October 2024 arXiv papers — page 66

Salvatore Raieli, Nathalie Jeanray, Stéphane Gerart, Sebastien Vachenc

Tabular datasets are widely used in scientific disciplines such as biology. While these disciplines have already adopted AI methods to enhance their findings and analysis, they mainly use tree-based methods due to their interpretability. At the same time, artificial neural networks have been shown to offer superior flexibility and depth for rich and complex

Romain Janodet, Berend van Wachem, Fabian Denner

The stability of most surface-tension-driven interfacial flow simulations is governed by the capillary time-step constraint. This concerns particularly small-scale flows and, more generally, highly-resolved liquid-gas simulations with moderate inertia. To date, the majority of interfacial-flow simulations are performed using an explicit surface-tension treat

Petros Papagiannis, Georgios Pallaris

This study evaluates the effectiveness of incorporating makerspace workshops into computer science education by assessing 21st century skills critical thinking, collaboration, communication, and creativity before and after the intervention. Using a pre test and post test approach with the "21st Century Skills Survey Instrument," the study quantifies the impa

Dean Korošak, Sandra Postić, Andraž Stožer, Boris Podobnik

Calcium signals in pancreatic beta-cells collectives show a sharp transition from uncorrelated to correlated state resembling a phase transition as the slowly increasing glucose concentration crosses the tipping point. However, the exact nature or the order of this phase transition is not well understood. Using confocal microscopy to record the collective ca

Kaiyuan Gu, Chenxin Huang

The universal Poincar\'e torsor, or more generally the universal semi-abelian scheme, can be viewed as a mixed Shimura variety. We give a classification of special subvarieties of the universal semi-abelian scheme of arbitrary toric rank. Given this classification, we show that the Zilber-Pink conjecture for mixed Shimura varieties implies the Zilber-Pink co

Ayush Thakur, Akshat Shrivastav, Rohan Sharma, Triyank Kumar

This research paper presents the development of an AI model utilizing YOLOv8 for real-time weapon detection, aimed at enhancing safety in public spaces such as schools, airports, and public transportation systems. As incidents of violence continue to rise globally, there is an urgent need for effective surveillance technologies that can quickly identify pote

Jaron Skovsted Gundersen, René Bødker Christensen, Markus Grassl, Petar Popovski

Classical coding theory contains several techniques to obtain new codes from other codes, including puncturing and shortening. For quantum codes, a form of puncturing is known, but its description is based on the code space rather than its generators. In this work, we generalize the puncturing procedure to allow more freedom in the choice of which coded stat

D. Edwin, Blesson Mathew, B. Shridharan, Vineeth Valsan

Low-mass emission-line stars belong to various evolutionary stages, from pre-main-sequence young stars to evolved stars. In this work, we present a catalog of late-type (F0 to M9) emission-line stars from the LAMOST Data Release 6. Using the scipy package, we created a Python code that finds the emission peak at H-alpha in all late-type stellar spectra. A da

Yuanting Fan, Chengxu Liu, Nengzhong Yin, Changlong Gao

Diffusion models (DMs) have shown promising results on single-image super-resolution and other image-to-image translation tasks. Benefiting from more computational resources and longer inference times, they are able to yield more realistic images. Existing DMs-based super-resolution methods try to achieve an overall average recovery over all regions via iter

Yousef Yeganeh, Rachmadio Lazuardi, Amir Shamseddin, Emine Dari

Surgical data science (SDS) is a field that analyzes patient data before, during, and after surgery to improve surgical outcomes and skills. However, surgical data is scarce, heterogeneous, and complex, which limits the applicability of existing machine learning methods. In this work, we introduce the novel task of future video generation in laparoscopic sur

Yi-Hsuan Lin

We consider the fractional anisotropic Calder\'on problem for the nonlocal parabolic equation $(\partial_t -\Delta_g)^s u=f$ ($0<s<1$) on closed Riemannian manifolds. More concretely, we can determine the Riemannian manifold $(M,g)$ up to isometry by using the local source-to-solution map in an arbitrarily small open cylinder in the spacetime domain. This ca

Noela Müller, Ralph Neininger, Haodong Zhu

We show that the set of atoms of the limiting empirical marginal distribution in the random $2$-SAT model is $\mathbb Q \cap (0,1)$, for all clause-to-variable densities up to the satisfiability threshold. While for densities up to $1/2$, the measure is purely discrete, we additionally establish the existence of a nontrivial continuous part for any density i

Tao Yu, Zhaonian Zou, Hao Xiong

Index tuning is crucial for optimizing database performance by selecting optimal indexes based on workload. The key to this process lies in an accurate and efficient benefit estimator. Traditional methods relying on what-if tools often suffer from inefficiency and inaccuracy. In contrast, learning-based models provide a promising alternative but face challen

P. Zhou, X. N. Peng, Y. Z. Hu, B. R. Pan

Considering the similarity of the real-space configurations for the opposite spin sublattices in both antiferromagnets (AFM) and altermagnets (AM), the relationship between them should be profound. In this work, we demonstrate that AFM and AM can be connected with spin groups and their subgroups. Consequently, the breaking of the combined inversion or transl

Soohyun Park

Most applications of the hard Lefschetz theorem related to combinatorial properties of simplicial complexes involve their $h$-vectors. In the context of positivity properties involving $h$-vectors of flag spheres, $f$-vectors with a Lefschetz-type ``Boolean'' decomposition have been studied. In this note, we explore families of flag simplicial complexes wher

Pham Truong Xuan

In this paper, we establish a conformal scattering theory for defocusing semilinear wave equations on Schwarzschild spacetime. We combine the energy and pointwise decay results for solutions obtained in \cite{Yang} with a Sobolev embedding on spacelike hypersurfaces to derive two-sided energy estimates between the energy flux of solutions through the Cauchy

Yao Tang, Zhihui Xie, Zichuan Lin, Deheng Ye

Masked prediction has emerged as a promising pretraining paradigm in offline reinforcement learning (RL) due to its versatile masking schemes, enabling flexible inference across various downstream tasks with a unified model. Despite the versatility of masked prediction, it remains unclear how to balance the learning of skills at different levels of complexit

Aymeric Walch

Coherent differentiation was introduced by Ehrhard in order to generalize differential categories to a setting in which the sum is only partially defined, in order to account for the deterministic nature of most models of computation. This internship report proves that the deriving transformation of a differential category with a categorical product always i

Xinyu Jia, Wenxin Wang, Jun Yang, Yongping Pan

Ensuring safety is crucial to promote the application of robot manipulators in open workspaces. Factors such as sensor errors or unpredictable collisions make the environment full of uncertainties. In this work, we investigate these potential safety challenges on redundant robot manipulators, and propose a task-oriented planning and control framework to achi

Zexu Huang, Sarah Monazam Erfani, Siying Lu, Mingming Gong

High-fidelity digital human representations are increasingly in demand in the digital world, particularly for interactive telepresence, AR/VR, 3D graphics, and the rapidly evolving metaverse. Even though they work well in small spaces, conventional methods for reconstructing 3D human motion frequently require the use of expensive hardware and have high proce

Andrzej Miskow, Abdulrahman Altahhan

In this paper, we study the effect of introducing channel and spatial attention mechanisms, namely SEN-Net, ECA-Net, and CBAM, to existing CNN vision-based models such as VGGNet, ResNet, and ResNetV2 to perform the Facial Emotion Recognition task. We show that not only attention can significantly improve the performance of these models but also that combinin

Marlene Lutz, Rochelle Choenni, Markus Strohmaier, Anne Lauscher

Stereotypical bias encoded in language models (LMs) poses a threat to safe language technology, yet our understanding of how bias manifests in the parameters of LMs remains incomplete. We introduce local contrastive editing that enables the localization and editing of a subset of weights in a target model in relation to a reference model. We deploy this appr

Achille Chiuchiarelli, Giacomo Franchini, Francesco Messina, Marcello Chiaberge

The field of autonomous navigation for unmanned ground vehicles (UGVs) is in continuous growth and increasing levels of autonomy have been reached in the last few years. However, the task becomes more challenging when the focus is on the exploration of planet surfaces such as Mars. In those situations, UGVs are forced to navigate through unstable and rugged

Dan Crisan, Martin Clark

This paper studies the identification of an $\mathbb{R}^d$-valued diffusion $X$ when a running function of it, say $h(X_t)$, is observed. A point-wise observation of the process (in other words, observing $h(X_t)$ in isolation) cannot identify $X_t$ unless the $h$ is injective. However observing $h(X_s)$ on a small interval $[t,t+\varepsilon]$ can be enough

Nishat Raihan, Joanna C. S. Santos, Marcos Zampieri

The recently introduced Mojo programming language (PL) by Modular, has received significant attention in the scientific community due to its claimed significant speed boost over Python. Despite advancements in code Large Language Models (LLMs) across various PLs, Mojo remains unexplored in this context. To address this gap, we introduce MojoBench, the first

Ach. Khozaimi, Wayan Firdaus Mahmudy

The Pap smear is a screening method for early cervical cancer diagnosis. The selection of the right optimizer in the convolutional neural network (CNN) model is key to the success of the CNN in image classification, including the classification of cervical cancer Pap smear images. In this study, stochastic gradient descent (SGD), RMSprop, Adam, AdaGrad, AdaD

Xiguang Li, Jiafu Chen, Yunhe Sun, Na Lin

With the rapid advancement of autonomous driving technology, efficient and accurate object detection capabilities have become crucial factors in ensuring the safety and reliability of autonomous driving systems. However, in low-visibility environments such as hazy conditions, the performance of traditional object detection algorithms often degrades significa

T. Vasina, D. Aoki, A. Miyake, G. Seyfarth

The existence of multiple superconducting phases induced by either pressure or magnetic field is one of the most striking features of superconductivity of UTe$_2$, among the many unusual superconducting properties of this system. Here we report thermodynamic measurements of the superconducting phase diagram combining pressure and magnetic fields up to 30 T.

Deepak Narayan Gadde, Aman Kumar, Djones Lettnin, Sebastian Simon

Ever-increasing design complexity of System-on-Chips (SoCs) led to significant verification challenges. Unlike software, bugs in hardware design are vigorous and eternal i.e., once the hardware is fabricated, it cannot be repaired with any patch. Despite being one of the powerful techniques used in verification, the dynamic random approach cannot give confid

Jacob Williams, Matthew Edwards, Joseph Gardiner

The convergence of information and operational technology networks has created previously unforeseen security issues. To address these issues, both researchers and practitioners have integrated threat intelligence methods into the security operations of converged networks, with some of the most valuable tools being honeypots that imitate industrial control s

Maxime Cazaux

We compute the genus-0 permutation-equivariant quantum K-theory of Fermat singularities, in parallel with the Givental-Lee theory for projective varieties. We extend Givental-Tonita's formalism of adelic Lagrangian cones to the singularity theory, and we obtain explicit $I$-functions for the invariants, which satisfy the same $q$-difference equation as Given

Peter Mathé, Bernd Hofmann

The difficulty for solving ill-posed linear operator equations in Hilbert space is reflected by the strength of ill-posedness of the governing operator, and the inherent solution smoothness. In this study we focus on the ill-posedness of the operator, and we propose a partial ordering for the class of all bounded linear operators which lead to ill-posed oper

Alexandru-Iulius Jerpelea, Alina Rădoi, Sergiu Nisioi

This paper presents the process of building a neural machine translation system with support for English, Romanian, and Aromanian - an endangered Eastern Romance language. The primary contribution of this research is twofold: (1) the creation of the most extensive Aromanian-Romanian parallel corpus to date, consisting of 79,000 sentence pairs, and (2) the de

Nilanjana Kumar, Gaadha Lekshmi

Boosted dark matter constitutes a small fraction of the total dark matter in the Universe, with mass ranging from eV to MeV and often exhibiting (semi)relativistic velocity. Hence the likelihood of detecting boosted dark matter in Earth-based direct detection experiments is relatively high. There is more than one explanation for the origin of the boosted dar

Tristan Bozec, Damien Calaque, Sarah Scherotzke

We construct symmetric monoidal higher categories of iterated Calabi-Yau cospans, that are noncommutative analogs of iterated lagrangian correspondences. We actually give a general (and functorial) procedure that applies to iterated nondegenerate cospans on certain comma categories. This allows us to factor the AKSZ fully extended TFT associated with the mod

Rahima Khanam, Muhammad Hussain

This study presents an architectural analysis of YOLOv11, the latest iteration in the YOLO (You Only Look Once) series of object detection models. We examine the models architectural innovations, including the introduction of the C3k2 (Cross Stage Partial with kernel size 2) block, SPPF (Spatial Pyramid Pooling - Fast), and C2PSA (Convolutional block with Pa

Sirio Resteghini

Given a Coxeter system with a fixed Coxeter element, there is a surjective group morphism $\Psi$ from the standard to the dual Artin groups. We give conditions that are sufficient, necessary or equivalent to $\Psi$ being an isomorphism. In particular, we prove that if the Hurwitz action on the reduced words of any element in the noncrossing partition poset i

Jean-Marc Drézet

A primitive multiple scheme is a Cohen-Macaulay scheme $\bf X$ such that the associated reduced scheme $X={\bf X}_{red}$ is smooth, irreducible, and that $\bf X$ can be locally embedded in a smooth variety of dimension $\dim(X)+1$. If ${\bf I}_X$ is the ideal sheaf of $X$, $L={\bf I}_X/{\bf I}_X^2$ is a line bundle on $X$, called the associated line bundle o

Siegfried Beckus, Jean Bellissard, Yannik Thomas

We study the Kohmoto model including Sturmian Hamiltonians and the associated Kohmoto butterfly. We prove spectral estimates for the operators using Farey numbers. In addition, we determine the impurities at rational rotations leading to the spectral defects in the Kohmoto butterfly. Our results are similar to the ones obtained for the Almost-Mathieu operato

Rong-Gen Cai, Shao-Jiang Wang, Zi-Yan Yuwen, Xiang-Xi Zeng

Recent reports of stochastic gravitational wave background from four independent pulsar-timing-array collaborations have renewed the interest in the cosmological gravitational wave background (CGWB), which is expected to open a new window into the early Universe. Although the early Universe is supposed to be extremely flat from an inflationary point of view,

Anna Fancelli, R. Flores-Calderón, Owen Benton, Bella Lake

Motivated by the recent appearance of the trillium lattice in the search for materials hosting spin liquids, we study the ground state of the classical Heisenberg model on its linegraph, the trilline lattice. We find that this network realises the recently proposed notion of a fragile spin liquid in three dimensions. Additionally, we analyze the Ising case a

Klaus Deckelnick, Robert Nürnberg

The paper addresses the numerical approximation of two variants of hyperbolic mean curvature flow of surfaces in $\mathbb R^3$. For each evolution law we propose both a finite element method, as well as a finite difference scheme in the case of axially symmetric surfaces. We present a number of numerical simulations, including convergence tests as well as si

Zhenhuan Liu, Weiyuan Gong, Zhenyu Du, Zhenyu Cai

In quantum learning tasks, quantum memory can offer exponential reductions in statistical complexity compared to any single-copy strategies, but this typically necessitates at least doubling the system size. We show that such exponential reductions can also be achieved by having access to the purification of the target mixed state. Specifically, for a low-ra

Benjamin Bennetzen, Daniel Vang Kleist, Emilie Sonne Steinmann, Loke Walsted

This paper presents the syntax and reduction rules for an abstract machine based on the JavaScript XML language. We incorporate the notion of cost into our reduction rules, and create a type system that over-approximate this cost. This over-approximation results in an equation that may contain unknowns originating from while loops. We conclude with a formal

Benjamin Bennetzen, Daniel Vang Kleist, Emilie Sonne Steinmann, Loke Walsted

Protecting confidential data from leaking is a critical challenge in computer systems, particularly given the growing number of observers on the internet. Therefore, limiting information flow using robust security policies becomes increasingly vital. We focus on the non-interference policy, where the goal is to ensure that confidential data can not impact pu

Yuting Tian, Jianhua Tu

Let $MIS(G)$ be the set of all maximal independent sets in a graph $G$, and let $mis(G)=|MIS(G)|$. In this paper, we show that for any tree $T$ with $n$ vertices and independence number $\alpha$, \[mis(T)\geq f(n-\alpha),\] and for any unicyclic graph $G$ with $n$ vertices and independence number $\alpha$, \begin{align*} mis(G)\geq \begin{cases} 2, & \text{i

Sven Kiefer, Nanna Bach-Møller, Dominic Samra, David A. Lewis

Warm Saturn type exoplanets orbiting M-dwarfs are particularly suitable for in-depth cloud characterisation through transmission spectroscopy due to their favourable stellar to planetary radius contrast. However, modelling cloud formation consistently within the 3D atmosphere remains computationally challenging. The aim is to explore the combined atmospheric

Elif Ceren Gok Yildirim, Murat Onur Yildirim, Joaquin Vanschoren

Continual Learning (CL) methods usually learn from all available data. However, this is not the case in human cognition which efficiently focuses on key experiences while disregarding the redundant information. Similarly, not all data points in a dataset have equal potential; some can be more informative than others. This disparity may significantly impact t

Xintong Wang, Jingheng Pan, Liang Ding, Longyue Wang

Large Language Models (LLMs) achieve remarkable performance through pretraining on extensive data. This enables efficient adaptation to diverse downstream tasks. However, the lack of interpretability in their underlying mechanisms limits the ability to effectively steer LLMs for specific applications. In this work, we investigate the intrinsic mechanisms of

Thierry Désiré Pomar, Tristan Steegemans, Sreejith Kumar, Rasmus Bjørk

Magnetometers based on the extraordinary magnetoresistance (EMR) effect are promising for applications which demand high sensitivity combined with room temperature operation but their application for magnetic field sensing requires further optimization. A key challenge is to obtain Ohmic metal/semiconductor contacts with low contact resistances in EMR device

Do Young Kim, Kyunghyun Kim, Gyeongseop Lee, Niloy Das

Solar vehicles, which simultaneously produce and consume energy, require meticulous energy management. However, potential users often feel uncertain about their operation compared to conventional vehicles. This study presents a simulator designed to help users understand long-distance travel in solar vehicles and recognize the importance of proper energy man

Yixin Ji, Yang Xiang, Juntao Li, Qingrong Xia

As large language models (LLMs) are widely applied across various fields, model compression has become increasingly crucial for reducing costs and improving inference efficiency. Post-training pruning is a promising method that does not require resource-intensive iterative training and only needs a small amount of calibration data to assess the importance of

Ya. S. Greenberg. O. A. Chuikin, A. G. Moiseev, A. A. Shtygashev

We present a time-dependent quantum calculations of the first order and second order photon correlation functions for the scattering of a single-photon pulse on a two-level atom (qubit) embedded in a one-dimensional open waveguide. Within Markov approximation we find the analytic expression for the quantum operator of positive frequency electric field. We re

Chaoyun Zhang, Randolph Yao, Si Qin, Ze Li

The presence of unhealthy nodes in cloud infrastructure signals the potential failure of machines, which can significantly impact the availability and reliability of cloud services, resulting in negative customer experiences. Effectively addressing unhealthy node mitigation is therefore vital for sustaining cloud system performance. This paper introduces Deo

Ali Saadat, Jacques Fellay

Genetic diseases can be classified according to their modes of inheritance and their underlying molecular mechanisms. Autosomal dominant disorders often result from DNA variants that cause loss-of-function, gain-of-function, or dominant-negative effects, while autosomal recessive diseases are primarily linked to loss-of-function variants. In this study, we i

Akihiro Inoue, Ken Ohsuga, Hiroyuki R. Takahashi, Yuta Asahina

Although ultraluminous X-ray pulsars (ULXPs) are believed to be powered by super-Eddington accretion onto a magnetized neutron star (NS), the detailed structures of the inflow-outflow and magnetic fields are still not well understood. We perform general relativistic radiation magnetohydrodynamics (GR-RMHD) simulations of super-Eddington accretion flows onto

Yuan Shen, Jérémy O'Byrne, Andreas Schoenit, Ananyo Maitra

The collective motion of epithelial cells is a fundamental biological process which plays a significant role in embryogenesis, wound healing and tumor metastasis. While it has been broadly investigated for over a decade both in vivo and in vitro, large scale coherent flocking phases remain underexplored and have so far been mostly described as fluid. In this

Andrei Constantin, Kit Fraser-Taliente, Thomas R. Harvey, Lucas T. Y. Leung

We study a class of supersymmetric Froggatt-Nielsen (FN) models with multiple U(1) symmetries and Standard Model (SM) singlets inspired by heterotic string compactifications on Calabi-Yau threefolds. The string-theoretic origin imposes a particular charge pattern on the SM fields and FN singlets, dividing the latter into perturbative and non-perturbative typ

Arvid Siqveland

We give a definition of associative schemes, schemes of associative rings, over a field $k,$ using the definition of completion of an associative $k$-algebra in a finite set of simple modules. We start by giving a weaker but sufficient definition of ordinary schemes of commutative rings which can be generalized to associative rings.

Adrià Labay-Mora, Jorge García-Beni, Gian Luca Giorgi, Miguel C. Soriano

Quantum optical networks are instrumental to address fundamental questions and enable applications ranging from communication to computation and, more recently, machine learning. In particular, photonic artificial neural networks offer the opportunity to exploit the advantages of both classical and quantum optics. Photonic neuro-inspired computation and mach

Y. Yu, Y. M. Xing, Y. H. Zhang, M. Wang

Using the B$\rho$-defined isochronous mass spectrometry technique, we report the first determination of the $^{23}$Si, $^{26}$P, $^{27}$S, and $^{31}$Ar masses and improve the precision of the $^{28}$S mass by a factor of 11. Our measurements confirm that these isotopes are bound and fix the location of the proton dripline in P, S, and Ar. We find that the m

Ying Li, Zhidi Lin, Yuhao Liu, Michael Minyi Zhang

Random feature latent variable models (RFLVMs) represent the state-of-the-art in latent variable models, capable of handling non-Gaussian likelihoods and effectively uncovering patterns in high-dimensional data. However, their heavy reliance on Monte Carlo sampling results in scalability issues which makes it difficult to use these models for datasets with a

S. Orlando, E. Greco, R. Hirai, T. Matsuoka

We investigate SN 2014C using three-dimensional hydrodynamic modeling, focusing on its early interaction with dense circumstellar medium (CSM). Our objective is to uncover the pre-supernova (SN) CSM structure and constrain the progenitor star's mass-loss history prior to core collapse. Our comprehensive model traces the evolution from the progenitor star thr

Sabine Bellstedt, Aaron S. G. Robotham

We use a volume-complete sample of ~8,000 galaxies from the GAMA survey to characterise the impact of stellar population libraries (SPLs) and model configurations on the resulting inferred galaxy properties from Spectral Energy Distribution (SED) fitting. We compare a fiducial SPL from ProGeny (a new tool that can generate SPLs quickly and flexibly) against

A. S. G. Robotham, S. Bellstedt

In this work we introduce ProGeny, a new stellar population library (SPL) software package written in R. This release encapsulates the core software (github.com/asgr/ProGeny) to generate simple/single stellar populations and their associated spectra (SSPs); the various data inputs required (in particular isochrones and stellar atmospheres); example scripts t

Alessandro Londei, Matteo Benati, Denise Lanzieri, Vittorio Loreto

Incorporating novelties into deep learning systems remains a challenging problem. Introducing new information to a machine learning system can interfere with previously stored data and potentially alter the global model paradigm, especially when dealing with non-stationary sources. In such cases, traditional approaches based on validation error minimization

Dongwen Luo

Power grid load scheduling is a critical task that ensures the balance between electricity generation and consumption while minimizing operational costs and maintaining grid stability. Traditional optimization methods often struggle with the dynamic and stochastic nature of power systems, especially when faced with renewable energy sources and fluctuating de

Ajith Balu, Kinjal Roy, Hemanth Manikantan, Abhisek Tamang

Centaurus X-3 is a persistent high-mass X-ray binary with the long-term light curve from the source exhibiting orbit-to-orbit intensity variations with no apparent superorbital periodicity. We used $\sim$13.5 years of MAXI/GSC data to study the long-term behaviour of X-ray absorption caused by the stellar wind from the companion star and any absorbing struct

Ziyang Chen, Xiaobin Wang, Yong Jiang, Jinzhi Liao

Question Answering (QA) systems face challenges in handling complex questions that require multi-domain knowledge synthesis. The naive RAG models, although effective in information retrieval, struggle with complex questions that require comprehensive and in-depth answers. The pioneering task is defined as explanatory answer generation, which entails handling

Laura Polimeno, Francesco Todisco, Rosanna Mastria, Milena De Giorgi

Transition-metal dichalcogenides monolayers exhibit strong exciton resonances that enable intense light-matter interactions at room temperature (RT). However, the sensitivity of these materials to the surrounding environment and their intense interactions with the sustaining substrate result in the enhancement of excitonic losses through scattering, dissocia

Edwin Fong, Andrew Yiu

The martingale posterior framework is a generalization of Bayesian inference where one elicits a sequence of one-step ahead predictive densities instead of the likelihood and prior. Posterior sampling then involves the imputation of unseen observables, and can then be carried out in an expedient and parallelizable manner using predictive resampling without r

Yujia Li, Han Li, ans S. Kevin Zhou

Clinical decision-making relies heavily on causal reasoning and longitudinal analysis. For example, for a patient with Alzheimer's disease (AD), how will the brain grey matter atrophy in a year if intervened on the A-beta level in cerebrospinal fluid? The answer is fundamental to diagnosis and follow-up treatment. However, this kind of inquiry involves count

Adam Casselman, Abraham P. Vinod, Sarah H. Q. Li

We optimize finite horizon multi-agent reach-avoid Markov decision process (MDP) via \emph{local feedback policies}. The global feedback policy solution yields global optimality but its communication complexity, memory usage and computation complexity scale exponentially with the number of agents. We mitigate this exponential dependency by restricting the so

Philipp Hehnle, Manfred Reichert

Different organisations often run similar digitised business processes to achieve their business goals. However, organisations often need to slightly adapt the business processes implemented in an information system in order to adopt them. Various approaches have been proposed to manage variants in process models. While these approaches mainly deal with cont

Tullio Ceccherini-Silberstein, Michel Coornaert, Xuan Kien Phung

We introduce the class of strongly sofic monoids. This class of monoids strictly contains the class of sofic groups and is a proper subclass of the class of sofic monoids. We define and investigate sofic topological entropy for actions of strongly sofic monoids on compact spaces. We show that sofic topological entropy is a topological conjugacy invariant for

Shoya Ohsumi, Yoshiki J. Sato, Ryuji Okazaki

Materials with axis-dependent conduction polarity are known as $p\times n$-type or goniopolar conductors that can be used for transverse thermoelectric devices, allowing the longitudinal thermal current to be converted into the transverse electrical current. Here, we performed experimental and computational studies on the transport properties of WSi$_2$ sing

Chen Chen, Xiaoyang He, Qizhen Xiong, Chuye Quan

Altermagnetism exhibits advantages over both ferromagnetic and antiferromagnetic counterparts by enabling spin splitting within antiferromagnetic materials. Currently, it is established that valley polarization in altermagnetism remains largely insensitive to spin-orbit coupling and spin. Here, using Cr$_2$S$_2$ as a case study, we investigate the mechanism

Ahmed H. Elsayed, Andrej Lejman, Frederic Stahl

Artificial Water Bodies (AWBs) are human-made and require continuous monitoring due to their artificial biological processes. These systems necessitate regular maintenance to manage their ecosystems effectively. Unmanned Surface Vehicle (USV) offers a collaborative approach for monitoring these environments, working alongside human operators such as boat ski

T. Mukherjee, T. Zafar, T. Nanayakkara, A. Gupta

We present spectroscopic properties of 22 Lyman-alpha emitters(LAEs) at z=5.5-6.6 with Lyman-alpha(Lya) luminosity log($L_{Lya}$[$ergs^{-1}$])=42.4-43.5, obtained using VLT/MUSE as part of the Middle Ages Galaxy Properties with Integral Field Spectroscopy(MAGPI) survey. Additionally, we incorporate broad-band photometric data from the Subaru Hyper Suprime-Ca

Oleksiy Arkhypov

The similarity of Mercury to the Moon raises the question on mercurian analogues of lunar transient phenomena. However, since the mid-1960s, this topic has remained out of attention. Nevertheless, the discoveries of the 21st century and the BepiColombo mission give hope for the registration of Mercury transient phenomena. In this regard, it is shown that the

Giovanni Canepa

We consider injectivity and surjectivity of some maps on the exterior algebra of isomorphic finite-dimensional vector spaces. We prove the properties of the maps in full generality, for any dimension of the vector space and any subspace. We also draw a connection with the Palatini-Cartan formulation of General Relativity, for which these maps are of crucial

Ryan L. Acosta Babb

It is known that the Bessel--Fourier coefficients $f_m$ of a function $f$ such that $\sqrt{x}f(x)$ is integrable over $[0,1]$ satisfy $f_m/\sqrt{m}\to 0$. We show a partial converse, namely that for $0\leq \alpha<1/2$ and any non-negative $a_m\to 0$, there is a function $f$ such that $x^{\alpha+1}f(x)$ is integrable and its Bessel--Fourier coefficients $f_m$

Catalina García García, Román Salmerón Gómez, Claudia García García

The residualization procedure has been applied in many different fields to estimate models with multicollinearity. However, there exists a lack of understanding of this methodology and some authors discourage its use. This paper aims to contribute to a better understanding of the residualization procedure to promote an adequate application and interpretation

Salar Jabbary Farrokhi, Aaron D. Ratschow, Steffen Hardt

We experimentally study the breakup of water-glycerol liquid bridges on non-conductive surfaces and find that spontaneous charge deposition at the receding contact line, slide electrification, can have a substantial influence. Electrostatic forces slow down the dynamics during, and cause spontaneous motion of satellite drops after the bridge breakup. We show

Nicholas Crawford, Vesna Iršič Chenoweth

A generalization of hyperopic cops and robber, analogous to the $k$-visibility cops and robber, is introduced in this paper. For a positive integer $k$ the $k$-hyperopic game of cops and robber is defined similarly as the usual cops and robber game, but with the robber being omniscient and invisible to the cops that are at distance at most $k$ away from the

Gerrit Schierholz

Starting from the running coupling in the gradient flow scheme, the QCD Lambda parameter $\Lambda_{\,\overline{\!\rm MS\!}\;}$ is determined analytically with respect to the reference scale $w_0$ in the pure gauge theory. A key element is the gluon condensate, which, being invariant under RG transformations, establishes a formal relationship between $\Lambda

Clara Meister, Mario Giulianelli, Tiago Pimentel

Surprisal theory posits that the cognitive effort required to comprehend a word is determined by its contextual predictability, quantified as surprisal. Traditionally, surprisal theory treats words as distinct entities, overlooking any potential similarity between them. Giulianelli et al. (2023) address this limitation by introducing information value, a mea

Nore Stolte, János Daru, Harald Forbert, Jörg Behler

Isotopic substitution, which can be realized both in experiment and computer simulations, is a direct approach to assess the role of nuclear quantum effects on the structure and dynamics of matter. Yet, the impact of nuclear quantum effects on the structure of liquid water as probed in experiment by comparing normal to heavy water has remained controversial.

Gee-Choon Lau, Wai Chee Shiu

It is known that null graphs and 1-regular graphs are the only regular graphs without local antimagic chromatic number. In this paper, we proved that the join of 1-regular graph and a null graph has local antimagic chromatic number is 3. Consequently, we also obtained many families of (possibly disconnected or regular) bipartite and tripartite graph with loc

Jan-Henrik Steg

This paper studies oligopolistic irreversible investment with closed-loop strategies. These permit fully dynamic interactions that result in much richer strategic behavior than previous studies with open-loop strategies allow. The tradeoff between preemption incentives and the option value of waiting becomes distinctly visible. Strategies that depend on pres

Hao-Yue Zhang, Yi-Xuan Yao, Bin-Yao Huang, Jing-Yi-Ran Jin

Two-dimensional coherent spectroscopy (2DCS) offers significant advantages in terms of high temporal and frequency resolutions and signal-to-noise ratio. Until now, the response-function (RF) formalism has been the prevalent theoretical description. In this study, we compare the non-Hermitian Hamiltonian (NHH) method with the RF formalism in a three-level sy

Diego R Villacreses Naranjo, Frédéric Vignat, Nicolas Béraud

Despite being the subject of study for several years, excessive vibration persists in the machining of metal parts. In this context, the Stability Lobe Diagram (SLD) is presented as a viable tool to mitigate this problem as a function of axial depth of cut and spindle speed. However, its accurate construction is subject to the consideration of multiple param

Xiong Yao, Hee Taek Yi, Deepti Jain, Xiaoyu Yuan

Since the discovery of superconductivity in the Fe(Te,Se) system, it has been a general consensus that the end member of FeTe is not superconducting. Nonetheless, in recent years, there have been reports of superconducting FeTe films, but the origin of their superconductivity remains mysterious. Here, we provide the first comprehensive review of all the repo

Mengying Wang, Andreas Spitz

Writing assistants and large language models see widespread use in the creation of text content. While their effectiveness for individual users has been evaluated in the literature, little is known about their proclivity to change language or reduce its richness when adopted by a large user base. In this paper, we take a first step towards quantifying this r

Ran Wang, Song-Bo Zhang, Ning Hao

In systems with unconventional Rashba bands, we propose that a finite-momentum pairing state can emerge without the need for an external magnetic field. We analyze the phase transition from a zero-momentum Bardeen-Cooper-Schrieffer (BCS) state to a finite-momentum pairing state using a microscopic interaction model. We demonstrate that the coexistence of zer

Pingzhi Yuan

In this paper, we propose a new algebraic structure of permutation polynomials over $\mathbb{F}_{q^n}$. As an application of this new algebraic structure, we give some classes of new PPs over $\mathbb{F}_{q^n}$ and answer an open problem in Charpin and Kyureghyan.

Fritz Grimpen, Anastasios Stefanou

Flat-injective presentations were introduced by Miller (2020) to provide combinatorial descriptions of $\mathbb Z^n$-graded modules. We consider them in the setting of local graded rings $R$, with grading over an abelian group, and give a criterion for minimality of them. In the special case of the polynomial ring, this criterion reduces to a family of $k$-l

L. Q. Lai

We investigate the dynamics of a Bose-Einstein condensate in a one-dimensional ring-shaped lattice with the Peierls phase and site-dependent modulations, where the condensate is confined in a single deep trap and the interparticle interaction strength is modulated by a time-periodic driving field. The system has a finite spectrum, which limits the excitation

Surya N. Panda, Qun Yang, Darius Pohl, Hua Lv

The rise of non-magnetic topological semimetals, which provide a promising platform for observing and controlling various spin-orbit effects, has led to significant advancements in the field of topological spintronics. RhSi exists in two distinct polymorphs: cubic and orthorhombic crystal structures. The noncentrosymmetric B20 cubic structure has been extens

Paul Friedrich, Yannik Frisch, Philippe C. Cattin

Deep generative modeling has emerged as a powerful tool for synthesizing realistic medical images, driving advances in medical image analysis, disease diagnosis, and treatment planning. This chapter explores various deep generative models for 3D medical image synthesis, with a focus on Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs),