April 2024 arXiv papers — page 145

Joshua Harrington, Lenny Jones

A monic polynomial $f(x)\in {\mathbb Z}[x]$ of degree $N$ is called monogenic if $f(x)$ is irreducible over ${\mathbb Q}$ and $\{1,\theta,\theta^2,\ldots ,\theta^{N-1}\}$ is a basis for the ring of integers of ${\mathbb Q}(\theta)$, where $f(\theta)=0$. In this article, we use the classification of the Galois groups of quartic polynomials, due to Kappe and W

Topi Halme, Venugopal V. Veeravalli, Visa Koivunen

The problem of quickest change detection is studied in the context of detecting an arbitrary unknown mean-shift in multiple independent Gaussian data streams. The James-Stein estimator is used in constructing detection schemes that exhibit strong detection performance both asymptotically and non-asymptotically. Our results indicate that utilizing the James-S

Kateryna Zatsarynna, Andrea Nava, Alex Zazunov, Reinhold Egger

We provide a theoretical framework to describe the quantum many-body dynamics of Andreev states in Josephson junctions with spin-orbit coupling and a magnetic Zeeman field. In such cases, employing a doubled Nambu spinor description is technically advantageous but one then has to be careful to avoid double-counting problems. By deriving the Lindblad master e

Xin Li

What is intelligence? We argue for a structural-dynamical account rooted in a topological closure law: \emph{the boundary of a boundary vanishes} ($\partial^2=0$). This principle forces transient fragments to cancel while closed cycles persist as invariants, yielding the cascade $\partial^2\!=\!0 \Rightarrow \text{cycles (invariants)} \Rightarrow \text{memor

Kseniia Petukhova, Roman Kazakov, Ekaterina Kochmar

In this paper, we present our submission to the SemEval-2024 Task 8 "Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection", focusing on the detection of machine-generated texts (MGTs) in English. Specifically, our approach relies on combining embeddings from the RoBERTa-base with diversity features and uses a resampled tra

JuneYoung Park, Da Young Kim, Yunsoo Kim, Jisu Yoo

Cardiologists use electrocardiograms (ECG) for the detection of arrhythmias. However, continuous monitoring of ECG signals to detect cardiac abnormal-ities requires significant time and human resources. As a result, several deep learning studies have been conducted in advance for the automatic detection of arrhythmia. These models show relatively high perfor

Jintu Borah, Tanujit Chakraborty, Md. Shahrul Md. Nadzir, Mylene G. Cayetano

Accurate and reliable air quality forecasting is essential for protecting public health, sustainable development, pollution control, and enhanced urban planning. This letter presents a novel WaveCatBoost architecture designed to forecast the real-time concentrations of air pollutants by combining the maximal overlapping discrete wavelet transform (MODWT) wit

Sandi Klavžar, Jing Tian

Let $G \otimes _f H$ denote the Sierpi\'nski product of graphs $G$ and $H$ with respect to the function $f$. The Sierpi\'nski general position number ${\rm gp}{_{\rm S}}(G,H)$ is introduced as the cardinality of a largest general position set in $G \otimes _f H$ over all possible functions $f$. Similarly, the lower Sierpi\'nski general position number $\unde

Thien Udomsrirungruang, Nobuko Yoshida

Session types are a type discipline for describing and specifying communication behaviours of concurrent processes. Session subtyping, firstly introduced by Gay and Hole, is widely used for enlarging typability of session programs. This paper gives the complexity analysis of three algorithms for subtyping of synchronous binary session types. First, we analys

Simon Fowler, Philipp Haller, Roland Kuhn, Sam Lindley

Behavioural types provide a promising way to achieve lightweight, language-integrated verification for communication-centric software. However, a large barrier to the adoption of behavioural types is that the current state of the art expects software to be written using the same tools and typing discipline throughout a system, and has little support for comp

Samuel Cavoj, Ivan Nikitin, Colin Perkins, Ornela Dardha

Session types are a typing discipline used to formally describe communication-driven applications with the aim of fewer errors and easier debugging later into the life cycle of the software. Protocols at the transport layer such as TCP, UDP, and QUIC underpin most of the communication on the modern Internet and affect billions of end-users. The transport lay

Alejandro Ramírez-Arroyo, Troels B. Sørensen, Peter Beltoft, Henrik Christiansen

This letter presents a measurement campaign carried out in an FR2 urban outdoor environment in a live experimental network deployment. The radio propagation analysis from a physical perspective at 26 GHz is essential for the correct deployment and dimensioning of future communication networks. This study performs a walk test emulating realistic conditions un

Puya Mirkarimi, David C. Hoyle, Ross Williams, Nicholas Chancellor

The standard approach to encoding constraints in quantum optimization is the quadratic penalty method. Quadratic penalties introduce additional couplings and energy scales, which can be detrimental to the performance of a quantum optimizer. In quantum annealing experiments performed on a D-Wave Advantage, we explore an alternative penalty method that only in

Pedro Ângelo, Atsushi Igarashi, Vasco T. Vasconcelos

We explore the integration of metaprogramming in a call-by-value linear lambda-calculus and sketch its extension to a session type system. We build on a model of contextual modal type theory with multi-level contexts, where contextual values, closing arbitrary terms over a series of variables, may then be boxed and transmitted in messages. Once received, one

Samuel Lemieux, Sohail A. Jalil, David Purschke, Neda Boroumand

Attosecond spectroscopy comprises several techniques to probe matter through electrons and photons. One frontier of attosecond methods is to reveal complex phenomena arising from quantum-mechanical correlations in the matter system, in the photon fields and among them. Recent theories have laid the groundwork for understanding how quantum-optical properties

Cesar Damian, Robert Holladay, Adriana Saldana, Michael von Spakovsky

This work presents an analysis of the evolution of perturbed Bell diagonal states using the equation of motion of steepest-entropy-ascent quantum thermodynamics (SEAQT), the Lindblad equation, and various measures of loss of entanglement. First, a brief derivation is presented showing that Bell diagonal states are stationary states that are not stable equili

Basile Couëtoux, Bastien Gastaldi, Guyslain Naves

We introduce splitter networks, which abstract the behavior of conveyor belts found in the video game Factorio. Based on this definition, we show how to compute the steady-state of a splitter network. Then, leveraging insights from the players community, we provide multiple designs of splitter networks capable of load-balancing among several conveyor belts,

Yulong Qiao, Frank Grossmann

Multi-mode Glauber coherent states (MMGS) as well as Bloch states with zero quasi-momentum, which are a special case of generalized coherent states (GCS), are frequently used to describe condensed phases of bosonic many-body systems. The difference of two-point correlators of MMGS and GCS vanishes in the thermodynamic limit. Using the established expansion o

Myles Thiessen, Aleksey Panas, Guy Khazma, Eyal de Lara

Linearizable datastores are desirable because they provide users with the illusion that the datastore is run on a single machine that performs client operations one at a time. To reduce the performance cost of providing this illusion, many specialized algorithms for linearizable reads have been proposed which significantly improve read performance compared t

Oleg Asipchuk, Laura De Carli, Weilin Li

Fourier matrices naturally appear in many applications and their stability is closely tied to performance guarantees of algorithms. The starting point of this article is a result that characterizes properties of an exponential system on a union of cubes in $\mathbb{R}^d$ in terms of a general class of Fourier matrices and their extreme singular values. This

Hugo Caselles-Dupré, Charles Mellerio, Paul Hérent, Alizée Lopez-Persem

The reconstruction of images observed by subjects from fMRI data collected during visual stimuli has made strong progress in the past decade, thanks to the availability of extensive fMRI datasets and advancements in generative models for image generation. However, the application of visual reconstruction has remained limited. Reconstructing visual imaginatio

Puya Mirkarimi, Ishaan Shukla, David C. Hoyle, Ross Williams

Constrained combinatorial optimization problems, which are ubiquitous in industry, can be solved by quantum algorithms such as quantum annealing (QA) and the quantum approximate optimization algorithm (QAOA). In these quantum algorithms, constraints are typically implemented with quadratic penalty functions. This penalty method can introduce large energy sca

Ségolène Martin, Yunshi Huang, Fereshteh Shakeri, Jean-Christophe Pesquet

Transductive inference has been widely investigated in few-shot image classification, but completely overlooked in the recent, fast growing literature on adapting vision-langage models like CLIP. This paper addresses the transductive zero-shot and few-shot CLIP classification challenge, in which inference is performed jointly across a mini-batch of unlabeled

He Wang, Pengcheng Guo, Xucheng Wan, Huan Zhou

Automatic lip-reading (ALR) aims to automatically transcribe spoken content from a speaker's silent lip motion captured in video. Current mainstream lip-reading approaches only use a single visual encoder to model input videos of a single scale. In this paper, we propose to enhance lip-reading by incorporating multi-scale video data and multi-encoder. Specif

Lluis Castrejon, Thomas Mensink, Howard Zhou, Vittorio Ferrari

Combining Large Language Models (LLMs) with external specialized tools (LLMs+tools) is a recent paradigm to solve multimodal tasks such as Visual Question Answering (VQA). While this approach was demonstrated to work well when optimized and evaluated for each individual benchmark, in practice it is crucial for the next generation of real-world AI systems to

Shingo Akama, Mian Zhu

It has been shown that primordial tensor non-Gaussianities from a cubic Weyl action with a non-dynamical coupling are suppressed by the so-called slow-roll parameter in a conventional framework of slow-roll inflation. In this paper, we consider matter bounce cosmology in which the background spacetime is no longer quasi-de Sitter, and hence one might expect

Walther Neuper

The paper presents the second part of a precise description of the prototype that has been developed in the course of the ISAC project over the last two decades. This part describes the "specify-phase", while the first part describing the "solve-phase" is already published. In the specify-phase a student interactively constructs a formal specification. The I

Elisabeth Wagner, Federico Dell'Anna, Ramil Nigmatullin, Gavin K. Brennen

The density classification (DC) task, a computation which maps global density information to local density, is studied using one-dimensional non-unitary quantum cellular automata (QCAs). Two approaches are considered: one that preserves the number density and one that performs majority voting. For number preserving DC, two QCAs are introduced that reach the

Rishabh Sharma, David Rey, Laurent Longchambon, Aurélien Perrin

We report the observation of the melting of a vortex lattice in a fast rotating quasi-two dimensional Bose gas, under the influence of thermal fluctuations. We image the vortex lattice after a time-of-flight expansion, for increasing rotation frequency at constant atom number and temperature. We detect the vortex positions and study the order of the lattice

Qinxiang Cao, Xiwei Wu, Yalun Liang

Sets and relations are very useful concepts for defining denotational semantics. In the Coq proof assistant, curried functions to Prop are used to represent sets and relations, e.g. A -> Prop, A -> B -> Prop, A -> B -> C -> Prop, etc. Further, the membership relation can be encoded by function applications, e.g. X a represents a in X if X: A -> Prop. This is

Simon Tobias Lund, Jørgen Villadsen

We present a formalization of higher-order logic in the Isabelle proof assistant, building directly on the foundational framework Isabelle/Pure and developed to be as small and readable as possible. It should therefore serve as a good introduction for someone looking into learning about higher-order logic and proof assistants, without having to study the muc

Christophe Scholliers

Dependently typed programming languages have become increasingly relevant in recent years. They have been adopted in industrial strength programming languages and have been extremely successful as the basis for theorem provers. There are however, very few entry level introductions to the theory of language constructs for dependently typed languages, and even

Guillaume Carlier, Alessio Figalli, Filippo Santambrogio

In this paper, we extend the scope of Caffarelli's contraction theorem, which provides a measure of the Lipschitz constant for optimal transport maps between log-concave probability densities in $\R^d$. Our focus is on a broader category of densities, specifically those that are $\nicefrac{1}{d}$-concave and can be represented as $V^{-d}$, where $V$ is conve

Runze You, Shi Pu

This paper considers the distributed learning problem where a group of agents cooperatively minimizes the summation of their local cost functions based on peer-to-peer communication. Particularly, we propose a highly efficient algorithm, termed ``B-ary Tree Push-Pull'' (BTPP), that employs two B-ary spanning trees for distributing the information related to

Christopher J. Keylock, Maurizio Carbone

Understanding the dynamics of the turbulent velocity gradient tensor (VGT) is essential to gain insights into the Navier-Stokes equations and improve small-scale turbulence modeling. However, characterizing the VGT dynamics conditional on all its relevant invariants in a continuous fashion is extremely difficult. In this paper, we represent the VGT Lagrangia

Vassili Korotkine, Mitchell Cohen, James Richard Forbes

This paper proposes a novel Hessian approximation for Maximum a Posteriori estimation problems in robotics involving Gaussian mixture likelihoods. Previous approaches manipulate the Gaussian mixture likelihood into a form that allows the problem to be represented as a nonlinear least squares (NLS) problem. The resulting Hessian approximation used within NLS

K. V. Pozharska, A. S. Romanyuk

Exact-order estimates are obtained for some approximation characteristics of the classes of periodic multivariate functions with mixed smoothness (the Nikol'skii-Besov classes $B^{\boldsymbol{r}}_{p, \theta}$) in the space $B_{q,1}$, $1 \leq p, q \leq \infty$, which norm is stronger than the $L_q$-norm. It is shown, that in the multivariate case (in contrast

Wenyang Hui, Kewei Tu

Large language models (LLMs) have demonstrated impressive capability in reasoning and planning when integrated with tree-search-based prompting methods. However, since these methods ignore the previous search experiences, they often make the same mistakes in the search process. To address this issue, we introduce Reflection on search Trees (RoT), an LLM refl

Syuhei Iguro, Teppei Kitahara, Ryoutaro Watanabe

Recently, several new experimental results of the test of lepton flavor universality (LFU) in $B\to D^{(\ast)}$ semi-leptonic decays were announced: the first result of $R_{D}$ from the LHCb Run 1 data, the first results of $R_{D}$ and $R_{D^\ast}$ from the LHCb Run 2 data, and the first result of $R_{D^\ast}$ from the Belle II collaboration. Including these

Manuel Schnaus, Lilly Palackal, Benedikt Poggel, Xiomara Runge

Routing problems are a common optimization problem in industrial applications, which occur on a large scale in supply chain planning. Due to classical limitations for solving NP-hard problems, quantum computing hopes to improve upon speed or solution quality. Several suggestions have been made for encodings of routing problems to solve them with variational

Gregory Sech, Giulio Poggi, Marina Ljubenovic, Marco Fiorucci

Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectral data from airborne sensors in identifying archaeological features has, on the other side, generated increased interest in enhancing hyperspectral data to achieve higher spatial

Xuanfan Ni, Hengyi Cai, Xiaochi Wei, Shuaiqiang Wang

Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks but are constrained by their small context window sizes. Various efforts have been proposed to expand the context window to accommodate even up to 200K input tokens. Meanwhile, building high-quality benchmarks with much longer text lengths and more demanding tasks to p

Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee

Imaging is a standard example of an inverse problem, where the task of reconstructing a ground truth from a noisy measurement is ill-posed. Recent state-of-the-art approaches for imaging use deep learning, spearheaded by unrolled and end-to-end models and trained on various image datasets. However, many such methods require the availability of ground truth d

Michael Wagner, Carmen Carlan

A system safety case is a compelling, comprehensible, and valid argument about the satisfaction of the safety goals of a given system operating in a given environment supported by convincing evidence. Since the publication of UL 4600 in 2020, safety cases have become a best practice for measuring, managing, and communicating the safety of autonomous vehicles

Valentin Gilbert, Stéphane Louise

Quantum annealers (QA), such as D-Wave systems, become increasingly efficient and competitive at solving combinatorial optimization problems. However, solving problems that do not directly map the chip topology remains challenging for this type of quantum computer. The creation of logical qubits as sets of interconnected physical qubits overcomes limitations

Yutan Huang, Tanjila Kanij, Anuradha Madugalla, Shruti Mahajan

Developing user-centred applications that address diverse user needs requires rigorous user research. This is time, effort and cost-consuming. With the recent rise of generative AI techniques based on Large Language Models (LLMs), there is a possibility that these powerful tools can be used to develop adaptive interfaces. This paper presents a novel approach

Simon Vincent, Philippe Guittienne, Patrick Quigley, Cyrille Sepulchre

A birdcage resonant helicon antenna is designed, mounted and tested in the toroidal device TORPEX. The birdcage resonant antenna is an alternative to the usual Boswell or half-helical antenna designs commonly used for $\sim$ 10 cm diameter helicon sources in low temperature plasma devices. The main advantage of the birdcage antenna lies in its resonant natur

David Valensi, Esther Derman, Shie Mannor, Gal Dalal

The standard formulation of Markov decision processes (MDPs) assumes that the agent's decisions are executed immediately. However, in numerous realistic applications such as robotics or healthcare, actions are performed with a delay whose value can even be stochastic. In this work, we introduce stochastic delayed execution MDPs, a new formalism addressing ra

Meenakshi Sarkar, Debasish Ghose

Long-term video generation and prediction remain challenging tasks in computer vision, particularly in partially observable scenarios where cameras are mounted on moving platforms. The interaction between observed image frames and the motion of the recording agent introduces additional complexities. To address these issues, we introduce the Action-Conditione

Yuki K. Wakabayashi, Masaki Kobayashi, Yuichi Seki, Kohei Yamagami

The burgeoning fields of spintronics and topological electronics require materials possessing a unique combination of properties: ferromagnetism, metallicity, and chemical stability. SrRuO3 (SRO) stands out as a compelling candidate due to its exceptional combination of these attributes. However, understanding its behavior under tensile strain, especially it

Anthony Lomax

Most earthquake energy release arises during fault slip many kilometers below the Earth's surface. Understanding earthquakes and their hazard requires mapping the geometry and distribution of this slip. Such finite-fault maps are typically derived from surface phenomena, such as seismic and geodetic ground motions. Here we introduce an imaging procedure for

Vincent Lahoche, Dine Ousmane Samary

This paper aims to establish a connection between Pisarski's fixed point and a (2+3)-spin-glass model with sextic confinement potential. This is made possible by the unconventional power-counting induced by the effective kinetics provided by the disorder coupling in the large $N$-limit. Because of the absence of epsilon expansion, our approach is more attrac

Nilanjan Das, Soma Das, Jaydeb Sarkar

We present complete classifications of Toeplitz + Hankel operators on vector-valued Hardy spaces and classify paired operators on $L^2(\mathbb{T})$. We also study the latter class through the lens of inner functions on the disc.

J. Chen, B. P. Kay, C. R. Hoffman, T. L. Tang

The spin-orbit splitting between neutron 1$p$ orbitals at $^{33}$Si has been deduced using the single-neutron-adding ($d$,$p$) reaction in inverse kinematics with a beam of $^{32}$Si, a long-lived radioisotope. Reaction products were analyzed by the newly implemented SOLARIS spectrometer at the reaccelerated-beam facility at the National Superconducting Cycl

Vincent Cohen-Addad, David Rasmussen Lolck, Marcin Pilipczuk, Mikkel Thorup

Correlation Clustering is a classic clustering objective arising in numerous machine learning and data mining applications. Given a graph $G=(V,E)$, the goal is to partition the vertex set into clusters so as to minimize the number of edges between clusters plus the number of edges missing within clusters. The problem is APX-hard and the best known polynomia

Xin He, Xiangsong Cheng, Baihua Wu, Jian Liu

The constraint coordinate-momentum phase space (CPS) formulation of finite-state quantum systems has recently revealed that the triangle window function approach is an isomorphic representation of the exact population-population correlation function of the two-state system. We use the triangle window (TW) function and the CPS mapping kernel element to formul

Seoksu Lee, Hyeongchang Jeon, Eun-Sun Cho

Code obfuscation involves the addition of meaningless code or the complication of existing code in order to make a program difficult to reverse engineer. In recent years, MBA (Mixed Boolean Arithmetic) obfuscation has been applied to virus and malware code to impede expert analysis. Among the various obfuscation techniques, Mixed Boolean Arithmetic (MBA) obf

Marcos M. Flores, Alexander Kusenko

Recently, a number of novel scenarios for primordial black hole (PBH) formation have been discovered. Some of them require very minimal new physics, some others require no new ingredients besides those already present in commonly considered models, such as supersymmetry. At the same time, new strategies have emerged for detection of PBHs. For example, an obs

Emily Saltz, Zaria Jalan, Tin Acosta

Online commenting platforms have commonly developed systems to address online harms by removing and down-ranking content. An alternative, under-explored approach is to focus on up-ranking content to proactively prioritize prosocial commentary and set better conversational norms. We present a study with 460 English-speaking US-based news readers to understand

Nikola Ljubešić, Vít Suchomel, Peter Rupnik, Taja Kuzman

The world of language models is going through turbulent times, better and ever larger models are coming out at an unprecedented speed. However, we argue that, especially for the scientific community, encoder models of up to 1 billion parameters are still very much needed, their primary usage being in enriching large collections of data with metadata necessar

Yuntong Zhang, Haifeng Ruan, Zhiyu Fan, Abhik Roychoudhury

Researchers have made significant progress in automating the software development process in the past decades. Recent progress in Large Language Models (LLMs) has significantly impacted the development process, where developers can use LLM-based programming assistants to achieve automated coding. Nevertheless, software engineering involves the process of pro

Benedetta Liberatori, Alessandro Conti, Paolo Rota, Yiming Wang

Zero-Shot Temporal Action Localization (ZS-TAL) seeks to identify and locate actions in untrimmed videos unseen during training. Existing ZS-TAL methods involve fine-tuning a model on a large amount of annotated training data. While effective, training-based ZS-TAL approaches assume the availability of labeled data for supervised learning, which can be impra

Anqi Ren, Lin Liu, Yi Wang, Xiao Liu

Government development projects vary significantly from private sector initiatives in scope, stakeholder complexity, and regulatory requirements. There is a lack of empirical studies focusing on requirements engineering (RE) activities specifically for government projects. We addressed this gap by conducting a series of semi-structured interviews with 12 pro

Tobias Meggendorfer, Maximilian Weininger, Patrick Wienhöft

Markov decision processes (MDPs) are a fundamental model for decision making under uncertainty. They exhibit non-deterministic choice as well as probabilistic uncertainty. Traditionally, verification algorithms assume exact knowledge of the probabilities that govern the behaviour of an MDP. As this assumption is often unrealistic in practice, statistical mod

Roberto Cabieces, Thiago C. Junqueira, Katrina Harris, Jesus Relinque

surfQuake is a new software designed to streamline the estimation of seismic source parameters. Its comprehensive set of toolboxes automate the determination of seismic arrival times, event association and locations, moment magnitude from P- or S- wave displacement spectra and moment tensor inversions within a Bayesian framework. surfQuake is programmed in P

Liguo Zhou, Yirui Zhou, Huaming Liu, Alois Knoll

In the rapidly evolving field of autonomous driving systems, the refinement of path planning algorithms is paramount for navigating vehicles through dynamic environments, particularly in complex urban scenarios. Traditional path planning algorithms, which are heavily reliant on static rules and manually defined parameters, often fall short in such contexts,

V. R. Misko, L. Baraban, D. Makarov, T. Huang

Active systems -- including sperm cells, living organisms like bacteria, fish, birds, or active soft matter systems like synthetic ''microswimmers'' -- are characterized by motility, i.e., the ability to propel using their own ''engine''. Motility is the key feature that distinguishes active systems from passive or externally driven systems. In a large ensem

Gianni Pascoli

Our main goal is here to make a comparative analysis between the well-known MOND theory and a more recent model called$\kappa$-model. An additional connection, between the $\kappa$-model and twoother novel MOND-type theories: Newtonian Fractional-DimensionGravity (NFDG) and Refracted Gravity (RG), is likewise presented.All these models are built to overtake

Koshvendra Singh, Joe P. Ninan, Marina M. Romanova, David A. H. Buckley

EX Lupi, a low-mass young stellar object, went into an accretion-driven outburst in March of 2022. The outburst caused a sudden phase change of ~ 112$^{\circ}$ $\pm$ 5$^{\circ}$ in periodically oscillating multiband lightcurves. Our high resolution spectra obtained with HRS on SALT also revealed a consistent phase change in the periodically varying radial ve

José Rodríguez

Let $\nu$ be a countably additive vector measure defined on a $\sigma$-algebra and taking values in a Banach space. In this paper we deal with the following three properties for the Banach lattice $L_1(\nu)$ of all $\nu$-integrable real-valued functions: the Dunford-Pettis property, the positive Schur property and being lattice-isomorphic to an AL-space. We

Taotao Ji, Meng Hua, Chunguo Li, Yongming Huang

To reap the active and passive beamforming gain in an intelligent reflecting surface (IRS)-aided wireless network, a typical way is to first acquire the channel state information (CSI) relying on the pilot signal, and then perform the joint beamforming design. However, it is a great challenge when the receiver can neither send pilot signals nor have complex

Ajit Jain, Andruid Kerne, Nic Lupfer, Gabriel Britain

We investigate how to use AI-based analytics to support design education. The analytics at hand measure multiscale design, that is, students' use of space and scale to visually and conceptually organize their design work. With the goal of making the analytics intelligible to instructors, we developed a research artifact integrating a design analytics dashboa

Johanna Michor, Peter W. Michor

The Cartan development takes a Lie algebra valued 1-form satisfying the Maurer-Cartan equation on a simply connected manifold $M$ to a smooth mapping from $M$ into the Lie group. In this paper this is generalized to infinite dimensional $M$ for infinite dimensional regular Lie groups. The Cartan development is viewed as a generalization of the evolution map

Yiming Li, Xueqing Peng, Jianfu Li, Xu Zuo

In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPT) present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims

Maksym Ivashechkin, Oscar Mendez, Richard Bowden

3D hand pose estimation from images has seen considerable interest from the literature, with new methods improving overall 3D accuracy. One current challenge is to address hand-to-hand interaction where self-occlusions and finger articulation pose a significant problem to estimation. Little work has applied physical constraints that minimize the hand interse

Naira Azatyan

The main aim of this paper is to study both the Interstellar Medium (ISM) and the young stellar population in the three star-forming regions, namely IRAS 05137+3919, 05168+3634, and 19110+1045. The study of the ISM includes determination of the hydrogen column density (N(H_2)) and dust temperature (T_d) in the regions using Modified blackbody fitting. The ma

Shunda Yin, Liping Ye, Hailong He, Xueqin Huang

Bound states in the continuum (BICs) are spatially localized states with energy embedded in the continuum spectrum of extended states. The combination of BICs physics and nontrivial band topology theory giving rise to topological BICs, which are robust against disorders and meanwhile of the merit of conventional BICs, is attracting wide attention recently. H

Ava Spataru, Eric Hambro, Elena Voita, Nicola Cancedda

In this work, we explicitly show that modern LLMs tend to generate correct facts first, then "drift away" and generate incorrect facts later: this was occasionally observed but never properly measured. We develop a semantic drift score that measures the degree of separation between correct and incorrect facts in generated texts and confirm our hypothesis whe

Ruofan Chen, Chu Guo

The path integral formalism is the building block of many powerful numerical methods for quantum impurity problems. However, existing fermionic path integral based numerical calculations have only been performed in either the imaginary-time or the real-time axis, while the most generic scenario formulated on the L-shaped Kadanoff-Baym contour is left unexplo

Marc S. Seibel, Hristina Uzunova, Timo Kepp, Heinz Handels

For a unified analysis of medical images from different modalities, data harmonization using image-to-image (I2I) translation is desired. We study this problem employing an optical coherence tomography (OCT) data set of Spectralis-OCT and Home-OCT images. I2I translation is challenging because the images are unpaired, and a bijective mapping does not exist d

Nina Moutonnet, Steven White, Benjamin P Campbell, Saeid Sanei

Machine learning algorithms for seizure detection have shown considerable diagnostic potential, with recent reported accuracies reaching 100%. Yet, only few published algorithms have fully addressed the requirements for successful clinical translation. This is, for example, because the properties of training data may limit the generalisability of algorithms,

Ioannis Contopoulos, Ioannis Dimitropoulos, Dimitris Ntotsikas, Konstantinos N. Gourgouliatos

We present the first new type of solution of the pulsar equation since 1999. In it, the whole magnetosphere is confined inside the light cylinder and an electrically charged layer wraps around it and holds it together. The reason this new solution has never been obtained before is that all current time-dependent simulations are initialized with a vacuum dipo

José Rodríguez

Let $\nu$ be a vector measure defined on a $\sigma$-algebra $\Sigma$ and taking values in a Banach space. We prove that if $\nu$ is homogeneous and $L_1(\nu)$ is non-separable, then there is a vector measure $\tilde{\nu}:\Sigma \to c_0(\kappa)$ such that $L_1(\nu)=L_1(\tilde{\nu})$ with equal norms, where $\kappa$ is the density character of $L_1(\nu)$. This

Pardis Moradbeiki, Nasser Ghadiri

Smart cities need the involvement of their residents to enhance quality of life. Conversational query-answering is an emerging approach for user engagement. There is an increasing demand of an advanced conversational question-answering that goes beyond classic systems. Existing approaches have shown that LLMs offer promising capabilities for CQA, but may str

Zeyuan Allen-Zhu, Yuanzhi Li

Scaling laws describe the relationship between the size of language models and their capabilities. Unlike prior studies that evaluate a model's capability via loss or benchmarks, we estimate the number of knowledge bits a model stores. We focus on factual knowledge represented as tuples, such as (USA, capital, Washington D.C.) from a Wikipedia page. Through

Sannara Ek, Riccardo Presotto, Gabriele Civitarese, François Portet

Human Activity Recognition (HAR) based on the sensors of mobile/wearable devices aims to detect the physical activities performed by humans in their daily lives. Although supervised learning methods are the most effective in this task, their effectiveness is constrained to using a large amount of labeled data during training. While collecting raw unlabeled d

Meng Yuan, Ye Wang, Chris Manzie, Zhezhuang Xu

Biaxial motion control systems are used extensively in manufacturing and printing industries. To improve throughput and reduce machine cost, lightweight materials are being proposed in structural components but may result in higher flexibility in the machine links. This flexibility is often position dependent and compromises precision of the end effector of

Jiacheng Du, Jiahui Hu, Zhibo Wang, Peng Sun

Federated learning (FL) facilitates collaborative model training among multiple clients without raw data exposure. However, recent studies have shown that clients' private training data can be reconstructed from shared gradients in FL, a vulnerability known as gradient inversion attacks (GIAs). While GIAs have demonstrated effectiveness under \emph{ideal set

Kejun Liu, Nadiia Pastukhova, Egon Pavlica, Gvido Bratina

Water surfaces catalyze some organic reactions more effectively, making them unique for 2D organic material synthesis. This report introduces a new synthesis method via surfactant-monolayer-assisted interfacial synthesis on water surfaces for ring-opening polymerization of pyrrole, producing distinct polypyrrole derivatives with polyacetylene backbones and i

Daniel de Andres, Weiguang Cui, Gustavo Yepes, Marco De Petris

Galaxy clusters are composed of dark matter, gas and stars. Their dark matter component, which amounts to around 80\% of the total mass, cannot be directly observed but traced by the distribution of diffused gas and galaxy members. In this work, we aim to infer the cluster's projected total mass distribution from mock observational data, i.e. stars, Sunyaev-

Paul Röttger, Fabio Pernisi, Bertie Vidgen, Dirk Hovy

The last two years have seen a rapid growth in concerns around the safety of large language models (LLMs). Researchers and practitioners have met these concerns by creating an abundance of datasets for evaluating and improving LLM safety. However, much of this work has happened in parallel, and with very different goals in mind, ranging from the mitigation o

Steffen Peer Zeuschner, Jan-Etienne Pudell, Maximilian Mattern, Matthias Rössle

Hafnium Nitride (HfN) is a promising and very robust alternative to gold for applications of nanoscale metals. Details of the nanomorphology related to variations in strain states and optical properties can be crucial for applications in nanophotonics and plasmon-assisted chemistry. We use ultrafast reciprocal space mapping (URSM) with hard x-rays to unveil

Kenny De Commer

We provide a novel construction of quantized universal enveloping $*$-algebras of real semisimple Lie algebras, based on Letzter's theory of quantum symmetric pairs. We show that these structures can be `integrated', leading to a quantization of the group C$^*$-algebra of an arbitrary semisimple algebraic real Lie group.

Giulia Pisegna, Suropriya Saha, Ramin Golestanian

Phenomenological rules that govern the collective behaviour of complex physical systems are powerful tools because they can make concrete predictions about their universality class based on generic considerations, such as symmetries, conservation laws, and dimensionality. While in most cases such considerations are manifestly ingrained in the constituents, n

Miriam Schönauer, Andreas Schröder

In this paper, optimal convergence for an adaptive finite element algorithm for elastoplasticity is considered. To this end, the proposed adaptive algorithm is established within the abstract framework of the axioms of adaptivity [Comput. Math. Appl., 67(6) (2014), 1195-1253], which provides a specific proceeding to prove the optimal convergence of the schem

Kenta Noguchi, Katsuhiro Ota, Yusuke Suzuki

A graph drawn on the plane is called $1$-plane if each edge is crossed at most once by another edge. In this paper, we show that every $4$-connected $1$-plane graph has a connected spanning plane subgraph. We also show that there exist infinitely many $4$-connected $1$-plane graphs that have no $2$-connected spanning plane subgraphs. Moreover, we consider th

Khoi Do, Duong Nguyen, Nguyen H. Tran, Viet Dung Nguyen

Beyond class frequency, we recognize the impact of class-wise relationships among various class-specific predictions and the imbalance in label masks on long-tailed segmentation learning. To address these challenges, we propose an innovative Pixel-wise Adaptive Training (PAT) technique tailored for long-tailed segmentation. PAT has two key features: 1) class

Artur Xarles, Sergio Escalera, Thomas B. Moeslund, Albert Clapés

In this paper, we introduce T-DEED, a Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in sports videos. T-DEED addresses multiple challenges in the task, including the need for discriminability among frame representations, high output temporal resolution to maintain prediction precision, and the necessity to capture information

Gianni Valerio Vinci, Maurizio Mattia

Local networks of neurons are nonlinear systems driven by synaptic currents elicited by its own spiking activity and the input received from other brain areas. Synaptic currents are well approximated by correlated Gaussian noise. Besides, the population dynamics of neuronal networks is often found to be multistable, allowing the noise source to induce state

Alexandre Sac-Morane, Hadrien Rattez, Manolis Veveakis

Rock weathering is a common phenomenon in most engineering applications, such as underground storage or geothermal energy. This work offers a discrete element modelization of the problem considering cohesive granular material and debonding effect. Oedometer conditions are applied during the weathering and the evolution of the coefficient of lateral earth pre