michael Th. Rassias

One of the themes of this paper is recent results on large gaps between primes. The first of these results has been achieved in the paper [12] by Ford, Green, Konyagin and Tao. It was later improved in the joint paper [13] of these four authors with Maynard. One of the main ingredients of these results are old methods due to Erd\H{o}s and Rankin. Other ingre

Guanchong Cheng, Lei Ni, Yajie Chen, Jun Lin

Ellerman bombs (EBs) with significant H$\alpha$ wing emissions and ultraviolet bursts (UV bursts) with strong Si IV emissions are two kinds of small transient brightening events that occur in the low solar atmosphere.We numerically investigated the magnetic reconnection process between the emerging arch magnetic field and the lower atmospheric background mag

Pengcheng An, Jiawen Zhu, Zibo Zhang, Yifei Yin

Voice messages, by nature, prevent users from gauging the emotional tone without fully diving into the audio content. This hinders the shared emotional experience at the pre-retrieval stage. Research scarcely explored "Emotional Teasers"-pre-retrieval cues offering a glimpse into an awaiting message's emotional tone without disclosing its content. We introdu

Akshat Gautam, Anurag Shandilya, Akshit Srivastava, Venkatapathy Subramanian

The necessity of large amounts of labeled data to train deep models, especially in medical imaging creates an implementation bottleneck in resource-constrained settings. In Insite (labelINg medical imageS usIng submodular funcTions and sEmi-supervised data programming) we apply informed subset selection to identify a small number of most representative or di

Diana Nunez, Diego Cordoba, Mario Octavio Cotilla, Antonio Pazos

The complex tectonic region of NE Caribbean, where Hispaniola and Puerto Rico are located, is bordered by subduction zone with oblique convergence in the north and by incipient subduction zone associated to Muertos Trough in the south. Central Caribbean basin is characterized by the presence of a prominent topographic structure known as Beata Ridge, whose oc

Marie-Thérèse Aimar, Abdelkader Intissar

This paper reviews the results of existence and uniqueness of the solutions of these equations: the Korteweg-de Vries equation, the Kuramoto-Sivashinsky equation, the generalized Korteweg-de Vries-Kuramoto-Sivashinski equation and the non homogeneous boundary value problem for KdV-KS equation in quarter plane.

Junha Kang, Taekoo Oh, Junhyun Lee, Bohm-Jung Yang

Despite its abundance in nature, predicting the occurrence of ferromagnetism in the ground state is possible only under very limited conditions such as in a flat band system with repulsive interaction or in a band with a single hole under infinitely large Coulomb repulsion, etc. Here, we propose a general condition to achieve saturated ferromagnetism based o

R. Cerezo, A. Bogarin, M. Esteban, C. Romero

Content assessment has broadly improved in e-learning scenarios in recent decades. However, the eLearning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only content, but also students' acquisition of core skills such as self-regulated learning. Our objective was to discover students' self-regulate

Wenbo Lyu

The rapid development of the digital economy has had a profound impact on the implementation of the rural revitalization strategy. Based on this, this study takes Hainan Province as the research object to deeply explore the impact of digital economic development on rural revitalization. The study collected panel data from 2003 to 2022 to construct an evaluat

R. Ferreira-Mello, M. Andre, A. Pinheiro, E. Costa

The explosive growth of online education environments is generating a massive volume of data, specially in text format from forums, chats, social networks, assessments, essays, among others. It produces exciting challenges on how to mine text data in order to find useful knowledge for educational stakeholders. Despite the increasing number of educational app

Andreas Bäuerle, Christian Mauz

We classify the locally factorial Fano fourfolds of Picard number two with a hypersurface Cox ring that admit an effective action of a three-dimensional torus.

V. M. Buchstaber, A. P. Veselov

We use the differential algebra of polytopes to explain the known remarkable relation of the combinatorics of the associahedra and permutohedra with the universal compositional and multiplicative inversion formulas for the formal power series. This approach allows to single out the associahedra and permutohedra among all graph-associahedra and emphasizes the

Wenbo Lyu, Jiayi Zhu, Yunan Ding, Keming Zhang

This paper proposes a referencable pattern of the recovery of the consumption sector, a new dimension to observe and evaluate the intrinsic value of the consumption sector, and proposes the concept of sensory-based consumption and the ranking of the weights of different categories;creates the concept of digital consumption index, coupled with digital RMB ind

Zehao Dong, Yixin Chen, Hiram Gay, Yao Hao

Treatment planning is currently a patient specific, time-consuming, and resource demanding task in radiotherapy. Dose-volume histogram (DVH) prediction plays a critical role in automating this process. The geometric relationship between DVHs in radiotherapy plans and organs-at-risk (OAR) and planning target volume (PTV) has been well established. This study

Arifa Khan, P. Saravanan, S. K Venkatesan

We provide a birds eye view of the rapid developments in AI and Deep Learning that has led to the path-breaking emergence of AI in Large Language Models. The aim of this study is to place all these developments in a pragmatic broader historical social perspective without any exaggerations while at the same time without any pessimism that created the AI winte

Farahmand Hasanov, Nikita Kolganov

Instantons present a deep insight into non-perturbative effects both in physics and mathematics. While leading instanton effects can be calculated simply as an exponent of the instanton action, the calculation of subleading contributions usually requires the spectrum of fluctuation operator on the instanton background and its Green's function, explicit knowl

Madhav Khirwar, Ankur Narang

Air pollution represents a pivotal environmental challenge globally, playing a major role in climate change via greenhouse gas emissions and negatively affecting the health of billions. However predicting the spatial and temporal patterns of pollutants remains challenging. The scarcity of ground-based monitoring facilities and the dependency of air pollution

H. Witała, J. Golak, R. Skibiński

We discuss two approaches which, by applying the screening method, permit one to include the long range proton-proton (pp) Coulomb force in proton-deuteron (pd) momentum-space scattering calculations. In the first one, based on Alt-Grassberger-Sandhas (AGS) equation, presented in Phys. Rev. C{\bf{71}}, 054005 (2005) and {\bf{73}}, 057001 (2006), one needs to

Mohammad Amin Jarrahi, Eirina Bourtsoulatze, Vahid Abolghasemi

Nowadays, the demand for image transmission over wireless networks has surged significantly. To meet the need for swift delivery of high-quality images through time-varying channels with limited bandwidth, the development of efficient transmission strategies and techniques for preserving image quality is of importance. This paper introduces an innovative app

Filip Cernatic, Emmanuel Fromager

A recent work [arXiv:2401.04685] has merged $N$-centered ensembles of neutral and charged electronic ground states with ensembles of neutral ground and excited states, thus providing a general and in-principle exact (so-called extended $N$-centered) ensemble density functional theory of neutral and charged electronic excitations. This formalism made it possi

Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes

We propose a new procedure named PASOA, for Bayesian experimental design, that performs sequential design optimization by simultaneously providing accurate estimates of successive posterior distributions for parameter inference. The sequential design process is carried out via a contrastive estimation principle, using stochastic optimization and Sequential M

Mordehai Milgrom

It is shown that the foundational axioms of MOND alone predict a strong correlation between a bulk measure of the baryonic surface density, $\Sigma_B$, and the corresponding dynamical one, $\Sigma_D$, of an isolated object, such as a galaxy. The correlation is encapsulated by its high- and low-$\Sigma_B$ behaviors. For $\Sigma_B\gg\Sigma_M\equiv a_0/2\pi G$

Claudionor N. Coelho, Hanchen Xiong, Tushar Karayil, Sree Koratala

The advancement of Large Language Models (LLM) has also resulted in an equivalent proliferation in its applications. Software design, being one, has gained tremendous benefits in using LLMs as an interface component that extends fixed user stories. However, inclusion of LLM-based AI agents in software design often poses unexpected challenges, especially in t

Xidong Feng, Ziyu Wan, Mengyue Yang, Ziyan Wang

Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks. However, RL is often hindered by issues such as low sample efficiency, lack of interpretability, and sparse supervision signals. To tackle these limitations, we take inspiration from the human learning process and introduce Natural Language Reinforcemen

Jun Hu, Pengzhan Jin

We propose a hybrid iterative method based on MIONet for PDEs, which combines the traditional numerical iterative solver and the recent powerful machine learning method of neural operator, and further systematically analyze its theoretical properties, including the convergence condition, the spectral behavior, as well as the convergence rate, in terms of the

A. Shukla, J. Wright, A. Henningsson, H. Stieglitz

Cadmium Telluride (CdTe) solar cell technology is a promising candidate to help boost green energy production. However, impurities and structural defects are major barriers to improving the solar power conversion efficiency. Grain boundaries often act as aggregation sites for impurities, resulting in strain localization in areas of high diffusion. In this st

Arend Bayer, Alexander Kuznetsov, Emanuele Macrì

We give a proof of Mukai's Theorem on the existence of certain exceptional vector bundles on prime Fano threefolds. To our knowledge this is the first complete proof in the literature. The result is essential for Mukai's biregular classification of prime Fano threefolds, and for the existence of semiorthogonal decompositions in their derived categories. Our

Beatrice Lorenz, Aras Bacho, Gitta Kutyniok

This paper provides rigorous error bounds for physics-informed neural networks approximating the semilinear wave equation. We provide bounds for the generalization and training error in terms of the width of the network's layers and the number of training points for a tanh neural network with two hidden layers. Our main result is a bound of the total error i

Dayou Chen, Sibo Cheng, Jinwei Hu, Matthew Kasoar

Wildfire prediction has become increasingly crucial due to the escalating impacts of climate change. Traditional CNN-based wildfire prediction models struggle with handling missing oceanic data and addressing the long-range dependencies across distant regions in meteorological data. In this paper, we introduce an innovative Graph Neural Network (GNN)-based m

Vikas Jangra, Satender Kataria, Max C. Lemme

Graphene has been extensively studied for a variety of electronic and optoelectronic applications. The reported contact resistance between metal and graphene, or rather its specific contact resistance (R{_C}), ranges from a few tens of {\Omega} {\mu}m up to a few k{\Omega} {\mu}m. Manufacturable solutions for defining ohmic contacts to graphene remain a subj

Mattia Ornaghi, Saurabh Singh, Amnon Yekutieli

In this paper we treat Grothendieck Duality for noetherian rings via rigid dualizing complexes. In particular, we prove that every ring, essentially finite type over a regular base ring, has a unique rigid dualizing complex. The rigid dualizing complexes have strong functorial properties, allowing us to construct the twisted induction pseudofunctor, which is

Kazuki Hasebe

Exploiting analogies between the precessing quantum spin system and the charge-monopole system, we construct Bloch hyper-spheres with $\it{exact}$ spherical symmetries in arbitrary dimensions. Such Bloch hyper-spheres are realized as a collection of the orbits of a precessing quantum spin. The geometry of Bloch hyper-spheres is exactly equal to the quantum N

Tingting Wang, Guilin Qi, Tianxing Wu

Fault localization is challenging in online micro-service due to the wide variety of monitoring data volume, types, events and complex interdependencies in service and components. Faults events in services are propagative and can trigger a cascade of alerts in a short period of time. In the industry, fault localization is typically conducted manually by expe

Eric L. Buehler, Markus J. Buehler

We report a mixture of expert strategy to create fine-tuned large language models using a deep layer-wise token-level approach based on low-rank adaptation (LoRA). Starting with a set of pre-trained LoRA adapters, our gating strategy uses the hidden states to dynamically mix adapted layers, allowing the resulting X-LoRA model to draw upon different capabilit

Martin S. Talla Noutack, Fabienne Amann, Sophie Nowak, Régis Poulain

Variations with oxygen concentration of titanium lattice parameters are obtained by means of ab initio calculations, considering the impact of oxygen ordering. The quasiharmonic approximation is used to take into account the thermal expansion at finite temperature. Results show that lattice parameters depend mainly on oxygen concentration and, to a lesser ex