March 2023 arXiv papers — page 104

Vincent Delecroix, Matthijs Ebbens, Francis Lazarus, Ivan Yakovlev

Consider a weighted, undirected graph cellularly embedded on a topological surface. The function assigning to each free homotopy class of closed curves the length of a shortest cycle within this homotopy class is called the marked length spectrum. The (unmarked) length spectrum is obtained by just listing the length values of the marked length spectrum in in

Alessio Colucci, Andreas Steininger, Muhammad Shafique

Deep Learning (DL) systems have proliferated in many applications, requiring specialized hardware accelerators and chips. In the nano-era, devices have become increasingly more susceptible to permanent and transient faults. Therefore, we need an efficient methodology for analyzing the resilience of advanced DL systems against such faults, and understand how

Alexandre Anahory Simoes, David Martín de Diego, Bernhard Maschke

In this paper we introduce discrete gradient methods to discretize irreversible port-Hamiltonian systems showing that the main qualitative properties of the continuous system are preserved using this kind discretizations methods.

Piotr Przybyła, Alexander Shvets, Horacio Saggion

Text classification methods have been widely investigated as a way to detect content of low credibility: fake news, social media bots, propaganda, etc. Quite accurate models (likely based on deep neural networks) help in moderating public electronic platforms and often cause content creators to face rejection of their submissions or removal of already publis

Qianqian Qi, David J. Hessen, Peter G. M. van der Heijden

Both latent semantic analysis (LSA) and correspondence analysis (CA) are dimensionality reduction techniques that use singular value decomposition (SVD) for information retrieval. Theoretically, the results of LSA display both the association between documents and terms, and marginal effects; in comparison, CA only focuses on the associations between documen

Jianjian Yin, Zhichao Zheng, Yanhui Gu, Junsheng Zhou

Existing approaches focus on using class-level features to improve semantic segmentation performance. How to characterize the relationships of intra-class pixels and inter-class pixels is the key to extract the discriminative representative class-level features. In this paper, we introduce for the first time to describe intra-class variations by multiple dis

Jinchao Li, Xixin Wu, Kaitao Song, Dongsheng Li

As a common way of emotion signaling via non-linguistic vocalizations, vocal burst (VB) plays an important role in daily social interaction. Understanding and modeling human vocal bursts are indispensable for developing robust and general artificial intelligence. Exploring computational approaches for understanding vocal bursts is attracting increasing resea

Amirhossein Hajavi, Ali Etemad

With the ubiquity of smart devices that use speaker recognition (SR) systems as a means of authenticating individuals and personalizing their services, fairness of SR systems has becomes an important point of focus. In this paper we study the notion of fairness in recent SR systems based on 3 popular and relevant definitions, namely Statistical Parity, Equal

Giovanni Catino, Paolo Mastrolia, Dario D. Monticelli

In this paper we prove a new rigidity results for complete, possibly non-compact, critical metrics of the quadratic curvature functional $\mathfrak{S}^2 = \int R_g^{2} dV_g$: we show that critical metrics $(M^n, g)$ with finite energy are always scalar flat, i.e. global minima, provided $n\geq 10$.

Olof Nebrin, Sambit K. Giri, Garrelt Mellema

The first stars, galaxies, star clusters, and direct-collapse black holes are expected to have formed in low-mass ($\sim$$10^{5}-10^{9} ~ M_{\odot}$) haloes at Cosmic Dawn ($z \sim 10 - 30$) under conditions of efficient gas cooling, leading to gas collapse towards the centre of the halo. The halo mass cooling threshold has been analyzed by several authors u

Joris Bierkens, Sebastiano Grazzi, Gareth Roberts, Moritz Schauer

We extend Monte Carlo samplers based on piecewise deterministic Markov processes (PDMP samplers) by formally defining different boundary conditions such as sticky floors, soft and hard walls and teleportation portals. This allows PDMP samplers to target measures with piecewise-smooth densities relative to mixtures of Dirac and continuous components and measu

Mai A. Shaaban, Mariam Kashkash, Maryam Alghfeli, Adham Ibrahim

One of the main challenges in the field of deep learning is obtaining the optimal model hyperparameters. The search for optimal hyperparameters usually hinders the progress of solutions to real-world problems such as healthcare. Previous solutions have been proposed, but they can still get stuck in local optima. To overcome this hurdle, we propose OptBA to a

K. Atalikov, A. Zotov

In this paper we study 1+1 field generalization of the rational $N$-body Calogero-Moser model. We show that this model is gauge equivalent to some special higher rank matrix Landau-Lifshitz equation. The latter equation is described in terms of ${\rm GL}_N$ rational $R$-matrix, which turns into the 11-vertex $R$-matrix in the $N=2$ case. The rational $R$-mat

Jinchao Li, Kaitao Song, Junan Li, Bo Zheng

With the global population aging rapidly, Alzheimer's disease (AD) is particularly prominent in older adults, which has an insidious onset and leads to a gradual, irreversible deterioration in cognitive domains (memory, communication, etc.). Speech-based AD detection opens up the possibility of widespread screening and timely disease intervention. Recent adv

Christo Kurisummoottil Thomas, Walid Saad

Future wireless services, such as the metaverse require high information rate, reliability, and low latency. Multi-user wireless systems can meet such requirements by utilizing the abundant terahertz bandwidth with a massive number of antennas, creating narrow beamforming solutions. However, existing solutions lack proper modeling of channel dynamics, result

Harold C. Steinacker

A detailed derivation of $3+1$ dimensional induced or emergent gravity in the IKKT matrix model at one loop is given, as announced in [1]. The mechanism requires a brane configuration with structure ${\cal M}^{3,1}\times {\cal K} \subset {\mathbb R}^{9,1}$, where ${\cal M}^{3,1}$ is the noncommutative space-time brane, and ${\cal K}$ are compact fuzzy extra

Guoxuan Xia, Christos-Savvas Bouganis

Deep Ensembles are a simple, reliable, and effective method of improving both the predictive performance and uncertainty estimates of deep learning approaches. However, they are widely criticised as being computationally expensive, due to the need to deploy multiple independent models. Recent work has challenged this view, showing that for predictive accurac

Fabio Chiarello, Roberto Leoni, Francesco Martini, Francesco Mattioli

Integrated arrays of Superconducting Nanowire Single Photon Detectors (SNSPDs) have shown capabilities such as Photon Number Resolution, single photon imaging and coincidences detection, and can be effectively used also in other different applications related to quantum optics. The growing complexity of such applications requires the use of multiplexing sche

Na Li, Ye Xing, Xiao-Hui Hu

We study the masses and production modes of pentaquark with the quark constituent $c\bar qqqq$, by the tridiquark-diquark model and systematical light flavor quark symmetry SU(3) analysis. The mass splittings show that the S-wave singly charm pentaquark $c\bar udds$, $c\bar dusu$, $c\bar sudu$, and $c\bar sudd$ are below their strong decay thresholds, while

Julian Eggert, Tim Puphal

In this paper, we compare three different model-based risk measures by evaluating their stengths and weaknesses qualitatively and testing them quantitatively on a set of real longitudinal and intersection scenarios. We start with the traditional heuristic Time-To-Collision (TTC), which we extend towards 2D operation and non-crash cases to retrieve the Time-T

Darius Petermann, Inseon Jang, Minje Kim

Spectral sub-bands do not portray the same perceptual relevance. In audio coding, it is therefore desirable to have independent control over each of the constituent bands so that bitrate assignment and signal reconstruction can be achieved efficiently. In this work, we present a novel neural audio coding network that natively supports a multi-band coding par

Vishal Parmar, Manoj K Sharma, S K Patra

The effective field theory motivated relativistic mean-field (E-RMF) formalism is employed to study the equation of state (EoS) for the infinite symmetric nuclear matter at finite temperature using the recently developed forces FSUGarnet, IOPB-I, G3, and the well known NL3 force parameter. The EoS is then used to estimate the critical temperature $T_c$, pres

Lukas Trümper, Tal Ben-Nun, Philipp Schaad, Alexandru Calotoiu

Performance optimization is an increasingly challenging but often repetitive task. While each platform has its quirks, the underlying code transformations rely on data movement and computational characteristics that recur across applications. This paper proposes to leverage those similarities by constructing an embedding space for subprograms. The continuous

Jikun Kang, Di Wu, Ju Wang, Ekram Hossain

In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs. To address this problem, BSs can work collaboratively to deliver a smooth migration (or handoff) and satisfy the UEs' service requirements. This paper formulates the load balancing problem as a Markov game and prop

P. Z. Sun, W. Q. Xiong, A. Bera, I. Timokhin

Graphite is one of the most chemically inert materials. Its elementary constituent, monolayer graphene, is generally expected to inherit most of the parent material's properties including chemical inertness. Here we show that, unlike graphite, defect-free monolayer graphene exhibits a strong activity with respect to splitting molecular hydrogen, which is com

Jialiang Zhao, Maria Bauza, Edward H. Adelson

In this paper, we address the problem of using visuo-tactile feedback for 6-DoF localization and 3D reconstruction of unknown in-hand objects. We propose FingerSLAM, a closed-loop factor graph-based pose estimator that combines local tactile sensing at finger-tip and global vision sensing from a wrist-mount camera. FingerSLAM is constructed with two constitu

Mao Fabrice Djete, Gaoyue Guo, Nizar Touzi

We introduce the possibility of default in the mean field game of mutual holding of Djete and Touzi [11]. This is modeled by introducing absorption at the origin of the equity process. We provide an explicit solution of this mean field game. Moreover, we provide a particle system approximation, and we derive an autonomous equation for the time evolution of t

Nico Reski, Aris Alissandrakis, Andreas Kerren

The design of intuitive three-dimensional user interfaces is vital for interaction in virtual reality, allowing to effectively close the loop between a human user and the virtual environment. The utilization of 3D gestural input allows for useful hand interaction with virtual content by directly grasping visible objects, or through invisible gestural command

Johan Kon, Naomi de Vos, Dennis Bruijnen, Jeroen van de Wijdeven

Tracking performance of physical-model-based feedforward control for interventional X-ray systems is limited by hard-to-model parasitic nonlinear dynamics, such as cable forces and nonlinear friction. In this paper, these nonlinear dynamics are compensated using a physics-guided neural network (PGNN), consisting of a physical model, embedding prior knowledge

Remko Fermin, Junxiang Yao, Kaveh Lahabi, Jan Aarts

The phenomenon of s-wave spin triplet Cooper pairs induced in ferromagnetic metals has been researched now for more than a decade, and its main aspects are well understood. Crucial in converting s-wave singlet pairs in the superconductor to s-wave triplets in the ferromagnet is the engineering of well-defined magnetic inhomogeneity (the 'generator') at the i

Yiming Tan, Dehai Min, Yu Li, Wenbo Li

ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge. Therefore, there is growing interest in exploring whether ChatGPT can replace traditional knowledge-based question answering (KBQA) models. Although there have been some works analyzing t

Kamil Bujel, Andrew Caines, Helen Yannakoudakis, Marek Rei

Long-sequence transformers are designed to improve the representation of longer texts by language models and their performance on downstream document-level tasks. However, not much is understood about the quality of token-level predictions in long-form models. We investigate the performance of such architectures in the context of document classification with

Kobra Khanmohammadi, Raphael Khoury

The National Vulnerability Disclosure Database is an invaluable source of information for security professionals and researchers. However, in some cases, a vulnerability report is initially published with incomplete information, a situation that complicates incident response and mitigation. In this paper, we perform an empirical study of vulnerabilities that

Prasun Roy, Subhankar Ghosh, Umapada Pal

Air-writing refers to virtually writing linguistic characters through hand gestures in three-dimensional space with six degrees of freedom. This paper proposes a generic video camera-aided convolutional neural network (CNN) based air-writing framework. Gestures are performed using a marker of fixed color in front of a generic video camera, followed by color-

Milena Gazdieva, Arip Asadulaev, Alexander Korotin, Evgeny Burnaev

While the continuous Entropic Optimal Transport (EOT) field has been actively developing in recent years, it became evident that the classic EOT problem is prone to different issues like the sensitivity to outliers and imbalance of classes in the source and target measures. This fact inspired the development of solvers that deal with the unbalanced EOT (UEOT

Mario Bruschi, Francesco Calogero

Consider the recursive relation generating a new positive integer $n_{\ell +1}$ from the positive integer $n_{\ell }$ according to the following simple rules: if the integer $n_{\ell }$ is odd, $n_{\ell +1}=3n_{\ell }+1$; if the integer $n_{\ell }$ is even, $n_{\ell +1}=n_{\ell }/2$. The so-called Collatz conjecture states that, starting from any positive in

Haozhe Jiang, Kaiyue Wen, Yilei Chen

We conduct a systematic study of solving the learning parity with noise problem (LPN) using neural networks. Our main contribution is designing families of two-layer neural networks that practically outperform classical algorithms in high-noise, low-dimension regimes. We consider three settings where the numbers of LPN samples are abundant, very limited, and

Albert Vexler, Alan D. Hutson

Data-driven most powerful tests are statistical hypothesis decision-making tools that deliver the greatest power against a fixed null hypothesis among all corresponding data-based tests of a given size. When the underlying data distributions are known, the likelihood ratio principle can be applied to conduct most powerful tests. Reversing this notion, we con

Michael Levet, Puck Rombach, Nicholas Sieger

In this paper, we show that the $(3k+4)$-dimensional Weisfeiler--Leman algorithm can identify graphs of treewidth $k$ in $O(\log n)$ rounds. This improves the result of Grohe & Verbitsky (ICALP 2006), who previously established the analogous result for $(4k+3)$-dimensional Weisfeiler--Leman. In light of the equivalence between Weisfeiler--Leman and the logic

Jian-Feng Cai, Zhiqiang Xu, Zili Xu

This paper investigates the spectral norm version of the column subset selection problem. Given a matrix $\mathbf{A}\in\mathbb{R}^{n\times d}$ and a positive integer $k\leq\text{rank}(\mathbf{A})$, the objective is to select exactly $k$ columns of $\mathbf{A}$ that minimize the spectral norm of the residual matrix after projecting $\mathbf{A}$ onto the space

Terry Easlick, Wei Sun

We investigate the parameter estimation and prediction of two forms of the stochastic SIR model driven by small L\'{e}vy noise with time-dependent periodic transmission. We present consistency and rate of convergence results for the least-squares estimators. We include simulation studies using the method of projected gradient descent.

K. Lange, C. Dominik, A. G. G. M. Tielens

Polycyclic aromatic hydrocarbons (PAHs) have been detected in numerous circumstellar discs. We propose the continuous processing of PAHs through clustering, adsorption on dust grains, and their reverse-processes as key mechanisms to reduce the emission-capable PAH abundance in protoplanetary discs. This cycle of processing is driven by vertical turbulence in

Ilia Musco, Karsten Jedamzik, Sam Young

Primordial black hole (PBH) formation during cosmic phase transitions and annihilation periods, such as the QCD transition or the $e^+e^-$-annihilation, is thought to be particularly efficient due to a softening of the equation of state. We present a detailed numerical study of PBH formation during the QCD epoch in order to derive an accurate PBH mass functi

Rachael Boyd, Richard Hepworth, Peter Patzt

We show that the homology of the partition algebras, interpreted as appropriate Tor-groups, is isomorphic to that of the symmetric groups in a range of degrees that increases with the number of nodes. Furthermore, we show that when the defining parameter $\delta$ of the partition algebra is invertible, the homology of the partition algebra is in fact isomorp

J. W. Hu, L. T. Yang, Q. Yue, X. P. Geng

Low-energy background through Compton scattering from the ambient $\gamma$ rays can be contaminated in direct dark matter search experiments. In this paper, we report comparable measurements on low-energy spectra via Compton scattering from several $\gamma$-ray sources with a p-type point-contact germanium detector. The spectra between 500 eV and 18 keV have

Kangkang Li, Jianming Wen, Yin Cai, Saeid Vashahri Ghamsari

Sources of entangled multiphotons are not only essential for fundamental tests of quantum foundations, but are also the cornerstone of a variety of optical quantum technologies today. Over past three decades, tremendous efforts have been devoted to creating multiphoton entanglement by multiplexing existing biphoton sources with linear optics and postselectio

Zhenghuan Gao, Xi-Nan Ma, Dekai Zhang

In this paper, we consider the Dirichlet problem for the homogeneous $k$-Hessian equation with prescribed asymptotic behavior at $0\in\Omega$ where $\Omega$ is a $(k-1)$-convex bounded domain in the Euclidean space. The prescribed asymptotic behavior at $0$ of the solution is zero if $k>\frac{n}{2}$, it is $\log|x|+O(1)$ if $k=\frac{n}{2}$ and $-|x|^{\frac{2

José Ferreira, Alan Oliveira, André Souto, José Cecílio

As the Internet of Things (IoT) continues to expand, data security has become increasingly important for ensuring privacy and safety, especially given the sensitive and, sometimes, critical nature of the data handled by IoT devices. There exist hardware-based trusted execution environments used to protect data, but they are not compatible with low-cost devic

Vishal Parmar, Manoj K Sharma, S K Patra

We present a comprehensive analysis of hot and dilute isospin-asymmetric nuclear matter employing the temperature-dependent effective-relativistic mean-field theory (E-RMF). The E-RMF is applied to study the effect of $\delta$ and $\omega-\rho$ meson cross-coupling on the thermal properties of asymmetric nuclear matter using two recently developed IOPB-I and

Juan A Perez

For more than a century, Cantor's theory of transfinite numbers has played a pivotal role in set theory, with ramifications that extend to many areas of mathematics. This article extends earlier findings with a fresh look at the critical facts of Cantor's theory: i) Cantor's widely renowned Diagonalization Argument (CDA) is fully refuted by a set of counter-

Eugen Dizer, Zoltán Harman

The hadronic vacuum polarization correction to the $g$ factor of a bound electron is investigated theoretically. An effective hadronic Uehling potential obtained from measured cross sections of $e^- e^+$ annihilation into hadrons is employed to calculate $g$ factor corrections for low-lying hydrogenic levels. Analytical Dirac-Coulomb wave functions, as well

Zehang Weng, Haofei Lu, Jens Lundell, Danica Kragic

This work addresses the problem of learning approach-constrained data-driven grasp samplers. To this end, we propose GoNet: a generative grasp sampler that can constrain the grasp approach direction to a subset of SO(3). The key insight is to discretize SO(3) into a predefined number of bins and train GoNet to generate grasps whose approach directions are wi

Michael Hahn, Navin Goyal

Scaling large language models (LLMs) leads to an emergent capacity to learn in-context from example demonstrations. Despite progress, theoretical understanding of this phenomenon remains limited. We argue that in-context learning relies on recombination of compositional operations found in natural language data. We derive an information-theoretic bound showi

Lucas Kreiss, Shaowei Jiang, Xiang Li, Shiqi Xu

Until recently, conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics, fundamental research and biotechnology. Despite this role as gold-standard, staining protocols face several challenges, such as a need for extensive, manual processing of samples, substantial

Martin Farnir, Angelo Valentino, Marc-Antoine Dupret, Anne-Marie Broomhall

The acoustic glitches' signature present in solar-like stars holds invaluable information. Indeed, it is caused by a sharp variation in the sound speed, therefore carrying localised information. One such glitch is the helium glitch caused by the hydrogen and first and second partial helium ionisation region, allowing us to constrain the surface helium abunda

Vishal Parmar, Manoj K Sharma, S K Patra

This work aim to study the various thermal characteristics of nuclei in view of the saturation and critical behavior of infinite nuclear matter. The free energy of a nucleus is parametrized using the density and temperature-dependent liquid-drop model and interaction among nucleons is worked out within the effective relativistic mean-field theory (E-RMF). Th

Xiao-Yun Wang, Chen Dong, Quanjin Wang

In this work, we use the artificial neural network (ANN) method to study and predict the distribution of strong coupling constants by fitting the existing data. Our approach takes advantage of the ability of ANN to learn complex nonlinear relations and excellent generalization, and allows for a systematic treatment of the uncertainties associated with the da

Jakob Stein, Matt Turner

We classify $G_2$-instantons admitting $SU(2)^3$-symmetries, and construct a new family of examples on the spinor bundle of the 3-sphere, equipped with the asymptotically conical, co-homogeneity one $G_2$-metric of Bryant-Salamon. We also show that, outside of the $SU(2)^3$-invariant examples, any other $G_2$-instanton on this metric with the same asymptotic

Avijit Lahiri

We briefly review a number of major features of the approach to quantum measurement theory based on environment-induced decoherence of the measuring apparatus, and summarize our observations in the form of a couple of general principles that, unlike the wave function collapse hypothesis, emerge as ones consistent with the unitary Schr\"odinger evolution of w

Nils Wauschkuhn, Katja Frenzel, Burkhard Beckhoff, Philipp Hönicke

The L-shell fluorescence yields and the Coster-Kronig factors of ruthenium (and the corresponding uncertainty) were determined for the first time experimentally by applying radiometrically calibrated instrumentation of the Physikalisch-Technische Bundesanstalt. The resulting fluorescence yields ($\omega_{L_3}=0.0459(20)$, $\omega_{L_2}=0.0415(26)$, $\omega_{

Armin Fatemi, Franziska Tischbein, Frank Wirtz, Christin Schmoger

The decarbonization of for example the energy or heat sector leads to the transformation of distribution grids. The expansion of decentralized energy resources and the integration of new consumers due to sector coupling (e.g. heat pumps or electric vehicles) into low voltage grids increases the need for grid expansion and usage of flexibilities in the grid.

Karim Slimani, Brahim Tamadazte, Catherine Achard

This paper introduces a new method for 3D point cloud registration based on deep learning. The architecture is composed of three distinct blocs: (i) an encoder composed of a convolutional graph-based descriptor that encodes the immediate neighbourhood of each point and an attention mechanism that encodes the variations of the surface normals. Such descriptor

Đorđe Dangić, Lorenzo Monacelli, Raffaello Bianco, Francesco Mauri

Phonon anharmonicity plays a crucial role in determining the stability and vibrational properties of high-pressure hydrides. Furthermore, strong anharmonicity can render phonon quasiparticle picture obsolete questioning standard approaches for modeling superconductivity in these material systems. In this work, we show the effects of non-Lorentzian phonon lin

Edoardo Filippi-Mazzola, Ernst C. Wit

Until 2022, the US patent citation network contained almost 10 million patents and over 100 million citations. To overcome limitations in analyzing such complex networks, we propose a stochastic gradient relational event additive model (STREAM) that models the relationships between citing patents as events that occur over time, where predictors are modeled t

Grzegorz Gutowski, Konstanty Junosza-Szaniawski, Felix Klesen, Paweł Rzążewski

A \emph{mixed interval graph} is an interval graph that has, for every pair of intersecting intervals, either an arc (directed arbitrarily) or an (undirected) edge. We are particularly interested in scenarios where edges and arcs are defined by the geometry of intervals. In a proper coloring of a mixed interval graph $G$, an interval $u$ receives a lower (di

I. Yoon

This study presents techniques for the mass production of large-sized GEM foils for the CMS phase-2 upgrade by the Korean CMS group. The foil production facility is designed with a focus on mass production, including the adoption of the double-mask technique. A polyimide wet etching technology that uses mono ethanolamine is reported, providing a safer workin

Marc Roda-Llordes, Andreu Riera-Campeny, Davide Candoli, Piotr T. Grochowski

We present an experimental proposal for the rapid preparation of the center of mass of a levitated particle in a macroscopic quantum state, that is a state delocalized over a length scale much larger than its zero-point motion and that has no classical analog. This state is prepared by letting the particle evolve in a static double-well potential after a sud

Ezana N. Beyenne

The challenges of using inadequate online recruitment systems can be addressed with machine learning and software engineering techniques. Bi-directional personalization reinforcement learning-based architecture with active learning can get recruiters to recommend qualified applicants and also enable applicants to receive personalized job recommendations. Thi

Somepalli Venkateswarlu, Ahmed Misssaoui, Andreas Honecker, Guy Trambly de Laissardière

It is now well established theoretically and experimentally that a moir\'e pattern, due to a rotation of two atomic layers with respect to each other, creates low-energy flat bands. First discovered in twisted bilayer graphene, these new electronic states are at the origin of strong electronic correlations and even of unconventional superconductivity. Twiste

Kazem Taghandiki, Mohammad Hassan Ahmadi, Elnaz Rezaei Ehsan

The proliferation of data and text documents such as articles, web pages, books, social network posts, etc. on the Internet has created a fundamental challenge in various fields of text processing under the title of "automatic text summarisation". Manual processing and summarisation of large volumes of textual data is a very difficult, expensive, time-consum

C. Charbonnel, D. Schaerer, N. Prantzos, L. Ramírez-Galeano

Unusually high N/O abundance ratios were recently reported for a very compact, intensively star-forming object GN-z11 at $z=10.6$ from JWST/NIRSpec observations. We present an empirical comparison with the C, N, and O abundance ratios in Galactic globular clusters (GCs) over a large metallicity range. We show that hot hydrogen-burning nucleosynthesis within

Luisa Di Piazza, Valeria Marraffa, Kazimierz Musial, Anna Rita Sambucini

In this paper convergence theorems for sequences of scalar, vector and multivalued Pettis integrable functions on a topological measure space are proved for varying measures vaguely convergent.

Samuel I. Watson, Alan Girling, Karla Hemming

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying the most efficient study design is complex though, owing to the correlation between observations within clusters and ov

Jorge J. Betancor, Xuan Thinh Duong, Ming-Yi Lee, Ji Li

Fix $\lambda>0$. Consider the Bessel operator $\triangle_\lambda:=-\frac{d^2}{dx^2}-\frac{2\lambda}{x} \frac d{dx}$ on $\mathbb{R_+}$, where $\mathbb{R_+}:=(0,\infty)$ and $dm_\lambda:=x^{2\lambda}dx$ with $dx$ the Lebesgue measure. We provide a deeper study of the Bessel Riesz transform and fractional integral operator via the related Besov and Triebel--Liz

Maorong Wang, Ling Xiao, Toshihiko Yamasaki

Online knowledge distillation (KD) has received increasing attention in recent years. However, while most existing online KD methods focus on developing complicated model structures and training strategies to improve the distillation of high-level knowledge like probability distribution, the effects of the multi-level knowledge in the online KD are greatly o

W. Baumjohann, R. A. Treumann

Recapitulation of the resonance condition for the fundamental and higher electron cyclotron harmonics in the Electron Cyclotron Maser Instability (ECMI) enables radiation below and confirms the possibility of radiation in a narrow band above harmonics $n>1$. Near $n=1$ resonance on the confined lower X-mode branch, amplification is supported by the decrease

Aida Abiad, Shaun M. Fallat, Mark Kempton, Rupert H. Levene

An important facet of the inverse eigenvalue problem for graphs is to determine the minimum number of distinct eigenvalues of a particular graph. We resolve this question for the join of a connected graph with a path. We then focus on bordering a matrix and attempt to control the change in the number of distinct eigenvalues induced by this operation. By appl

Cathy Mengying Fang, Ryo Suzuki, Daniel Leithinger

This paper introduces VR Haptics at Home, a method of repurposing everyday objects in the home to provide casual and on-demand haptic experiences. Current VR haptic devices are often expensive, complex, and unreliable, which limits the opportunities for rich haptic experiences outside research labs. In contrast, we envision that, by repurposing everyday obje

Paul C. Kainen

Sphere-bases are constructed for the $\mathbb{Z}_2$ vector space formed by the $k$-dimensional subcomplexes, of $n$-simplex (or $n$-cube), for which every $(k{-}1)$-face is contained in a positive even number of $k$-cells; addition is symmetric difference of the corresponding sets of $k$-cells. The bases consist of the boundaries of an algorithmically-specif

A. Harter, M. Weinert, L. Knafla, J. -M. Régis

The performance of two implementations of digital real-time interpolating constant fraction discriminator algorithms with respect to fast-timing lifetime measurements are investigated. The implementations integrated in two different digitizers were evaluated in terms of the effects of tuning parameters of the digital CFDs and the influence of different input

Francesco Greco, David Codony, Hossein Mohammadi, Sonia Fernandez-Mendez

The flexoelectric effect, coupling polarization and strain gradient as well as strain and electric field gradients, is universal to dielectrics, but, as compared to piezoelectricity, it is more difficult to harness as it requires field gradients and it is a small-scale effect. These drawbacks can be overcome by suitably designing metamaterials made of a non-

Chaehun Shin, Heeseung Kim, Che Hyun Lee, Sang-gil Lee

Despite the fact that text-to-video (TTV) model has recently achieved remarkable success, there have been few approaches on TTV for its extension to video editing. Motivated by approaches on TTV models adapting from diffusion-based text-to-image (TTI) models, we suggest the video editing framework given only a pretrained TTI model and a single <text, video>

Jeremy Speth, Nathan Vance, Patrick Flynn, Adam Czajka

Subtle periodic signals such as blood volume pulse and respiration can be extracted from RGB video, enabling remote health monitoring at low cost. Advancements in remote pulse estimation -- or remote photoplethysmography (rPPG) -- are currently driven by deep learning solutions. However, modern approaches are trained and evaluated on benchmark datasets with

Mari Dahl Eggen, Alise Danielle Midtfjord

To model time series accurately is important within a wide range of fields. As the world is generally too complex to be modelled exactly, it is often meaningful to assess the probability of a dynamical system to be in a specific state. This paper presents the Delay-SDE-net, a neural network model based on stochastic delay differential equations (SDDEs). The

P. Hartley, A. Bonaldi, R. Braun, J. N. H. S. Aditya

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of

Aljoscha Rörig, Sang-Kil Son, Tommaso Mazza, Philipp Schmidt

Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is crucial for gaining insights into the structure and dynamics of matter. One key aspect of nonlinear light-matter interaction was, so far, not studied systematically at free-electron lasers -- its dependence on the photon energy. Using resonant ion spectroscopy, we map out

Anastasiya Tanana

We consider existence and uniqueness of Nash equilibria in an $N$-player game of utility maximization under relative performance criteria of multiplicative form in complete semimartingale markets. For a large class of players' utility functions, a general characterization of Nash equilibria for a given initial wealth vector is provided in terms of invertibil

Jesus L. Lobo, Ibai Laña, Eneko Osaba, Javier Del Ser

AI-based digital twins are at the leading edge of the Industry 4.0 revolution, which are technologically empowered by the Internet of Things and real-time data analysis. Information collected from industrial assets is produced in a continuous fashion, yielding data streams that must be processed under stringent timing constraints. Such data streams are usual

Wei Sun, Pei-Pei Zhang, Peng-peng Zhou, Shao-long Chen

We investigate the $2\,^3\!S_1$--$2\,^3\!P_J$ ($J = 0, 1, 2$) transitions in $\rm^6Li^+$ using the optical Ramsey technique and achieve the most precise values of the hyperfine splittings of the $2\,^3\!S_1$ and $2\,^3\!P_J$ states, with smallest uncertainty of about 10~kHz. The present results reduce the uncertainties of previous experiments by a factor of

Zhaoyang Lyu, Jinyi Wang, Yuwei An, Ya Zhang

Mesh generation is of great value in various applications involving computer graphics and virtual content, yet designing generative models for meshes is challenging due to their irregular data structure and inconsistent topology of meshes in the same category. In this work, we design a novel sparse latent point diffusion model for mesh generation. Our key in

Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Hyeonsu Kim

Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting. However, the lack of 3D awareness in the 2D diffusion models destabilizes score distillation-based methods from reconstructing a p

Tim Puphal, Malte Probst, Misa Komuro, Yiyang Li

We address the problem of motion planning for four-way intersection crossings with right-of-ways. Road safety typically assigns liability to the follower in rear-end collisions and to the approaching vehicle required to yield in side crashes. As an alternative to previous models based on heuristic state machines, we propose a planning framework which changes

Qihan He, Yafei Li, Yanfang Peng

In this paper, we study the following coupled nonlinear logarithmic Hartree system \begin{align*} \left\{ \displaystyle \begin{array}{ll} \displaystyle -\Delta u+ \lambda_1 u =\mu_1\left( -\frac{1}{2\pi}\ln(|x|) \ast u^2 \right)u+\beta \left( -\frac{1}{2\pi}\ln(|x|) \ast v^2 \right)u, & x \in ~ \mathbb R^2, \vspace{.4cm}\\ -\Delta v+ \lambda_2 v =\mu_2\left(

Jean-Christophe Pain

In this note, we propose simple summations for primes, which involve two finite nested sums and Bernoulli numbers. The summations can also be expressed in terms of Bernoulli polynomials.

Xanthi Pedeli, Roland Fried

We study the problem of intervention effects generating various types of outliers in an integer-valued autoregressive model with Poisson innovations. We concentrate on outliers which enter the dynamics and can be seen as effects of extraordinary events. We consider three different scenarios, namely the detection of an intervention effect of a known type at a

Max van Haren, Lennart Blanken, Tom Oomen

The increasing demands for motion control result in a situation where Linear Parameter-Varying (LPV) dynamics have to be taken into account. Inverse-model feedforward control for LPV motion systems is challenging, since the inverse of an LPV system is often dynamically dependent on the scheduling sequence. The aim of this paper is to develop an identificatio

Charlotte Simmonds, Sandro Tacchella, Michael V. Maseda, Christina Williams

We study the ionising photon production efficiency at the end of the Epoch of Reionisation ($z \sim 5.4 - 6.6$) for a sample of 30 Lyman-$\alpha$ emitters. This is a crucial quantity to infer the ionising photon budget of the Universe. These objects were selected to have reliable spectroscopic redshifts, assigned based on the profile of their Lyman-$\alpha$

Ian Dobson

Poisson process models are defined in terms of their rates for outage and restore processes in power system resilience events. These outage and restore processes easily yield the performance curves that track the evolution of resilience events, and the area, nadir, and duration of the performance curves are standard resilience metrics. This letter analyzes t

Andreas Mueller

The exponential and Cayley map on SE(3) are the prevailing coordinate maps used in Lie group integration schemes for rigid body and flexible body systems. Such geometric integrators are the Munthe-Kaas and generalized-alpha schemes, which involve the differential and its directional derivative of the respective coordinate map. Relevant closed form expression

Kijung Lee, Prudence Attablayo

This research aims to investigate the impact of users' privacy awareness on their self-disclosing behavior. Our primary research question is to investigate how young social media users feel about the benefits and risks of disclosing them-selves on social media and how risk-benefit awareness influences the assess-ment of their self-disclosure. Based on the da