March 2024 arXiv papers — page 45

Hyunki Seong, David Hyunchul Shim

This paper focuses on the acquisition of mapless navigation skills within unknown environments. We introduce the Skill Q-Network (SQN), a novel reinforcement learning method featuring an adaptive skill ensemble mechanism. Unlike existing methods, our model concurrently learns a high-level skill decision process alongside multiple low-level navigation skills,

Tanmay Biswas, Gerhard Kahl, Gaurav P. Shrivastav

Phase separation plays an role in determining the self-assembly of biological and soft-matter systems. In biological systems, liquid-liquid phase separation inside a cell leads to the formation of various macromolecular aggregates. The interaction among these aggregates is soft, i.e., these can significantly overlap at a small energy cost. From the computer

Yirong Zeng, Xiao Ding, Yi Zhao, Xiangyu Li

Fact-checking is the task of verifying the factuality of a given claim by examining the available evidence. High-quality evidence plays a vital role in enhancing fact-checking systems and facilitating the generation of explanations that are understandable to humans. However, the provision of both sufficient and relevant evidence for explainable fact-checking

Igor V. Netay

We introduce data structures and algorithms to count numerical inaccuracies arising from usage of floating numbers described in IEEE 754. Here we describe how to estimate precision for some collection of functions most commonly used for array manipulations and training of neural networks. For highly optimized functions like matrix multiplication, we provide

Anna Herring, Ruotong Huang, Adrian Sheppard

Diffusive transport has implications for the long-term status of underground storage of hydrogen (H$_2$) fuel and carbon dioxide (CO$_2$), technologies which are being pursued to mitigate climate change and advance the energy transition. Once injected underground, CO$_2$ and H$_2$ will exist in multiphase fluid-water-rock systems: being partially-soluble, in

Sayantani Bhattacharyya, Parthajit Biswas, Nilay Kundu

Focussing on theories for which the higher derivative terms are considered as small corrections in the Lagrangian to Einstein's two-derivative theory of general relativity (GR), we prove the classical version of the covariant entropy bound (also known as the Bousso bound) in arbitrary diffeomorphism invariant gravitational theories. Even if the higher deriva

P. Zasche, Z. Henzl, M. Wolf

We present the discovery of six new triple stellar system candidates composed of an inner eccentric-orbit eclipsing binary with an apsidal motion. These stars were studied using new, precise TESS light curves and a long-term collection of older photometric ground-based data. These data were used for the monitoring of ETVs (eclipse timing variations) and to d

Qianru Zhang, Lianghao Xia, Xuheng Cai, Siuming Yiu

Graph augmentation with contrastive learning has gained significant attention in the field of recommendation systems due to its ability to learn expressive user representations, even when labeled data is limited. However, directly applying existing GCL models to real-world recommendation environments poses challenges. There are two primary issues to address.

Rohit Raju, Peeta Basa Pati, SA Gandheesh, Gayatri Sanjana Sannala

Text continues to remain a relevant form of representation for information. Text documents are created either in digital native platforms or through the conversion of other media files such as images and speech. While the digital native text is invariably obtained through physical or virtual keyboards, technologies such as OCR and speech recognition are util

Yan Li, Liping Zhang

The previous support vector machine(SVM) including $0/1$ loss SVM, hinge loss SVM, ramp loss SVM, truncated pinball loss SVM, and others, overlooked the degree of penalty for the correctly classified samples within the margin. This oversight affects the generalization ability of the SVM classifier to some extent. To address this limitation, from the perspect

Piotr Lebiedowicz, Antoni Szczurek, Otto Nachtmann

We discuss the diffractive bremsstrahlung of a single photon in the $pp \to pp \gamma$ reaction at LHC energies and at forward photon rapidities. We compare the results for our standard approach, based on QFT and the tensor-Pomeron model, with two versions of soft-photon approximations, SPA1 and SPA2, where the radiative amplitudes contain only the leading t

Pepe Eulzer, Kevin Richter, Anna Hundertmark, Ralf Wickenhöfer

The emergence of computational fluid dynamics (CFD) enabled the simulation of intricate transport processes, including flow in physiological structures, such as blood vessels. While these so-called hemodynamic simulations offer groundbreaking opportunities to solve problems at the clinical forefront, a successful translation of CFD to clinical decision-makin

Osama Ahmad, Zawar Hussain, Hammad Naeem

This study is about the implementation of a reinforcement learning algorithm in the trajectory planning of manipulators. We have a 7-DOF robotic arm to pick and place the randomly placed block at a random target point in an unknown environment. The obstacle is randomly moving which creates a hurdle in picking the object. The objective of the robot is to avoi

Henry W J Reeve

The Dvoretzky--Kiefer--Wolfowitz--Massart inequality gives a sub-Gaussian tail bound on the supremum norm distance between the empirical distribution function of a random sample and its population counterpart. We provide a short proof of a result that improves the existing bound in two respects. First, our one-sided bound holds without any restrictions on th

Alison M. W. Mitchell, Giovanni Morlino, Silvia Celli, Stefano Menchiari

Young and massive stellar clusters are a potential source of galactic cosmic rays due to at least two acceleration mechanisms. Collective stellar winds from massive stars form a wind-blown bubble with a termination shock at which particle acceleration to PeV energies may be achieved. Furthermore, shock acceleration may occur at supernova remnants (SNRs) expa

Feiteng Fang, Liang Zhu, Min Yang, Xi Feng

Reinforcement learning from human feedback (RLHF) is a crucial technique in aligning large language models (LLMs) with human preferences, ensuring these LLMs behave in beneficial and comprehensible ways to users. However, a longstanding challenge in human alignment techniques based on reinforcement learning lies in their inherent complexity and difficulty in

Younghun Hong, Changhun Yang

The Korteweg-de Vries (KdV) equation is known as a universal equation describing various long waves in dispersive systems. In this article, we prove that in a certain scaling regime, a large class of rough solutions to the Boussinesq equation are approximated by the sums of two counter-propagating waves solving the KdV equations. It extends the earlier resul

Nandita Padhan, Ashutosh Dwibedi, Arghya Chatterjee, Sabyasachi Ghosh

We have investigated the influence of the Coriolis force on the electrical conductivity of hadronic matter formed in relativistic nuclear collisions, employing the Hadron Resonance Gas (HRG) model. A rotating matter in the peripheral heavy ion collisions can be expected from the initial stage of quark matter to late-stage hadronic matter. Present work is foc

Yuhang Ding, Liulei Li, Wenguan Wang, Yi Yang

Prominent solutions for medical image segmentation are typically tailored for automatic or interactive setups, posing challenges in facilitating progress achieved in one task to another.$_{\!}$ This$_{\!}$ also$_{\!}$ necessitates$_{\!}$ separate$_{\!}$ models for each task, duplicating both training time and parameters.$_{\!}$ To$_{\!}$ address$_{\!}$ above

Fan Li, Shanshan Feng, Yuqi Yan, Ching-Hung Lee

Advancements in technology, pilot shortages, and cost pressures are driving a trend towards single-pilot and even remote operations in aviation. Considering the extensive workload and huge risks associated with single-pilot operations, the development of a Virtual Co-Pilot (V-CoP) is expected to be a potential way to ensure aviation safety. This study propos

Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler

We present SIM-FSVGD for learning robot dynamics from data. As opposed to traditional methods, SIM-FSVGD leverages low-fidelity physical priors, e.g., in the form of simulators, to regularize the training of neural network models. While learning accurate dynamics already in the low data regime, SIM-FSVGD scales and excels also when more data is available. We

Qingping Zheng, Ling Zheng, Yuanfan Guo, Ying Li

Artifact-free super-resolution (SR) aims to translate low-resolution images into their high-resolution counterparts with a strict integrity of the original content, eliminating any distortions or synthetic details. While traditional diffusion-based SR techniques have demonstrated remarkable abilities to enhance image detail, they are prone to artifact introd

Ning-An Lai, Yi Zhou

Whether the 3D incompressible Navier-Stokes equations will have a global smooth solution for all smooth, finite energy initial data is a Millennium Prize problem. One of the main difficulties of this problem is that the Navier-Stokes equations are actually a system of semilinear heat equations rather than a single equation. In this paper, we discover a remar

Kyeongsu Choi, Jiuzhou Huang

We classify the smooth self-similar solutions of the semilinear heat equation $u_t=\Delta u+|u|^{p-1}u$ in $\mathbb{R}^n\times (0,T)$ satisfying an integral condition for all $p>1$ with positive speed. As a corollary, we prove that finite time blowing up solutions of this equation on a bounded convex domain with $u(\cdot,0)\geq 0$ and $u_t(\cdot,0)\geq 0$ co

Francesco Di Feola, Lorenzo Tronchin, Valerio Guarrasi, Paolo Soda

Generative Adversarial Networks (GANs) have proved as a powerful framework for denoising applications in medical imaging. However, GAN-based denoising algorithms still suffer from limitations in capturing complex relationships within the images. In this regard, the loss function plays a crucial role in guiding the image generation process, encompassing how m

Dietmar Winkler, Pirmin Urbanke, Rudolf Ramler

The readability of source code is key for understanding and maintaining software systems and tests. Several studies investigate the readability of source code, but there is limited research on the readability of test code and related influence factors. We investigate the factors that influence the readability of test code from an academic perspective complem

Jianfa Bai, Man Lin, Gang Cao

The advancement of generation models has led to the emergence of highly realistic artificial intelligence (AI)-generated videos. Malicious users can easily create non-existent videos to spread false information. This letter proposes an effective AI-generated video detection (AIGVDet) scheme by capturing the forensic traces with a two-branch spatio-temporal c

M. Praveen, Raghavendra Ramesh, Isaac Doidge

Decentralized Finance (DeFi) has emerged as a contemporary competitive as well as complementary to traditional centralized finance systems. As of 23rd January 2024, per Defillama approximately USD 55 billion is the total value locked on the DeFi applications on all blockchains put together. A Byzantine Fault Tolerant (BFT) State Machine Replication (SMR) pro

Juan Gerardo Alcázar, Hüsnü Anıl Çoban, Uğur Gözütok

Two curves are affinely equivalent if there exists an affine mapping transforming one of them onto the other. Thus, detecting affine equivalence comprises, as important particular cases, similarity, congruence and symmetry detection. In this paper we generalize previous results by the authors to provide an algorithm for computing the affine equivalences betw

Si Liu, Zihan Ding, Jiahui Fu, Hongyu Li

The objective of the collaborative vehicle-to-everything perception task is to enhance the individual vehicle's perception capability through message communication among neighboring traffic agents. Previous methods focus on achieving optimal performance within bandwidth limitations and typically adopt BEV maps as the basic collaborative message units. Howeve

Manel Velasco, Isiah Zaplana, Arnau Dória-Cerezo, Pau Martí

Geometric algebra (GA) is a mathematical tool for geometric computing, providing a framework that allows a unified and compact approach to geometric relations which in other mathematical systems are typically described using different more complicated elements. This fact has led to an increasing adoption of GA in applied mathematics and engineering problems.

Shin'ichiro Ando, Shunichi Horigome, Ethan O. Nadler, Daneng Yang

We combine the semi-analytical structure formation model, SASHIMI, which predicts subhalo populations in collisionless, cold dark matter (CDM), with a parametric model that maps CDM halos to self-interacting dark matter (SIDM) halos. The resulting model, SASHIMI-SIDM, generates SIDM subhalo populations down to sub-galactic mass scales, for an arbitrary input

Andrea Titton

This paper investigates the endogenous formation of supply chains and its consequences for disruption propagation. In production networks where upstream risk is highly correlated and supplier relationships are not observable, the marginal risk reduction of adding an additional supplier is low, because this additional supplier's risk is likely to be correlate

Andrea Auconi

An integral relation is derived from the Fokker-Planck equation which connects the steady-state probability currents with the dynamics of relaxation on short timescales in the limit of small perturbation fields. As a consequence of this integral relation, a lower bound on the steady-state entropy production is obtained. For the particular case of an ensemble

Grazia Sveva Ascione, Valerio Sterzi

This paper makes two contributions to the field of text-based patent similarity. First, it compares the performance of different kinds of patent-specific pretrained embedding models, namely static word embeddings (such as word2vec and doc2vec models) and contextual word embeddings (such as transformers based models), on the task of patent similarity calculat

Vladyslav Romankov, Moritz Bernhardt, Martin Heinrich, Diana Vaclavkova

The molecular self-assembly and the magnetic properties of two cyclooctatetraenide (COT) - based single-ion magnets (SIM) adsorbed on Ag(100) in the sub-monolayer range are reported. Our study combines scanning-tunneling microscopy, X-ray photoemission spectroscopy and polarized X-ray absorption spectroscopy to show that Cp*ErCOT (Cp* = 1,2,3,4,5-pentamethyl

A. Philip Dawid, Francesco Dotto, Maxine Graves, Jay B. Kadane

We compare three graphical methods for displaying evidence in a legal case: Wigmore Charts, Bayesian Networks and Chain Event Graphs. We find that these methods are aimed at three distinct audiences, respectively lawyers, forensic scientists and the police. The methods are illustrated using part of the evidence in the case of the murder of Meredith Kercher.

Yuda Song, Zehao Sun, Xuanwu Yin

Recent advancements in diffusion models have positioned them at the forefront of image generation. Despite their superior performance, diffusion models are not without drawbacks; they are characterized by complex architectures and substantial computational demands, resulting in significant latency due to their iterative sampling process. To mitigate these li

Amazigh Amrane, Hugo Bazille, Emily Clement, Uli Fahrenberg

Interval-order partially ordered multisets with interfaces (ipomsets) have shown to be a versatile model for executions of concurrent systems in which both precedence and concurrency need to be taken into account. In this paper, we develop a presentation of ipomsets as generated by a graph of certain discrete ipomsets (starters and terminators) under the rel

Simon Schirren

We present a new method for constructing virtual cycles for rank-2 Higgs sheaves $(E,\phi)$ on a smooth projective surface $S$. Using this, we redefine the $\mathbf{SU}(2)$-perfect obstruction theory previously constructed by Tanaka-Thomas. The key step in our construction involves modifying the $\mathbf{C}^\times$-localisation formula of Graber-Pandharipand

Jaime Sancho, Manuel Villa, Miguel Chavarrías, Eduardo Juarez

Over the last two decades, augmented reality (AR) has led to the rapid development of new interfaces in various fields of social and technological application domains. One such domain is medicine, and to a higher extent surgery, where these visualization techniques help to improve the effectiveness of preoperative and intraoperative procedures. Following thi

Weimin Zhang

To our knowledge, this paper is the first attempt to consider the existence issue for fractional $p$-Laplacian equation: $(-\Delta)_p^s u= \lambda f(u),\; u> 0 ~\text{in}~\Omega;\; u=0\;\text{in}~ \mathbb{R}^N\setminus\Omega$, where $p>1$, $s\in (0,1)$, $\lambda>0$ and $\Omega$ is a bounded domain with $C^{1, 1}$ boundary. We first propose a notion of stable

Wei Liu, Lei Wang, Yu Zhang

A light pseudoscalar $A$ in the sufficient large $\tan\beta$ region of type-I two-Higgs-doublet model (2HDM) can be naturally a long-lived particle (LLP). We focus on $H^{\pm}A$, $HA$ and $AA$ pair productions via the electroweak processes mediated by the bosons at the LHC, including $pp \rightarrow W^\pm/Z \rightarrow H^{\pm}/H A$ and $pp \rightarrow h \rig

Leoni Winschermann, Marco E. T. Gerards, Johann Hurink

In parking lots with large groups of electric vehicles (EVs), charging has to happen in a coordinated manner, among others, due to the high load per vehicle and the limited capacity of the electricity grid. To achieve such coordination, model predictive control can be applied, thereby repeatedly solving an optimization problem. Due to its repetitive nature a

N. M. Rosário, O. D. S. Demangeon, S. C. C. Barros, D. Gandolfi

We aim to constrain the internal structure and composition of HD 15337 b and c, two short-period planets situated on opposite sides of the radius valley, using new transit photometry and radial velocity data. We acquire 6 new transit visits with the CHaracterising ExOPlanet Satellite (CHEOPS) and 32 new radial velocity measurements from the High Accuracy Rad

S. Takatori, M. Hasegawa, M. Hazumi, D. Kaneko

The Simons Array (SA) project is a ground-based Cosmic Microwave Background (CMB) polarization experiment. The SA observes the sky using three telescopes, and POLARBEAR-2A (PB-2A) is the receiver system on the first telescope. For the ground-based experiment, atmospheric fluctuation is the primary noise source that could cause polarization leakage. In the PB

Mahdi Nobar, Jürg Keller, Alisa Rupenyan, Mohammad Khosravi

This article presents the guided Bayesian optimization algorithm as an efficient data-driven method for iteratively tuning closed-loop controller parameters using an event-triggered digital twin of the system based on available closed-loop data. We define a controller tuning framework independent of the controller or the plant structure. Our proposed methodo

Mohammad Ali Abbassi, Lukas Novotny

We investigate the radiation damping experienced by a dielectric spherical particle when it is illuminated by an electromagnetic plane wave within the Rayleigh regime. We derive the equivalent electric dipole of the moving particle and subsequently calculate the electromagnetic force acting on it from two different approaches. In the first approach, we calcu

Grite L. Abma, Michael A. Parkes, Daniel A. Horke

Tautomers are ubiquitous throughout chemistry, and typically considered inseparable in solution. Yet (bio)chemical activity is highly tautomer specific, with common examples being the amino and nucleic acids. While tautomers exist in an equilibrium in solution, in the cold environment of a molecular beam the barrier to tautomerization is typically much too h

Halil Mutuk

We study systematically magnetic moments of hiddden-bottom pentaquark states with quantum numbers $J^P=\frac{1}{2}^{\pm}$, $J^P=\frac{3}{2}^{\pm}$, and $J^P=\frac{5}{2}^{\pm}$ with molecular, diquark-diquark-antiquark, and diquark-triquark models. The numerical results show that magnetic moments are different within the same model according to same quantum n

A. A. Molavi Choobini, F. M. Aghamir, S. S. Ghaffari-Oskooei

Pulse shaping provides a significant level of control and precision when optimizing laser-plasma interactions. Pulse shaping enables precise control and manipulation, resulting in enhanced energy deposition, optimized particle acceleration, controlled polarization, and exploitation of resonant effects. The present study investigates the interaction of struct

Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera

Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions. Pre-trained language models have advanced performance in crisis informatics, but their contextual embeddings lack semantic meaningfulness. Although the CrisisTransformers family in

Binh Vinh Duc Nguyen, Andrew Vande Moere

This technical description details the design and engineering process of a semi-autonomous robotic partition. This robotic partition prototype was subsequently employed in a longer-term evaluation in-the-wild study conducted by the authors in a real-world office setting.

Busra Asan, Abdullah Akgül, Alper Unal, Melih Kandemir

Seasonal forecasting is a crucial task when it comes to detecting the extreme heat and colds that occur due to climate change. Confidence in the predictions should be reliable since a small increase in the temperatures in a year has a big impact on the world. Calibration of the neural networks provides a way to ensure our confidence in the predictions. Howev

Reinaldo Francener, Victor P. Goncalves, Diego R. Gratieri

The flux of atmospheric and astrophysical neutrinos measured in UHE neutrino detectors is strongly dependent on the description of the propagation and absorption of the neutrinos during the passage through Earth to the detector. In particular, the attenuation of the incident neutrino flux depends on the details of the matter structure between the source and

Kota Dohi, Yohei Kawaguchi

To develop a machine sound monitoring system, a method for detecting anomalous sound is proposed. In this paper, we explore a method for multiple clients to collaboratively learn an anomalous sound detection model while keeping their raw data private from each other. In the context of industrial machine anomalous sound detection, each client possesses data f

Biswesh Mohapatra, Seemab Hassan, Laurent Romary, Justine Cassell

Successful conversations often rest on common understanding, where all parties are on the same page about the information being shared. This process, known as conversational grounding, is crucial for building trustworthy dialog systems that can accurately keep track of and recall the shared information. The proficiencies of an agent in grounding the conveyed

James S. Cummins, Natalia G. Berloff

We introduce the Vector Ising Spin Annealer (VISA), a framework in gain-based computing that harnesses light-matter interactions to solve complex optimization problems encoded in spin Hamiltonians. Traditional driven-dissipative systems often select excited states due to limitations in spin movement. VISA transcends these constraints by enabling spins to ope

Chen Li, Ruijie Ma, Xiang Qian, Xiaohao Wang

Addressing the challenge of data scarcity in industrial domains, transfer learning emerges as a pivotal paradigm. This work introduces Style Filter, a tailored methodology for industrial contexts. By selectively filtering source domain data before knowledge transfer, Style Filter reduces the quantity of data while maintaining or even enhancing the performanc

Francisco J. Rodríguez-Lera, Miguel A. González-Santamarta, Alejandro González-Cantón, Laura Fernández-Becerra

In an era where autonomous robots increasingly inhabit public spaces, the imperative for transparency and interpretability in their decision-making processes becomes paramount. This paper presents the overview of a Robotic eXplanation and Interpretability Engine (ROXIE), which addresses this critical need, aiming to demystify the opaque nature of complex rob

Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé

In recent years, semantic segmentation has become a pivotal tool in processing and interpreting satellite imagery. Yet, a prevalent limitation of supervised learning techniques remains the need for extensive manual annotations by experts. In this work, we explore the potential of generative image diffusion to address the scarcity of annotated data in earth o

C. J. Guzman-Valencia, J. Toriz-Salinas, H. Espinosa-Jimenez, A. B. Salazar-Arriaga

The surface tension of monolayers with mixtures of anionic and nonionic surfactant at the liquid/vapour interface is studied. Previous works have observed that calculations of the surface tension of simple fluids show artificial oscillations for small interfacial areas, indicating that the surface tension data fluctuate due to the finite size effects and per

Georges Gras

Let $k = \mathbb{Q}(\sqrt {-m})$ and $p \geq 3$ split in $k$. We prove new properties of the $\mathbb{Z}_p$-extensions $K/k$, distinct from the cyclotomic one; we do not assume $K/k$ totally ramified, nor the triviality of the $p$-class group of $k$. These properties are governed by the $p$-valuation $\delta_p(k)$ of a Fermat quotient of the fundamental $p$-

Annalisa Baldi, Bruno Franchi, Pierre Pansu

It is shown that higher degree exact differential forms on compact Riemannian $n$-manifolds possess continuous primitives whose uniform norm is controlled by their $L^n$ norm. A contact sub-Riemannian analogue is proven, with differential forms replaced with Rumin differential forms.

Lili Du, Yang Pu, Jing Yang

This article is devoted to investigate the singular profile of the free boundary of two-dimensional incompressible inviscid fluid with external force near the stagnation point. More precisely, given an external force with some polynomial type decay close to the stagnation point, the singular profile of the free boundary at stagnation point possible are corne

Binh Vinh Duc Nguyen, Andrew Vande Moere

This positional paper outlines our vision of 'adaptive architecture', which involves the integration of robotic technology to physically change an architectural space in supporting the changing needs of its occupants, in response to the CHI'24 workshop "HabiTech - Inhabiting Buildings, Data & Technology" call on "How do new technologies enable and empower th

S. M. Tschopp, J. M. Brader

The superadiabatic dynamical density functional theory (superadiabatic-DDFT) is a promising new method for the study of colloidal systems out-of-equilibrium. Within this approach the viscous forces arising from interparticle interactions are accounted for in a natural way by treating explicitly the dynamics of the two-body correlations. For bulk systems subj

K. Haydukivska, V. Blavatska

We analyze the universal conformational properties of complex copolymer macromolecules, based on two topologies: the rosette structure containing $f_c$ linear branches and $f_r$ closed loops grafted to the central core, and the symmetric pom-pom structure, consisting of a backbone linear chain terminated by two branching points with functionalities $f$. We a

Yujie Wang, Yan Duan, Yuwen Chen, Man Zhang

Effective regulation of the morphology of transition metal spinel structures is crucial for creating efficient and stable bifunctional catalysts for electrocatalysis of water. In this work, micro-flower NiCo2O4 (F-NCO) assembled by nanosheets via a chemical template method for the simultaneous promotion of hydrogen evolution reaction (HER) and oxygen evoluti

Giorgia Bellomonte, Stefan Ivkovic, Camillo Trapani

The GNS construction for positive invariant sesquilinear forms on quasi *-algebras is generalized to a class of positive C*-valued sesquilinear maps on quasi *-algebras. The result is a *-representation taking values in a space of operators acting on a certain quasi-normed C-module.

L. Contessi, M. Pavon Valderrama, U. van Kolck

We consider a possible resummation of subleading effects in two-body systems with a large scattering length as described by a short-range effective field theory (EFT). In particular, we investigate the consequences of a resummation of part of the range corrections. Explicit calculations of the two-body phase shifts and charge form factor indicate that, excep

Andrew Vande Moere, Sara Arko, Alena Safrova Drasilova, Tomáš Ondráček

As the academic consortia members of the EU Horizon project SONATA ("Situation-aware OrchestratioN of AdapTive Architecture"), we respond to the workshop call for "Office Wellbeing by Design: Don't Stand for Anything Less" by proposing the "Adaptive Workplace" concept. In essence, our vision aims to adapt a workplace to the ever-changing needs of individual

Jinsol Seo

We introduce a general $L_p$-solvability result for the Poisson equation in non-smooth domains $\Omega\subset \mathbb{R}^d$, with the zero Dirichlet boundary condition. Our sole assumption on the domain $\Omega$ is the Hardy inequality: There exists a constant $N>0$ such that $$ \int_{\Omega}\Big|\frac{f(x)}{d(x,\partial\Omega)}\Big|^2\,\mathrm{d} x\leq N\in

Kudaibergen Abutalip, Numan Saeed, Ikboljon Sobirov, Vincent Andrearczyk

Deploying deep learning (DL) models in medical applications relies on predictive performance and other critical factors, such as conveying trustworthy predictive uncertainty. Uncertainty estimation (UE) methods provide potential solutions for evaluating prediction reliability and improving the model confidence calibration. Despite increasing interest in UE,

Thao Dang, Alexandre Donzé, Inzemamul Haque, Nikolaos Kekatos

We present a novel method for imitation learning for control requirements expressed using Signal Temporal Logic (STL). More concretely we focus on the problem of training a neural network to imitate a complex controller. The learning process is guided by efficient data aggregation based on counter-examples and a coverage measure. Moreover, we introduce a met

Ashok Urlana, Aditya Saibewar, Bala Mallikarjunarao Garlapati, Charaka Vinayak Kumar

The Large Language Models (LLMs) exhibit remarkable ability to generate fluent content across a wide spectrum of user queries. However, this capability has raised concerns regarding misinformation and personal information leakage. In this paper, we present our methods for the SemEval2024 Task8, aiming to detect machine-generated text across various domains i

Xiaojin Zhang, Wei Chen

The widespread adoption of machine learning necessitates robust privacy protection alongside algorithmic resilience. While Local Differential Privacy (LDP) provides foundational guarantees, sophisticated adversaries with prior knowledge demand more nuanced Bayesian privacy notions, such as Maximum Bayesian Privacy (MBP) and Average Bayesian Privacy (ABP), fi

Eleanor D'Arcy, Jonathan A Tawn

Max-autogressive moving average (Max-ARMA) processes are powerful tools for modelling time series data with heavy-tailed behaviour; these are a non-linear version of the popular autoregressive moving average models. River flow data typically have features of heavy tails and non-linearity, as large precipitation events cause sudden spikes in the data that the

Noga Alon, Or Zamir

A subset $S$ of the Boolean hypercube $\mathbb{F}_2^n$ is a sumset if $S = A+A = \{a + b \ | \ a, b\in A\}$ for some $A \subseteq \mathbb{F}_2^n$. We prove that the number of sumsets in $\mathbb{F}_2^n$ is asymptotically $(2^n-1)2^{2^{n-1}}$. Furthermore, we show that the family of sumsets in $\mathbb{F}_2^n$ is almost identical to the family of all subsets

Henrik Garde, Markus Hirvensalo

Recently an algorithm was given in [Garde & Hyv\"onen, SIAM J. Math. Anal., 2024] for exact direct reconstruction of any $L^2$ perturbation from linearised data in the two-dimensional linearised Calder\'on problem. It was a simple forward substitution method based on a 2D Zernike basis. We now consider the three-dimensional linearised Calder\'on problem in a

Sukhminder Singh, Lukas Pflug, Fabian Wein, Michael Stingl

Additively manufactured structures often exhibit a correlation between their mechanical properties, such as stiffness, strength, and porosity, and their wall thickness. This correlation stems from the interplay between the manufacturing process and the properties of the filler material. In this study, we investigate the thickness-dependent effect on structur

Feng-Ren Fan, Cong Xiao, Wang Yao

We discover an intrinsic dipole Hall effect in a variety of magnetic insulating states at integer fillings of twisted MoTe$_2$ moir\'e superlattice, including topologically trivial and nontrivial ferro-, antiferro-, and ferri-magnetic configurations. The dipole Hall current, in linear response to in-plane electric field, generates an in-plane orbital magneti

Shumpei Nishida, Kunihisa Okano

We study a linear quadratic regulation problem with a constraint where the control input can be nonzero only at a limited number of times. Given that this constraint leads to a combinational optimization problem, we adopt a greedy method to find a suboptimal solution. To quantify the performance of the greedy algorithm, we employ two metrics that reflect the

Nicolas Audinet de Pieuchon, Adel Daoud, Connor Thomas Jerzak, Moa Johansson

We investigate the potential of large language models (LLMs) to disentangle text variables--to remove the textual traces of an undesired forbidden variable in a task sometimes known as text distillation and closely related to the fairness in AI and causal inference literature. We employ a range of various LLM approaches in an attempt to disentangle text by i

Xufeng Xu, Francesco Stellacci

Protein-protein interactions (PPI) differ when measured in test tubes and cells due to the complexity of the intracellular environment. Free amino acids (AAs) and their derivatives constitute a significant fraction of the intracellular volume and mass. Recently, we have found that AAs have a general property of rendering protein dispersions more stable by re

Francisco Mena, Diego Arenas, Andreas Dengel

Studying and analyzing cropland is a difficult task due to its dynamic and heterogeneous growth behavior. Usually, diverse data sources can be collected for its estimation. Although deep learning models have proven to excel in the crop classification task, they face substantial challenges when dealing with multiple inputs, named Multi-View Learning (MVL). Th

Ashok K. Singal

Sky distributions of large samples of distant active galactic nuclei (AGNs) have shown dipoles significantly larger than the cosmic microwave background (CMB) dipole. However, a recent Bayesian analysis of the QUAIA sample, comprising 1.3 million quasars, has yielded a dipole that seems to be in tandem with the CMB dipole, in contravention of most previous s

Stefano Ardizzoni, Mattia Laurini, Rafael Praxedes, Luca Consolini

The behavior of cyclists when choosing the path to follow along a road network is not uniform. Some of them are mostly interested in minimizing the travelled distance, but some others may also take into account other features such as safety of the roads or pollution. Individuating the different groups of users, estimating the numerical consistency of each of

Hanchuan Chen, Yichao Liu, Fei Sun, Qianhan Sun

Simultaneously concentrating EM waves and heat fluxes to the same target region within an on-chip system carries substantial academic research importance and practical application value. Nevertheless, existing researches are primarily aimed at the design and experimentation of concentrators for individual EM waves or temperature fields. In this work, a therm

Lingdong Shen, Fangxin Shang, Xiaoshuang Huang, Yehui Yang

In the field of medical image segmentation, tackling Out-of-Distribution (OOD) segmentation tasks in a cost-effective manner remains a significant challenge. Universal segmentation models is a solution, which aim to generalize across the diverse modality of medical images, yet their effectiveness often diminishes when applied to OOD data modalities and tasks

Mohsen Faryabi, Amir Hossein Moradi

Nowadays, the number of emerging embedded systems rapidly grows in many application domains, due to recent advances in artificial intelligence and internet of things. The main inherent specification of these application-specific systems is that they have not a general nature and are basically developed to only perform a particular task and therefore, deal on

Amparo Güemes, Tiago da Silva Costa, Tamar Makin

Neurotechnologies are increasingly becoming integrated with our everyday lives, our bodies and our mental states. As the popularity and impact of neurotechnology grows, so does our responsibility to ensure we understand its particular implications on its end users, as well as broader ethical and societal implications. Enabling end-users and stakeholders to p

Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng

Antibody design, a crucial task with significant implications across various disciplines such as therapeutics and biology, presents considerable challenges due to its intricate nature. In this paper, we tackle antigen-specific antibody sequence-structure co-design as an optimization problem towards specific preferences, considering both rationality and funct

André F. C. Gomes, Mário A. T. Figueiredo

The partial information decomposition (PID) framework is concerned with decomposing the information that a set of (two or more) random variables (the sources) has about another variable (the target) into three types of information: unique, redundant, and synergistic. Classical information theory alone does not provide a unique way to decompose information in

Claudio Gambino, Paolo Pani, Fabio Riccioni

We compute the vacuum metric generated by a generic rotating object in arbitrary dimensions up to third post-Minkowskian order by computing the classical contribution of scattering amplitudes describing the graviton emission by massive spin-1 particles up to two loops. The solution depends on the mass, angular momenta, and on up to two parameters related to

Aleš Simončič, Andrej Hrovat, Grega Morano, Teodora Kocevska

Beam steering enables manipulation of the electromagnetic radiation patterns in antenna array systems. A methodology for steering beams in the near field of a planar antenna array with known phase wavefront functions towards arbitrary azimuth and elevation angles is described in this paper. Rotation of the phase wavefront function is used while preserving th

Rui Hu

In this thesis, we establish a necessary and sufficient condition for a weighted composition operator to commute with a self-adjoint weighted composition operator on the Fock space, then obtain a sufficient condition for these commuting weighted composition operators to be normal.

Hansi Hettiarachchi, Damith Premasiri, Lasitha Uyangodage, Tharindu Ranasinghe

The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. This is especially evident in low-resource languages, such as Sinhala, which face two primary challenges: the lack of substantial training data and limited benchmarking datasets. In response,

Z. Q. Qu, L. Chang, G. T. Dun, X. M. Cheng

Spectropolarimetric results of Fraunhofer lines between 516.3nm and 532.6nm are presented in local upper solar chromosphere, transition zone and inner corona below a height of about 0.04 solar radius above the solar limb. The data were acquired on Nov.3, 2013 during a total solar eclipse in Gabon by the prototype Fiber Arrayed Solar Optical Telescope(FASOT).

Md Abdul Kadir, GowthamKrishna Addluri, Daniel Sonntag

Explainable Artificial Intelligence (XAI) strategies play a crucial part in increasing the understanding and trustworthiness of neural networks. Nonetheless, these techniques could potentially generate misleading explanations. Blinding attacks can drastically alter a machine learning algorithm's prediction and explanation, providing misleading information by