March 2024 arXiv papers — page 25

Marco Di Marco, Antoine Julia, Sebastiano Nicolussi Golo, Davide Vittone

We introduce and study the notion of $C^1_\mathbb{H}$-regular submanifold with boundary in sub-Riemannian Heisenberg groups. As an application, we prove a version of Stokes' Theorem for $C^1_\mathbb{H}$-regular submanifolds with boundary that takes into account Rumin's complex of differential forms in Heisenberg groups.

Mohammadreza Amirian

Recent breakthroughs in machine and deep learning (ML and DL) research have provided excellent tools for leveraging enormous amounts of data and optimizing huge models with millions of parameters to obtain accurate networks for image processing. These developments open up tremendous opportunities for using artificial intelligence (AI) in the automation and h

Anamaria Hell

We study the degrees of freedom of the Proca theory, non-minimally coupled to gravity. In the Minkowski background, this theory propagates five degrees of freedom -- a massive longitudinal mode, two massive vector ones, and two massless tensor modes. At first sight, the non-linear coupling between the metric perturbations and the vector field indicates that

A. Mathey, J. Crassous, D. Marsan, J. Weiss

Sequences of aftershocks following Omori's empirical law are observed after most major earthquakes, as well as in laboratory-scale fault-mimicking experiments. Nevertheless, the origin of this memory effect is still unclear. In this letter, we present an analytical framework for treating labquake and earthquake catalogs on an equal footing. Using this analys

Payam Karisani, Heng Ji

Evaluating the veracity of everyday claims is time consuming and in some cases requires domain expertise. We empirically demonstrate that the commonly used fact checking pipeline, known as the retriever-reader, suffers from performance deterioration when it is trained on the labeled data from one domain and used in another domain. Afterwards, we delve into e

Dario Bambusi, Beatrice Langella

In this paper we present the notion of globally integrable quantum system that we introduced in [BL22]: we motivate it using the spectral theory of pseudodifferential operators and then we give some results on linear and nonlinear perturbations of a globally integrable quantum system. In particular, we give a spectral result ensuring stability of most of its

Chao Min, Yuan Cheng

We study the monic orthogonal polynomials with respect to a singularly perturbed Airy weight. By using Chen and Ismail's ladder operator approach, we derive a discrete system satisfied by the recurrence coefficients for the orthogonal polynomials. We find that the orthogonal polynomials satisfy a second-order linear ordinary differential equation, whose coef

Bar Eini Porat, Danny Eytan, Uri Shalit

Vital signs are crucial in intensive care units (ICUs). They are used to track the patient's state and to identify clinically significant changes. Predicting vital sign trajectories is valuable for early detection of adverse events. However, conventional machine learning metrics like RMSE often fail to capture the true clinical relevance of such predictions.

Yejin Kim, Scott Rome, Kevin Foley, Mayur Nankani

Addressing the challenges related to data sparsity, cold-start problems, and diversity in recommendation systems is both crucial and demanding. Many current solutions leverage knowledge graphs to tackle these issues by combining both item-based and user-item collaborative signals. A common trend in these approaches focuses on improving ranking performance at

Kieren Sharma, Lucia Marucci, Zahraa S. Abdallah

Gene essentiality, the necessity of a specific gene for the survival of an organism, is crucial to our understanding of cellular processes and identifying drug targets. Experimental determination of gene essentiality requires large growth screens that are time-consuming and expensive, motivating the development of in-silico approaches. Existing methods predo

Van Hao Can, Naoki Kubota, Shuta Nakajima

We consider the frog model with Bernoulli initial configuration, which is an interacting particle system on the multidimensional lattice consisting of two states of particles: active and sleeping. Active particles perform independent simple random walks. On the other hand, although sleeping particles do not move at first, they become active and can move arou

Olov Holmer, Erik Frisk, Mattias Krysander

In this paper, a family of neural network-based survival models is presented. The models are specified based on piecewise definitions of the hazard function and the density function on a partitioning of the time; both constant and linear piecewise definitions are presented, resulting in a family of four models. The models can be seen as an extension of the c

Philippe Charron, François Pagano

On a closed analytic manifold $(M,g)$, let $\phi_i$ be the eigenfunctions of $\Delta_g$ with eigenvalues $\lambda_i^2$ and let $f:=\prod \phi_{k_j}$ be a finite product of Laplace-Beltrami eigenfunctions. We show that $\left\langle f, \phi_i \right\rangle_{L^2(M)}$ decays exponentially as soon as $\lambda_i > C \sum \lambda_{k_j}$ for some constant $C$ depen

Florian J. Kiwit, Maximilian A. Wolf, Marwa Marso, Philipp Ross

Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to scale quantum machine learning (QML) to industrial-level applications. This paper investigates the scalability and noise resilience of quantum generative learning applications. We

Ethan Marx, William Benoit, Alec Gunny, Rafia Omer

The promise of multi-messenger astronomy relies on the rapid detection of gravitational waves at very low latencies ($\mathcal{O}$(1\,s)) in order to maximize the amount of time available for follow-up observations. In recent years, neural-networks have demonstrated robust non-linear modeling capabilities and millisecond-scale inference at a comparatively sm

Ruoyu Zhao, Qingnan Fan, Fei Kou, Shuai Qin

In recent years, instruction-based image editing methods have garnered significant attention in image editing. However, despite encompassing a wide range of editing priors, these methods are helpless when handling editing tasks that are challenging to accurately describe through language. We propose InstructBrush, an inversion method for instruction-based im

Janik-Vasily Benzin, Gyunam Park, Juergen Mangler, Stefanie Rinderle-Ma

Process events are recorded by multiple information systems at different granularity levels. Based on the resulting event logs, process models are discovered at different granularity levels, as well. Events stored at a fine-grained granularity level, for example, may hinder the discovered process model to be displayed due the high number of resulting model e

Gilad Lerman, Teng Zhang

This work analyzes the subspace-constrained Tyler's estimator (STE), a method designed to recover a low-dimensional subspace from a dataset that may be heavily corrupted by outliers. The STE has previously been shown to be competitive for fundamental computer vision problems. We assume a weak inlier-outlier model and allow the inlier fraction to fall bel

J. Álvarez-Cuervo, M. Obst, S. Dixit, G. Carini

The vast repository of van der Waals (vdW) materials supporting polaritons offers numerous possibilities to tailor electromagnetic waves at the nanoscale. The development of twistoptics - the modulation of the optical properties by twisting stacks of vdW materials - enables directional propagation of phonon polaritons (PhPs) along a single spatial direction,

Mrunal Korwar, Stefano Profumo

Black holes long-lived enough to be the dark matter have temperatures below the MeV. Since Hawking evaporation is a quasi-thermal process, no GeV emission is predicted to be produced by black holes if they are part, or all, of the cosmological dark matter. However, black holes could be ``spawned'' at late times with masses that correspond to short lifetimes,

Laura N. Casses, Binbin Zhou, Qiaoling Lin, Annie Tan

Exciton-plasmon polaritons (EPPs) are attractive both for the exploration of fundamental phenomena and applications in nanophotonics. Previous studies of EPPs mainly relied on far-field characterization. Here, using near-field optical microscopy, we quantitatively characterize the dispersion of EPPs existing in 13-nm-thick tungsten diselenide (WSe$_2$) depos

Arturo Fernández-Pérez, Evelia R. García Barroso, Nancy Saravia-Molina

Let $\mathcal{F}$ be a holomorphic foliation at $p\in\mathbb{C}^2$, and $B$ be a separatrix of $\mathcal{F}$. We prove the following Dimca-Greuel type inequality $3\mu_p(\mathcal{F},B)-4\tau_p(\mathcal{F},B)+GSV_p(\mathcal{F},B)\leq 0$, where $\mu_p(\mathcal{F},B)$ is the multiplicity of $\mathcal{F}$ along $B$, $\tau_p(\mathcal{F},B)$ is the dimension of th

Carsten Dietzel, Silvia Properzi, Senne Trappeniers

The quantum Yang-Baxter equation is a braiding condition on vector spaces which is of high relevance in several fields of mathematics, such as knot theory and quantum group theory. Their combinatorial counterpart are set-theoretic solutions to the Yang--Baxter equation, whose investigation is strongly driven by the study of algebraic objects called (skew) br

H. Arthur Weldon

The statistical mechanics of an ideal gas of point particles moving in a time independent background metric with $g_{0j}\neq 0$ is investigated. An explicit calculation shows that when there is no background electrostatic or magnetostatic field the thermodynamic pressure, energy density, and thermally averaged energy-momentum tensor depend on temperature and

Mohammad R. Salmanpour, Amin Mousavi, Yixi Xu, William B Weeks

This study investigates the foundational characteristics of image-to-image translation networks, specifically examining their suitability and transferability within the context of routine clinical environments, despite achieving high levels of performance, as indicated by a Structural Similarity Index (SSIM) exceeding 0.95. The evaluation study was conducted

Riccardo Periotto, Mina Ferizbegovic, Fernando S. Barbosa, Roberto C. Sundin

The paper focuses on the design of a control strategy for safety-critical remote teleoperation. The main goal is to make the controlled system track the desired velocity specified by an operator while avoiding obstacles despite communication delays. Control Barrier Functions (CBFs) are used to define the safety constraints that the system has to respect to a

Ajinkya Khoche, Aron Asefaw, Alejandro Gonzalez, Bogdan Timus

Data annotation in autonomous vehicles is a critical step in the development of Deep Neural Network (DNN) based models or the performance evaluation of the perception system. This often takes the form of adding 3D bounding boxes on time-sequential and registered series of point-sets captured from active sensors like Light Detection and Ranging (LiDAR) and Ra

Théo Lebeau, Stefano Ettori, Nabila Aghanim, Jenny G. Sorce

The splashback radius was proposed as a physically motivated boundary of clusters as it sets the limit between the infalling and the orbitally dominated regions. However, galaxy clusters are complex objects connected to filaments of the cosmic web from which they accrete matter that disturbs them and modifies their morphology. In this context, estimating the

Chengbo Liu, Yong Zhu

We propose an acceleration scheme for large language models (LLMs) through Speculative Decoding with Semantic Adaptive Tokens (SDSAT). The primary objective of this design is to enhance the LLM model's ability to generate draft tokens more accurately without compromising the model's accuracy. The core strategies involve: 1) Fine-tune the model by incorporati

Christian Cachin, David Lehnherr, Thomas Studer

In formal epistemology, group knowledge is often modelled as the knowledge that the group would have, if the agents shared all their individual knowledge. However, this interpretation does not account for relations between agents. In this work, we propose the notion of synergistic knowledge which makes it possible to model those relationships.

Cristina Flaut, Andreea Baias

In this paper we provide some properties of k-potent elements in algebras obtained by the Cayley-Dickson process over Zp. Moreover, we find a structure of nonunitary ring over Fibonacci quaternions over Z3 and we present a method to encrypt plain texts, by using invertible elements in such algebras.

Victor Hughes, Isaac Harris, Heejin Lee

In this paper, we consider the inverse scattering problem associated with an anisotropic medium with a conductive boundary. We will assume that the corresponding far-field pattern is known/measured and we consider two inverse problems. First, we show that the far-field data uniquely determines the boundary coefficient. Next, since it is known that anisotropi

Levent Ögretmen, Matthias Rowold, Alexander Langmann, Boris Lohmann

Existing approaches to trajectory planning for autonomous racing employ sampling-based methods, generating numerous jerk-optimal trajectories and selecting the most favorable feasible trajectory based on a cost function penalizing deviations from an offline-calculated racing line. While successful on oval tracks, these methods face limitations on complex cir

Martin Durand, Fanny Pascual

The collective schedules problem consists in computing a schedule of tasks shared between individuals. Tasks may have different duration, and individuals have preferences over the order of the shared tasks. This problem has numerous applications since tasks may model public infrastructure projects, events taking place in a shared room, or work done by co-wor

Gayatri Čaklović, Thibaut Lunet, Sebastian Götschel, Daniel Ruprecht

Parallel-across-the method time integration can provide small scale parallelism when solving initial value problems. Spectral deferred corrections (SDC) with a diagonal sweeper, which is closely related to iterated Runge-Kutta methods proposed by Van der Houwen and Sommeijer, can use a number of threads equal to the number of quadrature nodes in the underlyi

Marc Winstel, Semeon Valgushev

In this talk, we study a scalar $O(N)$ model with a so-called moat regime -- a regime with negative bosonic wave function renormalization -- using lattice field theory. For negative bare wave function renormalization, inhomogeneous condensates are solutions of the classical equations of motions. Using hybrid Monte Carlo simulations we demonstrate how bosonic

Jinhua Liang, Ines Nolasco, Burooj Ghani, Huy Phan

Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims to train a versatile animal sound detector using only a small set of audio samples. Previous efforts in this ar

Yalda Zafari-Ghadim, Essam A. Rashed, Mohamed Mabrok

Stroke remains a significant global health concern, necessitating precise and efficient diagnostic tools for timely intervention and improved patient outcomes. The emergence of deep learning methodologies has transformed the landscape of medical image analysis. Recently, Transformers, initially designed for natural language processing, have exhibited remarka

Eloi Moliner, Maija Turunen, Filip Elvander, Vesa Välimäki

This paper presents a novel approach to audio restoration, focusing on the enhancement of low-quality music recordings, and in particular historical ones. Building upon a previous algorithm called BABE, or Blind Audio Bandwidth Extension, we introduce BABE-2, which presents a series of improvements. This research broadens the concept of bandwidth extension t

Leonardo Pepino, Pablo Riera, Luciana Ferrer, Agustin Gravano

In this paper, we study different approaches for classifying emotions from speech using acoustic and text-based features. We propose to obtain contextualized word embeddings with BERT to represent the information contained in speech transcriptions and show that this results in better performance than using Glove embeddings. We also propose and compare differ

Elisha Falbel, Antonin Guilloux, Pierre Will

Bounded symmetric domains carry several natural invariant metrics, for example the Carath\'eodory, Kobayashi or the Bergman metric. We define another natural metric, from generalized Hilbert metric defined in [FGW20], by considering the Borel embedding of the domain as an open subset of its dual compact Hermitian symmetric space and then its Harish-Chandra r

Duygu Yıldırım

Hadron spectroscopy is revealed by observing heavy resonances. Among various explanations of the internal structure of these hadronic states, hadronic molecules play a unique role. For hadronic molecules, which are associated with meson-meson or meson-baryon interactions, the $\Lambda$ cutoff is a significant factor in determining the composite states' bindi

Yu Chen, Xuanyuan Yin, Shaoyuan Li, Xiang Yin

We investigate the problem of optimal control synthesis for Markov Decision Processes (MDPs), addressing both qualitative and quantitative objectives. Specifically, we require the system to satisfy a qualitative task specified by a Linear Temporal Logic (LTL) formula with probability one. Additionally, to quantify the system's performance, we introduce the c

Enzo Rucci, Gonzalo Tittarelli, Franco Ronchetti, Jorge F. Elgart

Detecting Type 2 Diabetes (T2D) and Prediabetes (PD) is a real challenge for medicine due to the absence of pathogenic symptoms and the lack of known associated risk factors. Even though some proposals for machine learning models enable the identification of people at risk, the nature of the condition makes it so that a model suitable for one population may

Zhen-hua Zhao, Jing Zhang, Xiang-Yi Wu

In this paper, we would like to point out that in the scenario that the right-handed neutrinos suddenly gain some masses much larger than the temperature of the Universe at that time so that the washout effects for the lepton asymmetry generated from their decays can be neglected safely, the purely flavored leptogenesis scenario (in which the total CP asymme

A. J. Smith, C. Hebborn, F. M. Nunes, R. G. T. Zegers

Charge-exchange reactions are versatile probes for nuclear structure. In particular, when populating isobaric analog states, these reactions are used to study isovector nuclear densities and neutron skins. The quality of the information extracted from charge-exchange data depends on the accuracy of the reaction models and their inputs; this work addresses th

Zhefan Wang, Weizhi Ma, Min Zhang

Most current recommender systems primarily focus on what to recommend, assuming users always require personalized recommendations. However, with the widely spread of ChatGPT and other chatbots, a more crucial problem in the context of conversational systems is how to minimize user disruption when we provide recommendation services for users. While previous r

Jiang Long, Run-Ze Yu

The helicity flux density is a novel quantity which characterizes the angle-dependence of the helicity of radiative gravitons and it may be tested by gravitational wave experiments in the future. We derive a quadrupole formula for the helicity flux density due to gravitational radiation in the slow motion and the weak field limit. We apply the formula to the

Yu Wang, Yimin Xiao, Lihu Xu

We study in this paper the EM scheme for a family of well-posed critical SDEs with the drift $-x\log(1+|x|)$ and $\alpha$-stable noises. Specifically, we find that when the SDE is driven by a rotationally symmetric $\alpha$-stable processes with $\alpha=2$ (i.e. Brownian motion), the EM scheme is bounded in the $L^2$ sense uniformly w.r.t. the time. In contr

I. A. Zaznobin, R. A. Burenin, A. A. Belinski, I. F. Bikmaev

We present the results of the optical identification and spectroscopic redshift measurements of 216 galaxy clusters detected in the SRG/eROSITA all-sky X-ray survey. The spectroscopic observations were performed in 2020-2023 with the 6-m BTA telescope at the Special Astrophysical Observatory of the Russian Academy of Sciences, the 2.5-m telescope at the Cauc

Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin

In the context of the rising interest in code language models (code LMs) and vulnerability detection, we study the effectiveness of code LMs for detecting vulnerabilities. Our analysis reveals significant shortcomings in existing vulnerability datasets, including poor data quality, low label accuracy, and high duplication rates, leading to unreliable model p

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh Mukherjee

In digital markets, antitrust law and special regulations aim to ensure that markets remain competitive despite the dominating role that digital platforms play today in everyone's life. Unlike traditional markets, market participant behavior is easily observable in these markets. We present a series of empirical investigations into the extent to which Amazon

Ankur Nahar, Koustav Kumar Mondal, Debasis Das, Rajkumar Buyya

This research addresses the critical necessity for advanced rapid response operations in managing a spectrum of environmental hazards. We propose a novel framework, qIoV that integrates quantum computing with the Internet-of-Vehicles (IoV) to leverage the computational efficiency, parallelism, and entanglement properties of quantum mechanics. Our approach in

Ting-Han Huang

In this paper, we generalize two results of H. Darmon and V. Rotger on triple product $p$-adic $L$-functions associated with Hida families to finite slope families. We first prove a $p$-adic Gross-Zagier formula, then demonstrate an application to a special case of the equivariant Birch and Swinnerton-Dyer conjecture for supersingular elliptic curves.

Sergio Calderón, Enzo Rucci, Franco Chichizola

Graphs have become a key tool when modeling and solving problems in different areas. The Floyd-Warshall (FW) algorithm computes the shortest path between all pairs of vertices in a graph and is employed in areas like communication networking, traffic routing, bioinformatics, among others. However, FW is computationally and spatially expensive since it requir

Defeng Sun, Yancheng Yuan, Guojun Zhang, Xinyuan Zhao

In this paper, we aim to accelerate a preconditioned alternating direction method of multipliers (pADMM), whose proximal terms are convex quadratic functions, for solving linearly constrained convex optimization problems. To achieve this, we first reformulate the pADMM into a form of proximal point method (PPM) with a positive semidefinite preconditioner whi

Giacomo De Palma, Davide Pastorello

We prove new concentration inequalities for quantum spin systems which apply to any local observable measured on any product state or on any state with exponentially decaying correlations. Our results do not require the spins to be arranged in a regular lattice, and cover the case of observables that contain terms acting on spins at arbitrary distance. Moreo

Yuchong Zhang, Miguel Vasco, Mårten Björkman, Danica Kragic

This paper presents findings from an exploratory needfinding study investigating the research current status and potential participation of the competitions on the robotics community towards four human-centric topics: safety, privacy, explainability, and federated learning. We conducted a survey with 34 participants across three distinguished European roboti

Eduardo M. K. Souza, Guilherme M. A. Almeida

We introduce a family of complex networks that interpolates between the Apollonian network and its binary version, recently introduced in [Phys. Rev. E \textbf{107}, 024305 (2023)], via random removal of nodes. The dilution process allows the clustering coefficient to vary from $C=0.828$ to $C=0$ while maintaining the behavior of average path length and othe

Akshit Goyal, Mikhail Tikhonov

The search for extraterrestrial life hinges on identifying biosignatures, often focusing on gaseous metabolic byproducts as indicators. However, most such biosignatures require assuming specific metabolic processes. It is widely recognized that life on other planets may not resemble that of Earth, but identifying biosignatures ``agnostic'' to such assumption

Yusuf Sulehman, Tingting Mu

Estimating the Lipschitz constant of deep neural networks is of growing interest as it is useful for informing on generalisability and adversarial robustness. Convolutional neural networks (CNNs) in particular, underpin much of the recent success in computer vision related applications. However, although existing methods for estimating the Lipschitz constant

Tadashi Arimitsu, Johannes Jaerisch, Hiroki Sumi, Takayuki Watanabe

We establish Bowen's formula for the Julia set of a non-elementary, expanding, irreducible and aperiodic rational graph-directed Markov system satisfying the backward separating condition. Towards this end, we shall prove that the associated skew product map is topologically exact on the skew product Julia set, and satisfies the density of repelling periodic

Jakob Führer, Vladislav Taranchuk

In this paper, we construct explicit families of polynomials $P \in \mathbb{F}_q[x_1,\dots,x_n]$ with large root sets which have restricted intersections with affine lines. We use these sets to make substantial progress on a number of problems in extremal combinatorics. For each prime power $q$ and integer $2 \le t \le q-1$, we construct $t$-line evasive sub

Claudio Gatti, Luca Visinelli, Michael Zantedeschi

High frequency gravitational waves (HFGWs) are predicted in various exotic scenarios involving both cosmological and astrophysical sources. These elusive signals have recently sparked the interest of a diverse community of researchers, due to the possibility of HFGW detection in the laboratory through graviton-photon conversion in strong magnetic fields. Not

Prithwineel Paul, Petr Sosik, Lucie Ciencialova

Spiking neural networks (SNN) are a biologically inspired model of neural networks with certain brain-like properties. In the past few decades, this model has received increasing attention in computer science community, owing also to the successful phenomenon of deep learning. In SNN, communication between neurons takes place through the spikes and spike tra

I. A. Zaznobin, R. A. Burenin, A. V. Meshcheryakov, M. R. Gilfanov

We discuss an algorithm whereby the massive galaxy clusters detected in the SRG/eROSITA all-sky survey are identified and their photometric redshifts are estimated. For this purpose, we use photometric redshift estimates for galaxies and WISE forced photometry. To estimate the algorithm operation quality, we used a sample of 634 massive galaxy clusters from

Hanqing Fu, Gaolei Li, Jun Wu, Jianhua Li

Federated neuromorphic learning (FedNL) leverages event-driven spiking neural networks and federated learning frameworks to effectively execute intelligent analysis tasks over amounts of distributed low-power devices but also perform vulnerability to poisoning attacks. The threat of backdoor attacks on traditional deep neural networks typically comes from ti

Lai Zhao, Meirong Tang, Zhaoyi Xu

The quantum-corrected black hole model demonstrates significant potential in the study of gravitational lensing effects. By incorporating quantum effects, this model addresses the singularity problem in classical black holes. In this paper, we investigate the impact of the quantum correction parameter on the lensing effect based on the quantum corrected blac

Trong-Tung Nguyen, Duc-Anh Nguyen, Anh Tran, Cuong Pham

Our work addresses limitations seen in previous approaches for object-centric editing problems, such as unrealistic results due to shape discrepancies and limited control in object replacement or insertion. To this end, we introduce FlexEdit, a flexible and controllable editing framework for objects where we iteratively adjust latents at each denoising step

Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah

Tourism affects not only the tourism industry but also society and stakeholders such as the environment, local businesses, and residents. Tourism Recommender Systems (TRS) can be pivotal in promoting sustainable tourism by guiding travelers toward destinations with minimal negative impact. Our paper introduces a composite sustainability indicator for a city

Dominik Ciurla

Interactions of small-amplitude monochromatic plane waves with domain walls in (1+1) dimensional abelian Higgs model with a sextic potential were studied. The effective force exerted on a domain wall was derived from a linearized equation and compared with numerical simulations of the original model. It was shown that the domain walls always accelerate in on

Alessio Albanese, Wouter Kohlen, Pariya Behrouzi

Motivation: In recent years, the availability of multi-omics data has increased substantially. Multi-omics data integration methods mainly aim to leverage different molecular layers to gain a complete molecular description of biological processes. An attractive integration approach is the reconstruction of multi-omics networks. However, the development of ef

Wei Wei, Julian Gebhardt, Daniel F. Urban, Christian Elsässer

The integrated device of a perovskite solar cell with a Li-ion battery is an innovative solution for decentralized energy storage in smart electronic devices. In this study, we examine the stability of Li ions intercalated in a CsPbI$_3$ perovskite and their effect on the electronic structure of Li$_x$CsPbI$_3$ compounds using first-principles density functi

Ali Zare, Yulei Niu, Hammad Ayyubi, Shih-fu Chang

Procedure Planning in instructional videos entails generating a sequence of action steps based on visual observations of the initial and target states. Despite the rapid progress in this task, there remain several critical challenges to be solved: (1) Adaptive procedures: Prior works hold an unrealistic assumption that the number of action steps is known and

Hoang Nguyen, Manuel Clavel

In the context of the model-driven development of data-centric applications, OCL constraints play a major role in adding precision to the source models (e.g., data models and security models). Several code-generators have been proposed to bridge the gap between source models with OCL constraints and their corresponding database implementations. However, the

Andrea Dagmar Pajdarová, Tomáš Kozák, Tomáš Tölg, Jiří Čapek

Time-resolved Langmuir probe diagnostics at the discharge centerline and at three distances from the target (35mm, 60mm, and 100mm) was carried out during long positive voltage pulses (a duration of 500$\mu$s and a preset positive voltage of 100V) in bipolar High-Power Impulse Magnetron Sputtering of a Ti target (a diameter of 100mm) using an unbalanced magn

Siavash Jafarzadeh, Stewart Silling, Lu Zhang, Colton Ross

Human tissues are highly organized structures with collagen fiber arrangements varying from point to point. Anisotropy of the tissue arises from the natural orientation of the fibers, resulting in location-dependent anisotropy. Heterogeneity also plays an important role in tissue function. It is therefore critical to discover and understand the distribution

Giulio Colombo, Marco Mariani, Marco Rigoli

We prove an extension of Eells and Sampson's rigidity theorem for harmonic maps from a closed manifold of non-negative Ricci curvature to a manifold of non-positive sectional curvature. We give an application of our result in the setting of harmonic-Einstein (or Ricci-harmonic) metrics and as a consequence we recover a classical rigidity result of Hamilton f

Sarah Peery, Yi-Hsin Liu, Xiaocan Li

The scaling of the relativistic reconnection outflow speed is studied in the presence of both shear flows parallel to the reconnecting magnetic fields and guide fields pointing out of the reconnection plane. In nonrelativistic reconnection, super-Alfv\'enic shear flows have been found to suppress reconnection. We extend the analytical model of this phenomeno

Daniele Bielli, Vaibhav Gautam, Vasileios Moustakis, Andrea Prinsloo

We study the boundary integrability problem of the massless sector of $AdS_3 \times S^3 \times T^4 $ string theory. Exploiting the difference-form of the massless scattering theory, we find a very simple and exhaustive list of reflection matrices for all the possible boundary coideal subalgebras - singlet and vector representations, right and left boundary -

Run Shao, Zhaoyang Zhang, Chao Tao, Yunsheng Zhang

The tokenizer, as one of the fundamental components of large models, has long been overlooked or even misunderstood in visual tasks. One key factor of the great comprehension power of the large language model is that natural language tokenizers utilize meaningful words or subwords as the basic elements of language. In contrast, mainstream visual tokenizers,

Rick Durrett

In this paper we will consider the contact process in a very simple type of random environment that physicists call the random dilution model. We start with the contact process on a graph, here either $\mathbb{Z}^d$, a $d$-dimensional torus or an \ER graph, and then flip independent $(1-p)$ coins to delete edges, or delete vertices. Let $p^*$ be the threshol

M. Eisaei, Gh. R. Moghimi

In this paper, we investigate $\theta$-derivations on Banach algebra $ L_0^{\infty} (w)^*$. First, we study the range of them and prove the Singer-Wermer conjucture. We also give a characterization of the space of all $\theta$-derivations on $ L_0^{\infty} (w)^*$. Then, we prove automatic continuity and Posner's theorems for $\theta$-derivations.

Martin Bruse, Luca Versari, Zoltan Szabadka, Jyrki Alakuijala

We performed pairwise comparisons by human raters of JPEG images from MozJPEG, libjpeg-turbo and our new Jpegli encoder. When compressing images at a quality similar to libjpeg-turbo quality 95, the Jpegli images were 54% likely to be preferred over both libjpeg-turbo and MozJPEG images, but used only 2.8 bits per pixel compared to libjpeg-turbo and MozJPEG

Steven M. LaValle, Evan G. Center, Timo Ojala, Matti Pouke

This paper makes the case that a powerful new discipline, which we term perception engineering, is steadily emerging. It follows from a progression of ideas that involve creating illusions, from historical paintings and film, to video games and virtual reality in modern times. Rather than creating physical artifacts such as bridges, airplanes, or computers,

Andreas Müller, Erwin Quiring

Resource efficiency plays an important role for machine learning nowadays. The energy and decision latency are two critical aspects to ensure a sustainable and practical application. Unfortunately, the energy consumption and decision latency are not robust against adversaries. Researchers have recently demonstrated that attackers can compute and submit so-ca

Arseni Goussev, Felix Quinque, Jaewoo Joo, Andrew Burbanks

The probability density of a quantum particle moving freely within a circular ring can exhibit local flow patterns inconsistent with its angular momentum, a phenomenon known as quantum backflow. In this study, we examine a quantum particle confined to a ring and prepared in a state composed of a fixed (yet arbitrary) number of lowest energy eigenstates with

Andrea Sacchetti

While the phenomenon of the exact crossing of energy levels is a rarely occurring event, in the case of quantum resonances associated with metastable states this phenomenon is much more frequent and various scenarios can occur. When there is an exact crossing of the imaginary parts of the resonances in a two-level quantum system subject to an external DC ele

Philip Metzger

In the companion paper ("Erosion rate of lunar soil under a landing rocket, part 1: identifying the rate-limiting physics", this issue) an equation was developed for the rate that lunar soil erodes under the exhaust of a landing rocket. That equation has only one parameter that is not calibrated from first principles, so here it is calibrated by the blowing

Philip Metzger

Multiple nations are planning activity on the Moon's surface, and to deconflict lunar operations we must understand the sandblasting damage from rocket exhaust blowing soil. Prior research disagreed over the scaling of the erosion rate, which determines the magnitude of the damage. Reduced gravity experiments and two other lines of evidence now indicate that

Dominik Hasiwar, Andreas Gruber, Christian Dragschitz, Igor Ivkić

In the evolving landscape of workplace dynamics, the shift towards hybrid working models has highlighted inefficiencies in the use of traditional office space and the need for an improved employee experience. In this position paper we propose a Smart Office solution that addresses these challenges by integrating a microservice architecture with Internet of T

Caio Cesar Daumann, Mauro Donega, Johannes Erdmann, Massimiliano Galli

Simulated events are key ingredients in almost all high-energy physics analyses. However, imperfections in the simulation can lead to sizeable differences between the observed data and simulated events. The effects of such mismodelling on relevant observables must be corrected either effectively via scale factors, with weights or by modifying the distributio

Mariagrazia Iuliano, Marie-Christine Slater, Arian J. Stolk, Matthew J. Weaver

We report on a quantum interface linking a diamond NV center quantum network node and 795nm photonic time-bin qubits compatible with Thulium and Rubidium quantum memories. The interface makes use of two-stage low-noise quantum frequency conversion and waveform shaping to match temporal and spectral photon profiles. Two-photon quantum interference shows high

Mahendra Gurve, Sankar Behera, Satyadev Ahlawat, Yamuna Prasad

The rise of Machine Learning as a Service (MLaaS) has led to the widespread deployment of machine learning models trained on diverse datasets. These models are employed for predictive services through APIs, raising concerns about the security and confidentiality of the models due to emerging vulnerabilities in prediction APIs. Of particular concern are model

Sabrina Herbst, Vincenzo De Maio, Ivona Brandic

The increasing capabilities of Machine Learning (ML) models go hand in hand with an immense amount of data and computational power required for training. Therefore, training is usually outsourced into HPC facilities, where we have started to experience limits in scaling conventional HPC hardware, as theorized by Moore's law. Despite heavy parallelization and

Gesine Reinert, Wenkai Xu

Generating graphs that preserve characteristic structures while promoting sample diversity can be challenging, especially when the number of graph observations is small. Here, we tackle the problem of graph generation from only one observed graph. The classical approach of graph generation from parametric models relies on the estimation of parameters, which

Ludmila Leroy, Shih-Wen Huang, Chun-Chien Chiu, Sheng-Zhu Ho

From extreme strain to bending, the possibilities in the manipulation of freestanding films of oxide perovskites bring a novel landscape to their properties and brings them one step closer to their application. It is therefore of great importance to fully understand the inherent properties of such films, in which dimensionality and surface effects can play a

Federico Camia, Yu Feng

It is believed that the large-scale geometric properties of two-dimensional critical percolation are described by a logarithmic conformal field theory, but it has been challenging to exhibit concrete examples of logarithmic singularities and to find an explanation and a physical interpretation, in terms of lattice observables, for their appearance. We show t

Hao Xu, Haipeng Li, Yinqiao Wang, Shuaicheng Liu

Reconstructing 3D hand mesh robustly from a single image is very challenging, due to the lack of diversity in existing real-world datasets. While data synthesis helps relieve the issue, the syn-to-real gap still hinders its usage. In this work, we present HandBooster, a new approach to uplift the data diversity and boost the 3D hand-mesh reconstruction perfo

J. Irving, T. Košir, M. Mastnak

We prove the Box Conjecture for pairs of commuting nilpotent matrices, as formulated by Iarrobino et al [28]. This describes the Jordan type of the dense orbit in the nilpotent commutator of a given nilpotent matrix. Our main tool is the Burge correspondence between the set of all partitions and a set of binary words [15, 16]. For connection with the algebra