May 2024 arXiv papers — page 91

Sebastian Bruch, Aditya Krishnan, Franco Maria Nardini

Clustering-based nearest neighbor search is an effective method in which points are partitioned into geometric shards to form an index, with only a few shards searched during query processing to find a set of top-$k$ vectors. Even though the search efficacy is heavily influenced by the algorithm that identifies the shards to probe, it has received little att

Tong Zeng, Daniel E. Acuna

Scientist learn early on how to cite scientific sources to support their claims. Sometimes, however, scientists have challenges determining where a citation should be situated -- or, even worse, fail to cite a source altogether. Automatically detecting sentences that need a citation (i.e., citation worthiness) could solve both of these issues, leading to mor

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo

Metacognitive knowledge refers to humans' intuitive knowledge of their own thinking and reasoning processes. Today's best LLMs clearly possess some reasoning processes. The paper gives evidence that they also have metacognitive knowledge, including ability to name skills and procedures to apply given a task. We explore this primarily in context of math reaso

Benoît Assi, Henry Lamm

The simulation of lattice gauge theories on quantum computers necessitates digitizing gauge fields. One approach involves substituting the continuous gauge group with a discrete subgroup, but the implications of this approximation still need to be clarified. To gain insights, we investigate the subduction of $ SU(2) $ and $ SU(3)$ to discrete crystal-like su

Sumi Lee, Gondy Leroy, David Kauchak, Melissa Just

This study investigates human and ChatGPT text simplification and its relationship to dependency distance. A set of 220 sentences, with increasing grammatical difficulty as measured in a prior user study, were simplified by a human expert and using ChatGPT. We found that the three sentence sets all differed in mean dependency distances: the highest in the or

Jiajun He, Gergely Flamich, José Miguel Hernández-Lobato

Relative entropy coding (REC) algorithms encode a random sample following a target distribution $Q$, using a coding distribution $P$ shared between the sender and receiver. Sadly, general REC algorithms suffer from prohibitive encoding times, at least on the order of $2^{D_{\text{KL}}[Q||P]}$, and faster algorithms are limited to very specific settings. This

Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon

In this work, we present an arbitrary-scale super-resolution (SR) method to enhance the resolution of scientific data, which often involves complex challenges such as continuity, multi-scale physics, and the intricacies of high-frequency signals. Grounded in operator learning, the proposed method is resolution-invariant. The core of our model is a hierarchic

Hongdi Huang, Van C. Nguyen, Padmini Veerapen, Kent B. Vashaw

We show that if two $m$-homogeneous algebras have Morita equivalent graded module categories, then they are quantum-symmetrically equivalent, that is, there is a monoidal equivalence between the categories of comodules for their associated universal quantum groups (in the sense of Manin) which sends one algebra to the other. As a consequence, any Zhang twist

Xianpeng Liu, Ce Zheng, Ming Qian, Nan Xue

We present Multi-View Attentive Contextualization (MvACon), a simple yet effective method for improving 2D-to-3D feature lifting in query-based multi-view 3D (MV3D) object detection. Despite remarkable progress witnessed in the field of query-based MV3D object detection, prior art often suffers from either the lack of exploiting high-resolution 2D features i

Dhruv Bhasin, Sayar Karmakar, Moumanti Podder, Souvik Roy

Each vertex of the infinite $2$-dimensional square lattice graph is assigned, independently, a label that reads trap with probability $p$, target with probability $q$, and open with probability $(1-p-q)$, and each edge is assigned, independently, a label that reads trap with probability $r$ and open with probability $(1-r)$. A percolation game is played on t

H. V. Ovcharenko, O. B. Zaslavskii

According to the Banados-SIlk-West (BSW) effect, two particles moving towards a black hole, can collide near the horizon with an unbounded energy in the center of mass frame. This requires one of particles to have fine-tuned parameters in such a way that the time component of generalized momentum is zero $X=0$. Thus the existence of such trjectories is a nec

Banafsheh Saber Latibari, Sujan Ghimire, Muhtasim Alam Chowdhury, Najmeh Nazari

Obfuscation stands as a promising solution for safeguarding hardware intellectual property (IP) against a spectrum of threats including reverse engineering, IP piracy, and tampering. In this paper, we introduce Obfus-chat, a novel framework leveraging Generative Pre-trained Transformer (GPT) models to automate the obfuscation process. The proposed framework

Marek M. Rams, Gabriela Wójtowicz, Aritra Sinha, Juraj Hasik

We present an open-source tensor network Python library for quantum many-body simulations. At its core is an abelian-symmetric tensor, implemented as a sparse block structure managed by logical layer on top of dense multi-dimensional array backend. This serves as the basis for higher-level tensor networks algorithms, operating on matrix product states and pr

Thiago S. Vaillant, Felipe Deveza de Almeida, Paulo Anselmo M. S. Neto, Cuiyun Gao

As Large Language Models (LLMs), including ChatGPT and analogous systems, continue to advance, their robust natural language processing capabilities and diverse applications have garnered considerable attention. Nonetheless, despite the increasing acknowledgment of the convergence of Artificial Intelligence (AI) and Software Engineering (SE), there is a lack

Li Gong, Alex R. Wright, Kullervo Hynynen, David E. Goertz

Thrombolytic occlusions in stroke, pulmonary embolism and the peripheral vasculature are increasingly treated with aspiration, a catheter-based approach that employs suction to extract clots through a hollow catheter lumen. Unfortunately, aspiration is frequently unsuccessful in extracting more challenging clots, which can become corked in the distal tip. We

Nur Ahmed, Amit Das, Kirsten Martin, Kawshik Banerjee

The transformative potential of AI presents remarkable opportunities, but also significant risks, underscoring the importance of responsible AI development and deployment. Despite a growing emphasis on this area, there is limited understanding of industry's engagement in responsible AI research, i.e., the systematic examination of AI's ethical, social, and l

Purna P. Paudel, Nathan O. Smith, Tudor D. Stanescu

Disorder effects in hybrid semiconductor-superconductor (SM-SC) nanowires, widely recognized as the main obstacle to realizing stable Majorana zero modes (MZMs) in these structures, have been systematically investigated theoretically in recent years. However, there are no corresponding detailed studies of disorder effects in planar Josephson junction (JJ) st

Paolo Sentinelli

We prove that the combinatorial invariance conjecture for parabolic Kazhdan-Lusztig polynomials, formulated by Mario Marietti, is equivalent to its restriction to maximal quotients. This equivalence lies at the other extreme in respect to the equivalence, recently proved by Barkley and Gaetz, with the invariance conjecture for Kazhdan-Lusztig polynomials, wh

Lilian Matthiesen, Joni Teräväinen, Mengdi Wang

We prove quantitative estimates for averages of the von Mangoldt and M\"obius functions along polynomial progressions $n+P_1(m),\ldots, n+P_k(m)$ for a large class of polynomials $P_i$. The error terms obtained save an arbitrary power of logarithm, matching the classical Siegel--Walfisz error term. These results give the first quantitative bounds for the Tao

Garrett M. Brown

We show that if $(M,\omega)$ is any compact K\"ahler manifold, then the blowup of $M$ at any point furnishes a K\"ahler metric with scalar curvature globally and arbitrarily $C^0$-close to the scalar curvature of $\omega$. It follows that if $M$ admits a positive scalar curvature K\"ahler metric, then so do all of its blowups. This special case extends a res

Matthew Maitra, Jeroen Tromp

The weak-field limit of Einstein--Cartan (EC) relativity is studied. The equations of EC theory are rewritten such that they formally resemble those of Einstein General Relativity (EGR); this allows ideas from post-Newtonian theory to be imported without essential change. The equations of motion are then written both at first post-Newtonian (1PN) order and a

Shir Barzel, Moshe Salhov, Ofir Lindenbaum, Amir Averbuch

Modern cameras typically offer two types of image states: a minimally processed linear raw RGB image representing the raw sensor data, and a highly-processed non-linear image state, such as the sRGB state. The CIE-XYZ color space is a device-independent linear space used as part of the camera pipeline and can be helpful for computer vision tasks, such as ima

Alfredo Capozucca, Maximiliano Cristiá, Ross Horne, Ricardo Katz

This paper revisits the Brewer-Nash security policy model inspired by ethical Chinese Wall policies. We draw attention to the fact that write access can be revoked in the Brewer-Nash model. The semantics of write access were underspecified originally, leading to multiple interpretations for which we provide a modern operational semantics. We go on to moderni

Yuxi Li, Yi Liu, Yuekang Li, Ling Shi

Large language models (LLMs) have revolutionized various applications, making robust safety alignment essential to prevent harmful outputs. Current safety alignment techniques, however, harbor inherent vulnerabilities due to their reliance on logit suppression. In this work, we identify critical logit-level vulnerabilities by introducing Semantic-sensitive A

Juhan Bae, Wu Lin, Jonathan Lorraine, Roger Grosse

Many training data attribution (TDA) methods aim to estimate how a model's behavior would change if one or more data points were removed from the training set. Methods based on implicit differentiation, such as influence functions, can be made computationally efficient, but fail to account for underspecification, the implicit bias of the optimization algorit

Stéphane Gaubert, Yiannis Vlassopoulos

Large Language Models are transformer neural networks which are trained to produce a probability distribution on the possible next words to given texts in a corpus, in such a way that the most likely word predicted is the actual word in the training text. In this paper we find what is the mathematical structure defined by such conditional probability distrib

Jan A. Krzywda, Łukasz Cywiński

Electron shuttling is one of the current avenues being pursued to scale semiconductor quantum dot-based spin qubits. Adiabatic spin qubit transfer along a chain of tunnel-coupled quantum dots is one of the possible schemes. In this scheme, we theoretically analyze the dephasing of a spin qubit that is adiabatically transferred between two tunnel-coupled quan

Aditya Shankar Kar, Kiran Kumar Challa, Alok Kumar Bharati, Ankit Singhal

Active distribution system with high penetration of inverter based distributed energy resources (DER) can be utilized for VAR-related ancillary services. To utilize the DER flexibility, transmission system operator (TSO) must be presented with the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation questions th

Ye Liu, Xuelei Lin, Yejia Chen, Reynold Cheng

Current graph clustering methods emphasize individual node and edge con nections, while ignoring higher-order organization at the level of motif. Re cently, higher-order graph clustering approaches have been designed by motif based hypergraphs. However, these approaches often suffer from hypergraph fragmentation issue seriously, which degrades the clustering

Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino

With the advent of supercomputers, multi-processor environments and parallel-in-time (PinT) algorithms offer ways to solve initial value problems for ordinary and partial differential equations (ODEs and PDEs) over long time intervals, a task often unfeasible with sequential solvers within realistic time frames. A recent approach, GParareal, combines Gaussia

Marco Bagnara, Lucio Galeati, Mario Maurelli

We consider the generalised Surface Quasi-Geostrophic (gSQG) equations in $\mathbb R^2$ with parameter $\beta\in (0,1)$, an active scalar model interpolating between SQG ($\beta=1$) and the 2D Euler equations ($\beta=0$) in vorticity form. Existence of weak $(L^1\cap L^p)$-valued solutions in the deterministic setting is known, but their uniqueness is open.

Yan Ru Pei, Olivier Coenen

We introduce a class of neural networks named PLEIADES (PoLynomial Expansion In Adaptive Distributed Event-based Systems), which contains temporal convolution kernels generated from orthogonal polynomial basis functions. We focus on interfacing these networks with event-based data to perform online spatiotemporal classification and detection with low latency

Dhruv Pathak, Debarati Chatterjee

With precision pulsar timing, measured values of a large set of pulsar parameters are obtainable. For some of those parameters, such as the time-derivatives of spin or orbital periods (in the case of binary pulsars), the measured values are not the intrinsic values of the parameters as they contain contributions from the dynamical effects. In the case of orb

Aksel Kobiałka, Oladunjoye A. Awoga, Martin Leijnse, Tadeusz Domański

We investigate the properties of a Fibonacci quasicrystal (QC) arrangement of a one-dimensional topological superconductor, such as a magnetic atom chain deposited on a superconducting surface. We uncover a general mutually exclusive competition between the QC properties and the topological superconducting phase with Majorana bound states (MBS): there are no

Marinos Vomvas, Norbert Ludant, Guevara Noubir

The fifth generation (5G) of cellular networks starts a paradigm shift from the traditional monolithic system design to a Service Based Architecture, that fits modern performance requirements and scales efficiently to new services. This paradigm will be the foundation of future cellular core networks beyond 5G. The new architecture splits network functionali

Christopher L. Carilli, Bojan Nikolic, Laura Torino, Ubaldo Iriso

We demonstrate the Shape-Orientation-Size conservation principle for a 3-element interferometer using aperture plane masking at the ALBA visible synchrotron radiation light source. We then use these data to demonstrate Image Plane Self-Calibration.

Vaibhav Dhore, Achintya Bhat, Viraj Nerlekar, Kashyap Chavhan

We present a new technique that explains the output of a CNN-based model using a combination of GradCAM and LRP methods. Both of these methods produce visual explanations by highlighting input regions that are important for predictions. In the new method, the explanation produced by GradCAM is first processed to remove noises. The processed output is then mu

Haoxiang Shi, Jiaan Wang, Jiarong Xu, Cen Wang

Text-to-Table aims to generate structured tables to convey the key information from unstructured documents. Existing text-to-table datasets are typically oriented English, limiting the research in non-English languages. Meanwhile, the emergence of large language models (LLMs) has shown great success as general task solvers in multi-lingual settings (e.g., Ch

Daniel Sinambela, Weiren Zhao, Ruizhao Zi

In this paper, we investigate the asymptotic stability of the three-dimensional Couette flow in a stratified fluid governed by the Stokes-transport equation. We observe that a similar lift-up effect to the three-dimensional Navier-Stokes equation near Couette flow destabilizes the system. We find that the inviscid damping type decay due to the Couette flow t

Arjun Parmar, Corey D Grozier, Robert Dima, Jessica E Tolzman

Advancements in wireless ultrasound technology allow for point of care cartilage imaging, yet validation against traditional ultrasound units remains to be established for knee cartilage outcomes. Therefore, the purpose of our study was to establish the agreement of articular cartilage thickness and echo-intensity measures between traditional and wireless ul

W. Spencer Smith, Ao Dong, Jacques Carette, Michael D. Noseworthy

We selected 29 medical imaging projects from 48 candidates, assessed 10 software qualities by answering 108 questions for each software project, and interviewed 8 of the 29 development teams. Based on the quantitative data, we ranked the MI software with the Analytic Hierarchy Process (AHP). The four top-ranked software products are 3D Slicer, ImageJ, Fiji,

Hamid Hassanzadeh, Kevin Vasconcellos

It is shown that in a Cohen-Macaulay local ring, the generic linkage of an ideal $I$ is a deformation of the arbitrary linkage of $I$. This fact does not need $I$ to be a Cohen-Macaulay ideal. The same holds for $s$-residual intersections of $I$ when $s$ does not exceed the height of $I$ by one. Under some slight conditions on $I$, one further generalizes th

Alexander I. Efimov

In this paper we introduce and study the so-called continuous $K$-theory for a certain class of "large" stable $\infty$-categories, more precisely, for dualizable presentable categories. For compactly generated categories, the continuous $K$-theory is simply the usual (non-connective) $K$-theory of the full subcategory of compact objects. More generally, we

Vishnu V. Ratnam, Bilal Sadiq, Hao Chen, Wei Sun

Although Wi-Fi is an ideal technology for many ranging applications, the performance of current methods is limited by the system bandwidth, leading to low accuracy of $\sim 1$ m. For many applications, measuring differential range, viz., the change in the range between adjacent measurements, is sufficient. Correspondingly, this work proposes WiDRa - a Wi-Fi

Ritwik Gupta, Leah Walker, Eli Glickman, Raine Koizumi

The integration of artificial intelligence (AI) into military capabilities has become a norm for major military power across the globe. Understanding how these AI models operate is essential for maintaining strategic advantages and ensuring security. This paper demonstrates an open-source methodology for analyzing military AI models through a detailed examin

Daniel Sinambela, Weiren Zhao, Ruizhao Zi

We study the Stokes-transport system in a two-dimensional channel with horizontally moving boundaries, which serves as a reduced model for oceanography and sedimentation. The density is transported by the velocity field, satisfying the momentum balance between viscosity, pressure, and gravity effects, described by the Stokes equation at any given time. Due t

Yanlong Shi, Kyle Kremer, Philip F. Hopkins

The detection of supermassive black holes (SMBHs) in high-redshift luminous quasars may require a phase of rapid accretion, and as a precondition, substantial gas influx toward seed black holes (BHs) from kilo-parsec or parsec scales. Our previous research demonstrated the plausibility of such gas supply for BH seeds within star-forming giant molecular cloud

Xiaobo Liang, Haoke Zhang, Helan hu, Juntao Li

The rapid advancement of large language models has given rise to a plethora of applications across a myriad of real-world tasks, mainly centered on aligning with human intent. However, the complexities inherent in human intent necessitate a dependence on labor-intensive and time-consuming human evaluation. To alleviate this constraint, we delve into the para

A. Belyaev, L. Cerrito, E. Lunghi, S. Moretti

The first model-independent sensitivity to CPT violation in the top-quark sector is extracted from ATLAS and CMS measurements of the top and antitop kinematical mass difference. We find that the temporal component of a CPT-violating background field interacting with the top-quark vector current is restricted within the interval $[-0.13,0.29]$ GeV at 95% conf

Jiaoyang Huang, Theo McKenzie, Horng-Tzer Yau

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq 3$, and denote the eigenvalues as $\lambda_1=d/\sqrt{d-1}\geq \lambda_2\geq\lambda_3\cdots\geq \lambda_N$. We prove that the optimal (up to an extra $N^{{\rm o}_N(1)}$ factor, where ${\rm o}_N(1)$ can be arbitrarily small) eigenvalue rigidity hold

Xiaofang Gao, Martino Garonzi

A family of groups is called (maximal) cyclic bounded ((M)CB) if, for every natural number $n$, there are only finitely many groups in the family with at most $n$ (maximal) cyclic subgroups. We prove that the family of groups of prime power order is MCB. We also prove that the family of finite groups without cyclic coprime direct factors is CB. As a conseque

Tullio Basaglia, Zane W. Bell, Daniele D'Agostino, Paul V. Dressendorfer

Geant4 is an object-oriented toolkit for the simulation of the passage of particles through matter. Its development was initially motivated by the requirements of physics experiments at high energy hadron colliders under construction in the last decade of the 20th century. Since its release in 1998, it has been exploited in many different applicative fields,

Saranyamol V. S., Jithin Sreekumar, Mohammed Ibrahim S

An experimental investigation was carried out to study heat transfer rates in a high-temperature, high-pressure region generated using the shock focusing technique. A shock tube test facility with a specially designed spherically converging test section was used in the present study. Two test cases, a shock of initial strength Mach 2 and Mach 4, were investi

H. M. Nagesh

For a simple graph $G$, a vertex labeling $\phi:V(G) \rightarrow \{1, 2,\ldots,k\}$ is called $k$-labeling. The weight of an edge $xy$ in $G$, written $w_{\phi}(xy)$, is the sum of the labels of end vertices $x$ and $y$, i.e., $w_{\phi}(xy)=\phi(x)+\phi(y)$. A vertex $k$-labeling is defined to be an edge irregular $k$-labeling of the graph $G$ if for every t

Hisaya Okahara, Kouji Tahata

This study introduces a novel model that effectively captures asymmetric structures in multivariate contingency tables with ordinal categories. Leveraging the principle of maximum entropy, our approach employs f-divergence to provide a rational model under the presence of a ``prior guess.'' Inspired by the constraints used in the derivation of multivariate n

Panas Kalayanamit

We study the existence and regularity of minimizers of the neo-Hookean energy in the closure of classes of deformations without cavitation. The exclusion of cavitation is imposed in the form of the divergence identities, which is equivalent to the well-known condition INV with $\text{Det} = \det$. We show that the neo-Hookean energy admits minimizers in clas

Guanlin Wu, Zhonghao Lyu, Juyong Zhang, Jie Xu

The efficient representation, transmission, and reconstruction of three-dimensional (3D) contents are becoming increasingly important for sixth-generation (6G) networks that aim to merge virtual and physical worlds for offering immersive communication experiences. Neural radiance field (NeRF) and 3D Gaussian splatting (3D-GS) have recently emerged as two pro

Martin Herdegen, Nazem Khan, Cosimo Munari

Risk and utility functionals are fundamental building blocks in economics and finance. In this paper we investigate under which conditions a risk or utility functional is sensitive to the accumulation of losses in the sense that any sufficiently large multiple of a position that exposes an agent to future losses has positive risk or negative utility. We call

Jan Bartsch, Simon Buchwald, Gabriele Ciaramella, Stefan Volkwein

Physical models often contain unknown functions and relations. The goal of our work is to answer the question of how one should excite or control a system under consideration in an appropriate way to be able to reconstruct an unknown nonlinear relation. To answer this question, we propose a greedy reconstruction algorithm within an offline-online strategy. W

Martin Farach-Colton, William Kuszmaul, Nathan Sheffield, Alek Westover

In the Memory Reallocation Problem a set of items of various sizes must be dynamically assigned to non-overlapping contiguous chunks of memory. It is guaranteed that the sum of the sizes of all items present at any time is at most a $(1-\varepsilon)$-fraction of the total size of memory (i.e., the load-factor is at most $1-\varepsilon$). The allocator receiv

Umme Salma, H. M. Nagesh, Narahari N

For a simple graph $G$, a vertex labeling $\phi:V(G) \rightarrow \{1, 2,\ldots,k\}$ is called $k$-labeling. The weight of an edge $uv$ in $G$, written $w_{\phi}(uv)$, is the sum of the labels of end vertices $u$ and $v$, i.e., $w_{\phi}(uv)=\phi(u)+\phi(v)$. A vertex $k$-labeling is defined to be an edge irregular $k$-labeling of the graph $G$ if for every t

Zahida Sultanova, Saleh Sultansoy

The upcoming phase of space exploration not only includes trips to Mars and beyond, but also holds great promise for human progress. However, the harm caused by cosmic radiation, consisting of Galactic Cosmic Rays and Solar Particle Events, is an important safety concern for astronauts and other living things that will accompany them. Research exploring the

Bipin Saha, Md. Johirul Islam, Shaikh Khaled Mostaque, Aditya Bhowmik

The success of autonomous navigation relies on robust and precise vehicle recognition, hindered by the scarcity of region-specific vehicle detection datasets, impeding the development of context-aware systems. To advance terrestrial object detection research, this paper proposes a native vehicle detection dataset for the most commonly appeared vehicle classe

Jason Kristiano, Jun'ichi Yokoyama

In order to produce appreciable amount of primordial black holes (PBHs), the square amplitude of curvature perturbation must take a large value of $\mathcal{O}(0.01)$, namely, seven digits larger than the value observed by cosmic microwave background radiation (CMB) on large scales. Such a large fluctuation can be achieved by violating the slow-roll (SR) con

François Hamel, Emmanuel Russ

We prove a Faber-Krahn inequality for the Laplacian with drift under Robin boundary condition, provided that the $\beta$ parameter in the Robin condition is large enough. The proof relies on a compactness argument, on the convergence of Robin eigenvalues to Dirichlet eigenvalues when $\beta$ goes to infinity, and on a strict Faber-Krahn inequality under Diri

Robert E. Wray, James R. Kirk, John E. Laird

Cognitive systems generally require a human to translate a problem definition into some specification that the cognitive system can use to attempt to solve the problem or perform the task. In this paper, we illustrate that large language models (LLMs) can be utilized to map a problem class, defined in natural language, into a semi-formal specification that c

Lucas Barreto-Mota, Elisabete M. de Gouveia Dal Pino, Siyao Xu, Alexandre Lazarian

Cosmic rays (CRs) interact with turbulent magnetic fields in the intestellar medium, generating nonthermal emission. After many decades of studies, the theoretical understanding of their diffusion in the ISM continues to pose a challenge. This study numerically explores a recent prediction termed "mirror diffusion" and its synergy with traditional diffusion

Jason Kristiano, Jun'ichi Yokoyama

In single-field inflation, violation of the slow-roll approximation can lead to growth of curvature perturbation outside the horizon. This violation is characterized by a period with a large negative value of the second slow-roll parameter. At an early time, inflation must satisfy the slow-roll approximation, so the large-scale curvature perturbation can exp

Maho Kajiura, Junya Nakamura

Network Intrusion Detection Systems (NIDSs) detect intrusion attacks in network traffic. In particular, machine-learning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A distributed processing framework for machine-learning-based NIDSs employing a scalable distributed stream processing system has been proposed

Yihan Wu, Tao Chang, Siliang Chen, Xiaodong Niu

Glioma cells can reshape functional neuronal networks by hijacking neuronal synapses, leading to partial or complete neurological dysfunction. These mechanisms have been previously explored for language functions. However, the impact of glioma on sensorimotor functions is still unknown. Therefore, we recruited a control group of patients with unaffected moto

Nicolò Masi

G(2) is the smallest exceptional group and it is the simplest and viable gauge group to minimally extend the strong interaction sector: G(2) includes the group SU(3) of Quantum Chromodynamics (QCD) as a maximal subgroup and it is equipped with six additional gluons that can acquire mass via a Higgs mechanism driven by a new Higgs particle and constitute dark

Yuzhou Hao, Yuting Zuo, Jiongzhi Zheng, Wenjie Hou

Efficient and precise calculations of thermal transport properties and figure of merit, alongside a deep comprehension of thermal transport mechanisms, are essential for the practical utilization of advanced thermoelectric materials. In this study, we explore the microscopic processes governing thermal transport in the distinguished crystalline material Tl$_

Arianna Favale, Adrià Gómez-Valent, Marina Migliaccio

Several studies in the literature have found a disagreement between data on Baryon Acoustic Oscillations (BAO) derived using two distinct methodologies: the two-dimensional (2D or angular) BAO, which extracts the BAO signal from the angular two-point correlation function; and the three-dimensional (3D) BAO, which also exploits the radial signal imprinted on

Seigo Nakazawa, Rina Tazai, Youichi Yamakawa, Seiichiro Onari

The exotic electronic states in the charge loop current (cLC) phase, in which the permanent charge current breaks the time-reversal symmetry, have been attracting increasing attention in recently discovered kagome metals AV3Sb5 (A = Cs, Rb, K). Interestingly, the cLC state is sensitively controlled by applying a small magnetic field as well as a tiny uniaxia

Connor Sponsler, Matheus Hostert, Ivan Martinez-Soler, Carlos A. Argüelles

Neutrinos produced in the atmosphere traverse a column density of air before being detected at neutrino observatories like IceCube or KM3NeT. In this work, we extend the neutrino flavor evolution in the {nuSQuIDS} code accounting for the varying height of neutrino production and the variable air density in the atmosphere. These effects can lead to sizeable s

Xuchen Li, Xiaokun Feng, Shiyu Hu, Meiqi Wu

Visual Language Tracking (VLT) enhances single object tracking (SOT) by integrating natural language descriptions from a video, for the precise tracking of a specified object. By leveraging high-level semantic information, VLT guides object tracking, alleviating the constraints associated with relying on a visual modality. Nevertheless, most VLT benchmarks a

Scott Zimmerman

This paper gives an alternate, elementary proof of a result of Magnani: maps between Carnot groups that preserve horizontal curves and are continuously differential in horizontal directions in the Euclidean sense are continuously Pansu differentiable. This proof contains primarily Euclidean arguments and also reproves a version of Magnani's mean value estima

Carl A. Moore, Jesús Pando

NASA's Science Mission Directorate (SMD) has initiated a program to enhance the participation of historically underrepresented institutions and communities in NASA's mission. Currently known as the NASA SMD Bridge Program, its goal is to establish enduring partnerships among these institutions, research-intensive universities, and NASA centers. There are con

Ayush Moharana, K. G. Hełminiak, F. Marcadon, T. Pawar

Eclipsing Compact Hierarchical Triples (ECHTs) are systems with the tertiary star orbiting an eclipsing binary (EB) in an orbit of fewer than 1000 days. In a CHT, all three stars exist in a space less than 5 AU in separation. A low-mass CHT is an interesting case to understand multiple star and planet formation at such small scales. In this study, we combine

A. Ritacco, L. Bizzarri, S. Savorgnano, F. Boulanger

The cosmic microwave background (CMB), a remnant of the Big Bang, provides unparalleled insights into the primordial universe, its energy content, and the origin of cosmic structures. The success of forthcoming terrestrial and space experiments hinges on meticulously calibrated data. Specifically, the ability to achieve an absolute calibration of the polariz

Lukas Bol, Li Chen, Yue Li

In this paper, the well-posedness of two-dimensional signal-dependent Keller-Segel system and its mean-field derivation from a interacting particle system on the whole space are investigated. The signal dependence effect is reflected by the fact that the diffusion coefficient in the particle system depends non-linearly on the interactions between the individ

Yushan Zeng, Bin Zhang, Kecheng Cao, Xiao-jing Liu

In pursuit of quantum advancements across disciplines, a bright and coherent electron source is expected to be a cornerstone of diverse applications including electron microscopy, laser accelerators, and free electron lasers. Current cathodes, such as cold field and photoemission, can generate high-quality electron beams with different cathode materials, geo

Edson OliveiraJr, Fernanda Madeiral, Alcemir Rodrigues Santos, Christina von Flach

Open Science aims to foster openness and collaboration in research, leading to more significant scientific and social impact. However, practicing Open Science comes with several challenges and is currently not properly rewarded. In this paper, we share our vision for addressing those challenges through a conceptual framework that connects essential building

Debajyoti Sengupta, Stephen Mulligan, David Shih, John Andrew Raine

We present SkyCURTAINs, a data driven and model agnostic method to search for stellar streams in the Milky Way galaxy using data from the Gaia telescope. SkyCURTAINs is a weakly supervised machine learning algorithm that builds a background enriched template in the signal region by leveraging the correlation of the source's characterising features with their

Ting Jiang, Shaohan Huang, Shengyue Luo, Zihan Zhang

Low-rank adaptation is a popular parameter-efficient fine-tuning method for large language models. In this paper, we analyze the impact of low-rank updating, as implemented in LoRA. Our findings suggest that the low-rank updating mechanism may limit the ability of LLMs to effectively learn and memorize new knowledge. Inspired by this observation, we propose

Francesco Dal Corso, Marco Amato, Davide Bigoni

A homogeneous elastic solid, bounded by a flat surface in its unstressed configuration, undergoes a finite strain when in frictionless contact against a rigid and rectilinear constraint, ending with a rounded or sharp corner, in a two-dimensional formulation. With a strong analogy to fracture mechanics, it is shown that (i.) a path-independent $J$--integral

Sofiane Bouarroudj, Quentin Ehret

We develop the process of symplectic double extensions for Lie superalgebras with degenerate center. The construction is a superization of a recent work by Fischer, and generalize our previous work. We provide a standard model for such double extensions, where the symplectic form is either orthosymplectic or periplectic. Additionally, we show that every doub

Sanjay Shukla, Marc E. Brachet, Rahul Pandit

We develop a theoretical framework that allows us to explore the coupled motion of neutron-superfluid vortices and proton-superconductor flux tubes in a gravitationally collapsed condensate, which describe neutron stars that form pulsars. Our framework uses the 3D Gross-Pitaevskii-Poisson-Equation (GPPE) for neutron Cooper pairs, the Real-Time-Ginzburg-Landa

Nida Nasir, Muneeb Ahmed, Neda Afreen, Mustafa Sameer

Deep learning, a cutting-edge machine learning approach, outperforms traditional machine learning in identifying intricate structures in complex high-dimensional data, particularly in the domain of healthcare. This study focuses on classifying Magnetic Resonance Imaging (MRI) data for Alzheimer's disease (AD) by leveraging deep learning techniques characteri

Takuzumi Nishio, Moju Zhao, Kei Okada, Masayuki Inaba

Manipulation performance improvement is crucial for aerial robots. For aerial manipulators, the baselink position and attitude errors directly affect the precision at the end effector. To address this stability problem, fixed-body approaches such as perching on the environment using the rotor suction force are useful. Additionally, conventional arm-equipped

Soon-young Oh, Yongsu Ahn

In schools, teachers play a multitude of roles, serving as educators, counselors, decision-makers, and members of the school community. With recent advances in artificial intelligence (AI), there is increasing discussion about how AI can assist, complement, and collaborate with teachers. To pave the way for better teacher-AI complementary relationships in sc

Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang

Neural combinatorial optimization (NCO) is a promising learning-based approach to solving various vehicle routing problems without much manual algorithm design. However, the current NCO methods mainly focus on the in-distribution performance, while the real-world problem instances usually come from different distributions. A costly fine-tuning approach or ge

Zejian Li, Anna Delmonte, Xhek Turkeshi, Rosario Fazio

Measurement-induced phases exhibit unconventional dynamics as emergent collective phenomena, yet their behavior in tailored interacting systems -- crucial for quantum technologies -- remains less understood. We develop a systematic toolbox to analyze monitored dynamics in long-range interacting systems, relevant to platforms like trapped ions and Rydberg ato

Andreas Defant, Daniel Galicer, Martín Mansilla, Mieczysław Mastyło

We investigate projection constants within classes of multivariate polynomials over finite-dimensional real Hilbert spaces. Specifically, we consider the projection constant for spaces of spherical harmonics and spaces of homogeneous polynomials as well as for spaces of polynomials of finite degree on the unit sphere. We establish a connection between these

Shemonto Das

Training machine learning models for classification tasks often requires labeling numerous samples, which is costly and time-consuming, especially in time series analysis. This research investigates Active Learning (AL) strategies to reduce the amount of labeled data needed for effective time series classification. Traditional AL techniques cannot control th

Esther Hänggi, Severin Winkler

One-sided output secure function evaluation is a cryptographic primitive where the two mutually distrustful players, Alice and Bob, both have a private input to a bivariate function. Bob obtains the value of the function for the given inputs, while Alice receives no output. It is known that this primitive cannot be securely implemented if the two players onl

Boyi Liu, Jingwen Tong, Yufan Zhuang

This paper presents EdgeLoc, an infrastructure-assisted, real-time localization system for autonomous driving that addresses the incompatibility between traditional localization methods and deep learning approaches. The system is built on top of the Robot Operating System (ROS) and combines the real-time performance of traditional methods with the high accur

Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang

Large language models (LLMs) are revolutionizing conversational recommender systems by adeptly indexing item content, understanding complex conversational contexts, and generating relevant item titles. However, controlling the distribution of recommended items remains a challenge. This leads to suboptimal performance due to the failure to capture rapidly cha

Georg Lehner

We give a generalization of Quillen's $S^{-1}S$ construction for arbitrary $E_n$-monoids as an $E_{n-1}$-monoidal $\infty$-category and show that its realization models the group completion provided that $n \geq 2$. We will also show how this construction is related to a variety of other constructions of the group completion.

Peter Donovan, Erling Jellum, Byeonggil Jun, Hokeun Kim

Discrete-event (DE) systems are concurrent programs where components communicate via tagged events, where tags are drawn from a totally ordered set. Reactors are an emerging model of computation based on DE and realized in the open-source coordination language Lingua Franca. Distributed DE (DDE) systems are DE systems where the components (reactors) communic