March 2024 arXiv papers — page 44

Martina Lippi, Michael C. Welle, Maciej K. Wozniak, Andrea Gasparri

Haptic feedback is essential for humans to successfully perform complex and delicate manipulation tasks. A recent rise in tactile sensors has enabled robots to leverage the sense of touch and expand their capability drastically. However, many tasks still need human intervention/guidance. For this reason, we present a teleoperation framework designed to provi

D. Paoletti, J. Rubino-Martin, M. Shiraishi, D. Molinari

We present detailed forecasts for the constraints on primordial magnetic fields (PMFs) that will be obtained with the LiteBIRD satellite. The constraints are driven by the effects of PMFs on the CMB anisotropies: the gravitational effects of magnetically-induced perturbations; the effects on the thermal and ionization history of the Universe; the Faraday rot

Lavinia Corina Ciungu

We introduce the notion of distributivity for implicative-orthomodular lattices, proving an analogue result of the Foulis-Holland theorem. Based on this result, we characterize the distributive implicative-orthomodular lattices. Moreover, we define the center of an implicative-orthomodular lattice as the set of all elements that commute with all other elemen

Alex Jin, Shreyas Singh, Zhuo Zhang, AJ Hildebrand

By a classical result of Gauss and Kuzmin, the continued fraction expansion of a ``random'' real number contains each digit $a\in\mathbb{N}$ with asymptotic frequency $\log_2(1+1/(a(a+2)))$. We generalize this result in two directions: First, for certain sets $A\subset\mathbb{N}$, we establish simple explicit formulas for the frequency with which the continu

Di Cooke, Abigail Edwards, Sophia Barkoff, Kathryn Kelly

One of the current principal defenses against weaponized synthetic media continues to be the ability of the targeted individual to visually or auditorily recognize AI-generated content when they encounter it. However, as the realism of synthetic media continues to rapidly improve, it is vital to have an accurate understanding of just how susceptible people c

M. D. Gorski, S. Aalto, S. König, C. F. Wethers

How galaxies regulate nuclear growth through gas accretion by supermassive black holes (SMBHs) is one of the most fundamental questions in galaxy evolution. One potential way to regulate nuclear growth is through a galactic wind that removes gas from the nucleus. It is unclear whether galactic winds are powered by jets, mechanical winds, radiation, or via ma

Daniel Braak, Lei Cong, Hans-Peter Eckle, Henrik Johannesson

The Rabi-Stark model is a non-linear generalization of the quantum Rabi model including the dynamical Stark shift as a tunable term, which can be realized via quantum simulation on a cavity QED platform. When the Stark coupling becomes equal to the mode frequency, the spectrum changes drastically, a transition usually termed "spectral collapse" because numer

Jason Crampton, Eduard Eiben, Gregory Gutin, Daniel Karapetyan

Role mining is a technique used to derive a role-based authorization policy from an existing policy. Given a set of users $U$, a set of permissions $P$ and a user-permission authorization relation $\mahtit{UPA}\subseteq U\times P$, a role mining algorithm seeks to compute a set of roles $R$, a user-role authorization relation $\mathit{UA}\subseteq U\times R$

Pengcheng Hao, Oktay Karakus, Alin Achim

Driven by the filtering challenges in linear systems disturbed by non-Gaussian heavy-tailed noise, the robust Kalman filters (RKFs) leveraging diverse heavy-tailed distributions have been introduced. However, the RKFs rely on precise noise models, and large model errors can degrade their filtering performance. Also, the posterior approximation by the employe

Marko Maljkovic, Gustav Nilsson, Nikolas Geroliminis

When a centrally operated ride-hailing company considers to enter a market already served by another company, it has to make a strategic decision about how to distribute its fleet among different regions in the area. This decision will be influenced by the market share the company can secure and the costs associated with charging the vehicles in each region,

Zichen Hua, Yu Rong, Hui-jie Hu

We investigate the baryonic Tully-Fisher relation in low surface brightness galaxies selected from the Arecibo Legacy Fast ALFA survey. We find that the $\rm HI$-bearing low surface brightness galaxies still follow the baryonic Tully-Fisher relation of typical late-type galaxies, with a slope of approximately 4 in the baryonic mass versus rotational velocity

J. Mauxion, G. Lesur, S. Maret

Context: Protoplanetary discs are known to form around nascent stars from their parent molecular cloud as a result of angular momentum conservation. As they progressively evolve and dissipate, they also form planets. While a lot of modeling efforts have been dedicated to their formation, the question of their secular evolution, from the so-called class 0 emb

Artuur Stevens, Christophe Caloz

We present a general theory for calculating photon transitions in arbitrarily time-varying metamaterials. This theory circumvents the difficulties of conventional approaches in solving such a general problem by exploiting the eigenstates of time-dependent number operators. We demonstrate here the temporal evolution of these operators and the related transiti

Yamato Honda, Soma Onoda, Hiroshi Suzuki

We study how the symmetry operator of the axial $U(1)$ non-invertible symmetry acts on the 't~Hooft line operator in the $U(1)$ gauge theory by employing the modified Villain-type lattice formulation. We model the axial anomaly by a compact scalar boson, the ``QED axion''. For the gauge invariance, the simple 't~Hooft line operator, which is defined by a lin

Zhiwei Jiang, Yongjian Zeng, Ruichao Guo, Lu Lin

Nanostructured catalysts have attracted the increased attention for biomass conversion into high-valued chemicals due to the rapid depletion of fossil resources and increasingly severe environmental issues. Supercritical carbon dioxide (scCO2) fluid is an attractive medium for synthesizing nanostructured materials due to its favorable properties. In this rev

Deepak Narayan Gadde, Aman Kumar, Thomas Nalapat, Evgenii Rezunov

Modern hardware designs have grown increasingly efficient and complex. However, they are often susceptible to Common Weakness Enumerations (CWEs). This paper is focused on the formal verification of CWEs in a dataset of hardware designs written in SystemVerilog from Regenerative Artificial Intelligence (AI) powered by Large Language Models (LLMs). We applied

Haoyang Chen, Botong Xu, Kaiyang Zhong

Purpose: The study aims to investigate the application of the data element market in software project management, focusing on improving effort estimation by addressing challenges faced by traditional methods. Design/methodology/approach: This study proposes a solution based on feature selection, utilizing the data element market and reinforcement learning-ba

Nicolas Arancibia Robert, Paul Mezo

Arthur packets have been defined for pure real forms of symplectic and special orthogonal groups following two different approaches. The first approach, due to Arthur, Moeglin and Renard uses harmonic analysis. The second approach, due to Adams, Barbasch and Vogan uses microlocal geometry. We prove that the two approaches produce essentially equivalent Arthu

Yuchen Liu, Junyan Zhao

In this article, we study the K-moduli space of Fano threefolds obtained by blowing up $\mathbb{P}^3$ along $(2,3)$-complete intersection curves. This K-moduli space is a two-step birational modification of the GIT moduli space of $(3,3)$-curves on $\mathbb{P}^1 \times \mathbb{P}^1$. As an application, we show that our K-moduli space appears as one model of

Jakub Podgorný

This dissertation elaborates on X-ray polarisation features of astrophysical environments near accreting black holes. Although the work was originally assigned to supermassive black holes in active galactic nuclei, the results are also largely applicable to stellar-mass black holes in X-ray binary systems. Several numerical models predicting the X-ray polari

Luca Serena, Moreno Marzolla, Gabriele D'Angelo, Stefano Ferretti

Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably e

V. I. Shmotolokha, M. F. Holovko

This research focuses on the unique phase behavior of non-spherical patchy colloids in porous environments. Based on the theory of scaled particle (SPT), methods have been refined and applied to analyze the thermodynamic properties of non-spherical patchy particles in a disordered porous medium. Utilizing the associative theory of liquids in conjunction with

Vitalii Vertogradov, Maxim Misyura, Parth Bambhaniya

In this paper, we investigate the influence of primary hair ($l$) on the shadows of hairy Schwarzschild and Reissner-Nordstr\"om black holes obtained through gravitational decoupling. In the context of hairy Schwarzschild black holes, $l$ either has no effect or consistently enlarges the photon sphere radius. Notably, even when it violates the strong energy

Giulia Di Credico, Luca Consolini, Mattia Laurini, Marco Locatelli

We address the problem of parameter identification for the standard pharmacokinetic/pharmacodynamic (PK/PD) model for anesthetic drugs. Our main contribution is the development of a global optimization method that guarantees finding the parameters that minimize the one-step ahead prediction error. The method is based on a branch-and-bound algorithm, that can

V. I. Zhdanov, O. S. Stashko, Yu. V. Shtanov

We study spherically symmetric configurations of the quadratic $f(R)$ gravity in the Einstein frame. In case of a purely gravitational system, we have determined the global qualitative behavior of the metric and the scalaron field for all static solutions satisfying the conditions of asymptotic flatness. These solutions are proved to be regular everywhere ex

Everton Cavalcante, Thais Batista, Flavio Oquendo

Modern systems are increasingly connected and more integrated with other existing systems, giving rise to \textit{systems-of-systems} (SoS). An SoS consists of a set of independent, heterogeneous systems that interact to provide new functionalities and accomplish global missions through emergent behavior manifested at runtime. The distinctive characteristics

Gui-Juan Liu, Jia-Ming Zhang, Shan-Zhong Li, Zhi Li

We investigate the properties of mobility edge in an Aubry-Andr\'e-Harper model with non-reciprocal long-range hopping. The results reveal that there can be a new type of mobility edge featuring both strength-dependent and scale-free properties. By calculating the fractal dimension, we find that the positions of mobility edges are robust to the strength of n

Felix Agner, Ulrich Trabert, Anders Rantzer, Janybek Orozaliev

This work concerns reduction of the peak flow rate of a district heating grid, a key system property which is bounded by pipe dimensions and pumping capacity. The peak flow rate constrains the number of additional consumers that can be connected, and may be a limiting factor in reducing supply temperatures when transitioning to the 4th generation of district

Luca Di Persio, Matthias Ehrhardt, Sofia Rizzotto

This article presents an innovative approach to integrating port-Hamiltonian systems with neural network architectures, transitioning from deterministic to stochastic models. The study presents novel mathematical formulations and computational models that extend the understanding of dynamical systems under uncertainty and complex interactions. It emphasizes

Jonas Hein, Frédéric Giraud, Lilian Calvet, Alexander Schwarz

Surgery digitalization is the process of creating a virtual replica of real-world surgery, also referred to as a surgical digital twin (SDT). It has significant applications in various fields such as education and training, surgical planning, and automation of surgical tasks. In addition, SDTs are an ideal foundation for machine learning methods, enabling th

Hemjyoti Nath

We denote the number of partitions of $n$ wherein the even parts are distinct (and the odd parts are unrestricted) by $ped(n)$. In this paper, we will use generating function manipulations to obtain new congruences for $ped(n)$ modulo $24$.

Haishan Ye, Dachao Lin, Xiangyu Chang, Zhihua Zhang

In this paper, we propose a novel Anderson's acceleration method to solve nonlinear equations, which does \emph{not} require a restart strategy to achieve numerical stability. We propose the greedy and random versions of our algorithm. Specifically, the greedy version selects the direction to maximize a certain measure of progress for approximating the curre

Zhiwei Jiang, Zhiyue Zhao, Xin Li, Huaiguang Li

Developing a green and cost-effective catalytic system for the selective oxidation of biomass-derived alcohols is vital for the sustainable synthesis of fine chemicals. Herein, highly dispersed subnanometric amorphous CoOx clusters in anatase TiO2 nanosheets (Co-TiO2) fabricated by green solvent CO2 assisted approach could directly activate peroxymonosulfate

Nikita Durasov, Doruk Oner, Jonathan Donier, Hieu Le

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of their successive outputs is highly correlated with the accuracy of the value to which they converge. Thus,

Haoran Zhu

We analyze a system of linear algebraic equations whose solutions lead to a proof of a generalization of Boole's formula. In particular, our approach provides an elementary and short alternative to Katsuura's proof of this generalization.

Nils Ingelhag, Jesper Munkeby, Jonne van Haastregt, Anastasia Varava

In this paper, we build upon two major recent developments in the field, Diffusion Policies for visuomotor manipulation and large pre-trained multimodal foundational models to obtain a robotic skill learning system. The system can obtain new skills via the behavioral cloning approach of visuomotor diffusion policies given teleoperated demonstrations. Foundat

Yuichi Sano, Ikko Hamamura

Quantum circuits for loading probability distributions into quantum states are essential subroutines in quantum algorithms used in physics, finance engineering, and machine learning. The ability to implement these with high accuracy in low-depth quantum circuits is a critical issue. We propose a novel quantum state preparation method for probability distribu

Artem Khrapov, Vadim Popov, Tasnima Sadekova, Assel Yermekova

Diffusion models are known to be vulnerable to outliers in training data. In this paper we study an alternative diffusion loss function, which can preserve the high quality of generated data like the original squared $L_{2}$ loss while at the same time being robust to outliers. We propose to use pseudo-Huber loss function with a time-dependent parameter to a

Renato Vizuete, Paolo Frasca, Elena Panteley

In this paper we analyze continuous-time SIS epidemics subject to arrivals and departures of agents, by using an approximated process based on replacements. In defining the SIS dynamics in an open network, we consider a stochastic setting in which arrivals and departures take place according to Poisson processes with similar rates, and the new value of the i

Wen-Zheng Chen, Yang Liu, Siyu Li, Bin Hu

Recognizing the impact of contamination from weak gravitational lensing B-modes induced by Large Scale Structure, we examine delensing methods to enhance sensitivity to the tensor-to-scalar ratio $r$ in primordial B-mode detection experiments. This study presents a realistic pipeline to improve $r$ constraints using foreground-cleaned maps with negligible re

Sabri Koraltan, Rahul Gupta, Reshma Peremadathil Pradeep, Fabian Kammerbauer

Magnetic skyrmions are topologically protected local magnetic solitons that are promising for storage, logic or general computing applications. In this work, we demonstrate that we can use a skyrmion device based on [W/CoFeB/MgO] 1 0 multilayers for three-dimensional magnetic field sensing enabled by spin-orbit torques (SOT). We stabilize isolated chiral sky

Adil Belhaj, Abderrahim Bouhouch

Using $N = 2$ supergravity formalism, we investigate certain behaviors of five dimensional black objects from the compactification of M-theory on a Calabi-Yau three-fold. The manifold has been constructed as the intersection of two homogeneous polynomials of degrees $ (\omega+2,1)$ and $ (2,1) $ in a product of two weighted projective spaces given by $ \math

Shinya Tomizawa, Ryotaku Suzuki

We investigate possible configurations for vacuum multi-black holes that maintain static equilibrium in expanding bubbles. Our analysis assumes a five-dimensional Weyl metric to describe the spacetime, facilitating the derivation of solutions based on the provided rod structure. We consider a spacetime having expanding bubbles caused by one or two accelerati

Ramin Abolfath, Sedigheh Fardirad, Houda Kacem, Marie-Catherine Vozenin

Background: Lower production of H$_2$O$_2$ in water is a hallmark of ultra-high dose rate (UHDR) compared to the conventional dose rate (CDR). However, the current computational models based on the predicted yield of H$_2$O$_2$ are in opposite of the experimental data. Methods: We construct an analytical model for the rate equation in the production of H$_2$

Giovanni Amelino-Camelia, Iarley P. Lobo, Giovanni Palmisano

There has been strong interest in the possibility that in the quantum-gravity realm momentum space might be curved, mainly focusing, especially for what concerns phenomenological implications, on the case of a de Sitter momentum space. We here take as starting point the known fact that quantum gravity coupled to matter in $2+1$ spacetime dimensions gives ris

Beomki Yeo, Heather Gray, Andreas Salzburger, Stephen Nicholas Swatman

In high-energy physics experiments, the trajectories of charged particles are reconstructed using track reconstruction algorithms. Such algorithms need to both identify the set of measurements from a single charged particle and to fit the parameters by propagating tracks along the measurements. The propagation of the track parameter uncertainties is an impor

Adam Wyner, Tomasz Zurek, DOrota Stachura-Zurek

Agents act to bring about a state of the world that is more compatible with their personal or institutional values. To formalise this intuition, the paper proposes an action framework based on the STRIPS formalisation. Technically, the contribution expresses actions in terms of Value-based Formal Reasoning (VFR), which provides a set of propositions derived

Kazuya Shinjo, Kazuhiro Seki, Tomonori Shirakawa, Rong-Yang Sun

In periodically driven (Floquet) systems, evolution typically results in an infinite-temperature thermal state due to continuous energy absorption over time. However, before reaching thermal equilibrium, such systems may transiently pass through a meta-stable state known as a prethermal state. This prethermal state can exhibit phenomena not commonly observed

Fatima El Azzouzi, Detlef Klimm, Alexander Kapp, Leonard M. Verhoff

The investigation of the structural phase transition in the vicinity of the Curie temperature $T_c$ of LiNb$_{1-x}$Ta$_x$O$_3$ crystals is motivated by the expected combination of advantageous high-temperature properties of LiNbO$_3$ and LiTaO$_3$, including high piezoelectric modules and remarkable high-temperature stability, respectively. $T_c$ marks the u

Joris Raeymaekers, Canberk Sanli, Dieter Van den Bleeken

Formulation and supersymmetry localization of superconformal indices for $\mathcal{N}=2B$ superconformal quantum mechanics are reviewed by providing a generalization to fixed point submanifolds of resolved target space geometries, and future applications to gauged scaling quivers are discussed.

N. Lazarides, Giorgos P. Veldes, Amaria Javed, Ioannis Kourakis

The interaction between two co-propagating electrostatic wavepackets characterized by arbitrary carrier wavenumber is considered. A one-dimensional (1D) non-magnetized plasma model is adopted, consisting of a cold inertial ion fluid evolving against a thermalized (Maxwell-Boltzmann distributed) electron background. A multiple-scale perturbation method is emp

Christian Alber, Chupeng Ma, Robert Scheichl

We present a multiscale mixed finite element method for solving second order elliptic equations with general $L^{\infty}$-coefficients arising from flow in highly heterogeneous porous media. Our approach is based on a multiscale spectral generalized finite element method (MS-GFEM) and exploits the superior local mass conservation properties of mixed finite e

Luca Serena, Moreno Marzolla, Gabriele D'Angelo, Stefano Ferretti

Multilevel modeling and simulation (M&S) is becoming increasingly relevant due to the benefits that this methodology offers. Multilevel models allow users to describe a system at multiple levels of detail. From one side, this can make better use of computational resources, since the more detailed and time-consuming models can be executed only when/where requ

Philipp Hanisch, Markus Krötzsch

The chase is a widely implemented approach to reason with tuple-generating dependencies (tgds), used in data exchange, data integration, and ontology-based query answering. However, it is merely a semi-decision procedure, which may fail to terminate. Many decidable conditions have been proposed for tgds to ensure chase termination, typically by forbidding so

Menno van Zutphen, Giannis Delimpaltadakis, Maurice Heemels, Duarte Antunes

Regularization of control policies using entropy can be instrumental in adjusting predictability of real-world systems. Applications benefiting from such approaches range from, e.g., cybersecurity, which aims at maximal unpredictability, to human-robot interaction, where predictable behavior is highly desirable. In this paper, we consider entropy regularizat

Jeffrey S. Case, C Robin Graham, Tzu-Mo Kuo, Aaron J. Tyrrell

Assuming the extrinsic $Q$-curvature admits a decomposition into the Pfaffian, a scalar conformal submanifold invariant, and a tangential divergence, we prove that the renormalized area of an even-dimensional minimal submanifold of a Poincar\'e-Einstein manifold can be expressed as a linear combination of its Euler characteristic and the integral of a scalar

Jana N. Guenther, Szabolcs Borsányi, Zoltan Fodor, Ruben Kara

An efficient way to study the QCD phase diagram at small finite density is to extrapolate thermodynamical observables from imaginary chemical potential. The phase diagram features a crossover line starting from the transition temperature already determined at zero chemical potential. In this work we focus on the Taylor expansion of this line up to $\mu^4$ co

Zhiyue Zhao, Zhiwei Jiang, Yizhe Huang, Mebrouka Boubeche

Rational design and green synthesis of low-cost and robust catalysts efficient for the selective oxidation of various alcohols are full of challenges. Herein, we report a fast and solvent-free arc-melting (AM) method to controllably synthesize semimetal CoSi alloy (abbreviated as AM-CoSi) that is efficient for the base- and solvent-free oxidation of six type

Yasushi Esaki, Satoshi Koide, Takuro Kutsuna

Domain incremental learning (DIL) has been discussed in previous studies on deep neural network models for classification. In DIL, we assume that samples on new domains are observed over time. The models must classify inputs on all domains. In practice, however, we may encounter a situation where we need to perform DIL under the constraint that the samples o

Ke Yang, Enxuan Lin, Wangli Xu, Liping Zhu

Quantifying the heterogeneity is an important issue in meta-analysis, and among the existing measures, the $I^2$ statistic is most commonly used. In this paper, we first illustrate with a simple example that the $I^2$ statistic is heavily dependent on the study sample sizes, mainly because it is used to quantify the heterogeneity between the observed effect

Michio Jimbo, Evgeny Mukhin

We show that many tame modules of the quantum toroidal $\mathfrak{gl}_2$ algebra can be explicitly constructed in a purely combinatorial way using the theory of $q$-characters. The examples include families of evaluation modules obtained from analytic continuation and automorphism twists of Verma modules of the quantum affine $\mathfrak{gl}_2$ algebra. The c

Zvika Brakerski, Nir Magrafta

We explore a very simple distribution of unitaries: random (binary) phase -- Hadamard -- random (binary) phase -- random computational-basis permutation. We show that this distribution is statistically indistinguishable from random Haar unitaries for any polynomial set of orthogonal input states (in any basis) with polynomial multiplicity. This shows that ev

Ho-Meoyng Choi, Chueng-Ryong Ji

We investigate the interplay among the pion's form factor, transverse momentum dependent distributions (TMDs), and parton distribution functions (PDFs) extending our light-front quark model (LFQM) computation based on the Bakamjian-Thomas construction for the two-point function[41,42] to the three-point and four-point functions. Ensuring the four-momentum co

Zehan Li, Jianfei Zhang, Chuantao Yin, Yuanxin Ouyang

Retrieval-based code question answering seeks to match user queries in natural language to relevant code snippets. Previous approaches typically rely on pretraining models using crafted bi-modal and uni-modal datasets to align text and code representations. In this paper, we introduce ProCQA, a large-scale programming question answering dataset extracted fro

Jiaqi Feng, Xiaodong Zhou, Meiling Xu, Jingming Shi

Magneto-optical effects (MOE), interfacing the fundamental interplay between magnetism and light, have served as a powerful probe for magnetic order, band topology, and valley index. Here, based on multiferroic and topological bilayer antiferromagnets (AFMs), we propose a layer control of MOE (L-MOE), which is created and annihilated by layer-stacking or an

Chu Guo, Ruofan Chen

We present an infinite Grassmann time-evolving matrix product operator method for quantum impurity problems, which directly works in the steady state. The method embraces the well-established infinite matrix product state algorithms with the recently developed GTEMPO method, and benefits from both sides: it obtains real-time Green's functions without samplin

Yuanming Tian, Dongxu Li, Chuan Huang, Qingwen Liu

Resonant beam communications (RBCom), which adopt oscillating photons between two separate retroreflectors for information transmission, exhibit potential advantages over other types of wireless optical communications (WOC). However, echo interference generated by the modulated beam reflected from the receiver affects the transmission of the desired informat

Yunlong Tang, Yuxuan Wan, Lei Qi, Xin Geng

Source-Free Domain Generalization (SFDG) aims to develop a model that works for unseen target domains without relying on any source domain. Research in SFDG primarily bulids upon the existing knowledge of large-scale vision-language models and utilizes the pre-trained model's joint vision-language space to simulate style transfer across domains, thus elimina

Hanna Müller, Victor Kartsch, Michele Magno, Luca Benini

Nano-drones, distinguished by their agility, minimal weight, and cost-effectiveness, are particularly well-suited for exploration in confined, cluttered and narrow spaces. Recognizing transparent, highly reflective or absorbing materials, such as glass and metallic surfaces is challenging, as classical sensors, such as cameras or laser rangers, often do not

Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz

Prostate cancer is a dominant health concern calling for advanced diagnostic tools. Utilizing digital pathology and artificial intelligence, this study explores the potential of 11 deep neural network architectures for automated Gleason grading in prostate carcinoma focusing on comparing traditional and recent architectures. A standardized image classificati

Dongxu Li, Yuanming Tian, Chuan Huang, Qingwen Liu

This two-part paper focuses on the system design and performance analysis for a point-to-point resonant beam communication (RBCom) system under both the quasi-static and mobile scenarios. Part I of this paper proposes a synchronization-based information transmission scheme and derives the capacity upper and lower bounds for the quasi-static channel case. In

P. R. Stinga, M. Vaughan

We obtain sharp interior Schauder estimates for solutions to nonlocal Poisson problems driven by fractional powers of nondivergence form elliptic operators $(-a^{ij}(x) \partial_{ij})^s$, for $0<s<1$, in bounded domains under minimal regularity assumptions on the coefficients $a^{ij}(x)$. Solutions to the fractional problem are characterized by a local degen

Martin Wimmer, Myriam Kaiser, Jonas Kleiner, Jannis Wolff

Simulations and measurements on selective laser etching of display glasses are reported. By means of a holographic 3D beam splitter, ultrashort laser pulses are focused inside the volume of a glass sample creating type III modifications along a specific trajectory like pearls on a string. Superimposed by a feed of the glass sample a full 3D area of modificat

Yuuya Yoshida

For all $\alpha_1,\alpha_2\in(1,2)$ with $1/\alpha_1+1/\alpha_2>5/3$, we show that the number of pairs $(n_1,n_2)$ of positive integers with $N=\lfloor{n_1^{\alpha_1}}\rfloor+\lfloor{n_2^{\alpha_2}}\rfloor$ is equal to $\Gamma(1+1/\alpha_1)\Gamma(1+1/\alpha_2)\Gamma(1/\alpha_1+1/\alpha_2)^{-1}N^{1/\alpha_1+1/\alpha_2-1} + o(N^{1/\alpha_1+1/\alpha_2-1})$ as $

Francisco Caruso, Adílio Marques, Felipe Silveira

Starting from the perspective of reports published in Brazilian newspapers at the time, as well as letters exchanged between scientists who worked in Brazil and North American colleagues and documents from the symposium on cosmic rays, a chronological sequence of how the so-called Compton mission in Brazil took place and was perceived by the literate public

Sadanand Modak, Noah Patton, Isil Dillig, Joydeep Biswas

This paper addresses the problem of preference learning, which aims to align robot behaviors through learning user specific preferences (e.g. "good pull-over location") from visual demonstrations. Despite its similarity to learning factual concepts (e.g. "red door"), preference learning is a fundamentally harder problem due to its subjective nature and the p

Oliver Y. Feng, Yu-Chun Kao, Min Xu, Richard J. Samworth

In the context of linear regression, we construct a data-driven convex loss function with respect to which empirical risk minimisation yields optimal asymptotic variance in the downstream estimation of the regression coefficients. At the population level, the negative derivative of the optimal convex loss is the best decreasing approximation of the derivativ

Jiayue Zhang, Yiheng Liu, Wenqi Cai, Lanlan Wu

In recent years, the rapid development of artificial intelligence technology, especially the emergence of large language models (LLMs) such as ChatGPT, has presented significant prospects for application in the field of education. LLMs possess the capability to interpret knowledge, answer questions, and consider context, thus providing support for dialogic t

Dan Dicken, Macarena García Marín, Irene Shivaei, Pierre Guillard

The Mid-Infrared Instrument (MIRI) aboard the James Webb Space Telescope (JWST) provides the observatory with a huge advance in mid-infrared imaging and spectroscopy covering the wavelength range of 5 to 28 microns. This paper describes the performance and characteristics of the MIRI imager as understood during observatory commissioning activities, and throu

Nhat M. Hoang, Xuan Long Do, Duc Anh Do, Duc Anh Vu

The proliferation of online toxic speech is a pertinent problem posing threats to demographic groups. While explicit toxic speech contains offensive lexical signals, implicit one consists of coded or indirect language. Therefore, it is crucial for models not only to detect implicit toxic speech but also to explain its toxicity. This draws a unique need for u

Cheng Tan, Mingxun Deng, Yuanjun Yang, Linlin An

As a quasi-layered ferrimagnetic material, Mn$_3$Si$_2$Te$_6$ nanoflakes exhibit magnetoresistance behaviour that is fundamentally different from their bulk crystal counterparts. They offer three key properties crucial for spintronics. Firstly, at least 10^6 times faster response comparing to that exhibited by bulk crystals has been observed in current-contr

Dongjun Wu, Anders Rantzer

We investigate optimal mass transport problem of affine-nonlinear dynamical systems with input and density constraints. Three algorithms are proposed to tackle this problem, including two Uzawa-type methods and a splitting algorithm based on the Douglas-Rachford algorithm. Some preliminary simulation results are presented to demonstrate the effectiveness of

Yang Yang, Jiang-Tao Li, Theresa Wiegert, Zhiyuan Li

We report the discovery of the 10 kilo-parsec (kpc) scale radio lobes in the Sombrero galaxy (NGC 4594), using data from the Continuum Halos in Nearby Galaxies - an Expanded Very Large Array (VLA) Survey (CHANG-ES) project. We further examine the balance between the magnetic pressure inside the lobes and the thermal pressure of the ambient hot gas. At the ra

Borja Rodríguez-Gálvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund

This paper studies the truncation method from Alquier [1] to derive high-probability PAC-Bayes bounds for unbounded losses with heavy tails. Assuming that the $p$-th moment is bounded, the resulting bounds interpolate between a slow rate $1 / \sqrt{n}$ when $p=2$, and a fast rate $1 / n$ when $p \to \infty$ and the loss is essentially bounded. Moreover, the

Rene Winchenbach, Nils Thuerey

Learning physical simulations has been an essential and central aspect of many recent research efforts in machine learning, particularly for Navier-Stokes-based fluid mechanics. Classic numerical solvers have traditionally been computationally expensive and challenging to use in inverse problems, whereas Neural solvers aim to address both concerns through ma

Keita Ito, Ivan Kurniawan, Yusuke Shimada, Yoshio Miura

Flexible spintronics has opened new avenue to promising devices and applications in the field of wearable electronics. Particularly, miniaturized strain sensors exploiting the spintronic function have attracted considerable attention, in which the magnetoelasticity linking magnetism and lattice distortion is a vital property for high-sensitive detection of s

Dominik Müller, Philip Meyer, Lukas Rentschler, Robin Manz

Advances in digital pathology and artificial intelligence (AI) offer promising opportunities for clinical decision support and enhancing diagnostic workflows. Previous studies already demonstrated AI's potential for automated Gleason grading, but lack state-of-the-art methodology and model reusability. To address this issue, we propose DeepGleason: an open-s

Huifeng Yin, Mingkun Xu, Jing Pei, Lei Deng

Graph representation learning has become a crucial task in machine learning and data mining due to its potential for modeling complex structures such as social networks, chemical compounds, and biological systems. Spiking neural networks (SNNs) have recently emerged as a promising alternative to traditional neural networks for graph learning tasks, benefitin

Alireza Furutanpey, Qiyang Zhang, Philipp Raith, Tobias Pfandzelter

Nanosatellite constellations equipped with sensors capturing large geographic regions provide unprecedented opportunities for Earth observation. As constellation sizes increase, network contention poses a downlink bottleneck. Orbital Edge Computing (OEC) leverages limited onboard compute resources to reduce transfer costs by processing the raw captures at th

Dongxu Li, Yuanming Tian, Chuan Huang, Qingwen Liu

This two-part paper studies a point-to-point resonant beam communication (RBCom) system, where two separately deployed retroreflectors are adopted to generate the resonant beam between the transmitter and the receiver, and analyzes the transmission rate of the considered system under both the quasi-static and mobile scenarios. Part I of this paper focuses on

Antoine Gintrand, Quentin Moreno-Gelos

The evolution of shocks induced by massive stars does not depend only on the ambient magnetic field strength, but also on its orientation. In the present work, the dynamics of a magnetized blast wave is investigated under the influence of both azimuthal and axial ambient magnetic fields. The blast wave is driven by a central source and forms a shell that res

Huifeng Yin, Hanle Zheng, Jiayi Mao, Siyuan Ding

Spiking neural networks (SNNs), inspired by the neural circuits of the brain, are promising in achieving high computational efficiency with biological fidelity. Nevertheless, it is quite difficult to optimize SNNs because the functional roles of their modelling components remain unclear. By designing and evaluating several variants of the classic model, we s

Chihiro Tabata, Fusako Kon, Kyugo Ota, Ruo Hibino

Antiferromagnetic (AF) order of U$_{2}$Pt$_{6}$Ga$_{15}$ with the ordering temperature $T_{\rm N}$ = 26 K was investigated by resonant X-ray scattering and neutron diffraction on single crystals. This compound possesses a unique crystal structure in which uranium ions form honeycomb layers and then stacks along the $c$-axis with slight offset, which gives ri

Gemma Crowe

In this paper we provide an alternative solution to a result by Juh\'{a}sz that the twisted conjugacy problem for odd dihedral Artin groups is solvable, that is, groups with presentation $G(m) = \langle a,b \; | \; _{m}(a,b) = {}_{m}(b,a) \rangle$, where $m\geq 3$ is odd, and $_{m}(a,b)$ is the word $abab \dots$ of length $m$, is solvable. Our solution provi

Taekyun Kim, Dae san Kim

Let Y be a random variable whose moment generating function exists in some neighborhood of the origin. We consider the probabilistic bivariate Bell polynomials associated with Y and the probabilistic bivariate r-Bell polynomials associated with Y. For those polynomials, we derive the recurrence relations corresponding to the ones found by Zheng and Li for th

Yin Zhang, Jinhong Deng, Peidong Liu, Wen Li

Visual detection of Micro Air Vehicles (MAVs) has attracted increasing attention in recent years due to its important application in various tasks. The existing methods for MAV detection assume that the training set and testing set have the same distribution. As a result, when deployed in new domains, the detectors would have a significant performance degrad

Mali Jin, Daniel Preoţiuc-Pietro, A. Seza Doğruöz, Nikolaos Aletras

Bragging is the act of uttering statements that are likely to be positively viewed by others and it is extensively employed in human communication with the aim to build a positive self-image of oneself. Social media is a natural platform for users to employ bragging in order to gain admiration, respect, attention and followers from their audiences. Yet, litt

Fernando Acero, Parisa Zehtabi, Nicolas Marchesotti, Michael Cashmore

Portfolio optimization involves determining the optimal allocation of portfolio assets in order to maximize a given investment objective. Traditionally, some form of mean-variance optimization is used with the aim of maximizing returns while minimizing risk, however, more recently, deep reinforcement learning formulations have been explored. Increasingly, in

Paulo S. Piva, Gabriel Ruffolo

The Sleeping Beauty problem is a probability riddle with no definite solution for more than two decades and its solution is of great interest in many fields of knowledge. There are two main competing solutions to the problem: the halfer approach, and the thirder approach. The main reason for disagreement in the literature is connected to the use of different

Haichao Xu

The Fast Fourier Transform (FFT) is a fundamental tool for signal analysis, widely used across various fields. However, traditional FFT methods encounter challenges in adjusting the frequency bin interval, which may impede accurate spectral analysis. In this study, we propose a method for adjusting the frequency bin interval in FFT by introducing a parameter