July 2023 arXiv papers — page 156

Alvaro Bustos-Gajardo, Johannes Kellendonk, Reem Yassawi

In this article we completely characterise constant length substitution shifts which have an almost automorphic factor, or which have a bijective substitution factor. Our approach is algebraic: we study these dynamical properties in terms of a finite semigroup defined by the substitution. We characterise the existence of almost automorphic factors in terms o

Chris Gagne, Peter Dayan

Transformer-based large-scale language models (LLMs) are able to generate highly realistic text. They are duly able to express, and at least implicitly represent, a wide range of sentiments and color, from the obvious, such as valence and arousal to the subtle, such as determination and admiration. We provide a first exploration of these representations and

Ali Shoker, Paulo Esteves Verissimo, Marcus Völp

The hardware computing landscape is changing. What used to be distributed systems can now be found on a chip with highly configurable, diverse, specialized and general purpose units. Such Systems-on-a-Chip (SoC) are used to control today's cyber-physical systems, being the building blocks of critical infrastructures. They are deployed in harsh environmen

Salma Afifi, Febin Sunny, Amin Shafiee, Mahdi Nikdast

Graph neural networks (GNNs) have emerged as a powerful approach for modelling and learning from graph-structured data. Multiple fields have since benefitted enormously from the capabilities of GNNs, such as recommendation systems, social network analysis, drug discovery, and robotics. However, accelerating and efficiently processing GNNs require a unique ap

Shyan Akmal, Virginia Vassilevska Williams, Ryan Williams, Zixuan Xu

The $k$-Detour problem is a basic path-finding problem: given a graph $G$ on $n$ vertices, with specified nodes $s$ and $t$, and a positive integer $k$, the goal is to determine if $G$ has an $st$-path of length exactly $\text{dist}(s, t) + k$, where $\text{dist}(s, t)$ is the length of a shortest path from $s$ to $t$. The $k$-Detour problem is NP-hard when

Danish Gufran, Sudeep Pasricha

Indoor localization plays a vital role in applications such as emergency response, warehouse management, and augmented reality experiences. By deploying machine learning (ML) based indoor localization frameworks on their mobile devices, users can localize themselves in a variety of indoor and subterranean environments. However, achieving accurate indoor loca

Giuseppe Cavaliere, Thomas Mikosch, Anders Rahbek, Frederik Vilandt

Engle and Russell (1998, Econometrica, 66:1127--1162) apply results from the GARCH literature to prove consistency and asymptotic normality of the (exponential) QMLE for the generalized autoregressive conditional duration (ACD) model, the so-called ACD(1,1), under the assumption of strict stationarity and ergodicity. The GARCH results, however, do not accoun

Torty Sivill, Peter Flach

Despite their ubiquitous use, Shapley value feature attributions can be misleading due to feature interaction in both model and data. We propose an alternative attribution approach, Shapley Sets, which awards value to sets of features. Shapley Sets decomposes the underlying model into non-separable variable groups using a recursive function decomposition alg

Tapan K. Sengupta, Aditi Sengupta, Bhavna Joshi

The perturbation equation for aeroacoustics has been derived in a dissipative medium from the linearized compressible Navier-Stokes equation without any assumption, by expressing the same in spectral plane as in Continuum perturbation field in quiescent ambience: Common foundation of flows and acoustics Sengupta et al., Phys. Fluids,35, 056111 (2023). The go

Erwan Faou, Antoine Mouzard

We start from the remark that in wave turbulence theory, exemplified by the cubic twodimensional Schr{ö}dinger equation (NLS) on the real plane, the regularity of the resonant manifold is linked with dispersive properties of the equation and thus with scattering phenomena. In contrast with classical analysis starting with a dynamics on a large periodic box,

Jan Rooduijn, Yde Venema

We introduce a cyclic proof system for the two-way alternation-free modal $μ$-calculus. The system manipulates one-sided Gentzen sequents and locally deals with the backwards modalities by allowing analytic applications of the cut rule. The global effect of backwards modalities on traces is handled by making the semantics relative to a specific strategy of t

Sarah A. Obead, Hsuan-Yin Lin, Eirik Rosnes, Jörg Kliewer

We consider the problem of private computation (PC) in a distributed storage system. In such a setting a user wishes to compute a function of $f$ messages replicated across $n$ noncolluding databases, while revealing no information about the desired function to the databases. We provide an information-theoretically accurate achievable PC rate, which is the r

Aifang Qu, Xueying Su, Hairong Yuan

We consider the problem of uniform steady supersonic Euler flows passing a straight conical body with attack angles, and study Radon measure solutions describing the infinite-thin shock layers, particularly for the Chaplygin gas and limiting hypersonic flows. As a byproduct, we obtain the generalized Newton-Busemann pressure laws. To construct the Radon meas

Darlington Akogo, Issah Samori, Cyril Akafia, Harriet Fiagbor

The Ghana Cashew Disease Identification with Artificial Intelligence (CADI AI) project demonstrates the importance of sound data work as a precondition for the delivery of useful, localized datacentric solutions for public good tasks such as agricultural productivity and food security. Drone collected data and machine learning are utilized to determine crop

Guangzhi Sun, Chao Zhang, Ivan Vulić, Paweł Budzianowski

Manually annotating fine-grained slot-value labels for task-oriented dialogue (ToD) systems is an expensive and time-consuming endeavour. This motivates research into slot-filling methods that operate with limited amounts of labelled data. Moreover, the majority of current work on ToD is based solely on text as the input modality, neglecting the additional c

Shashank A. Deshpande, Ankur A. Kulkarni

We have shown that entanglement assisted stochastic strategies allow access to strategic measures beyond the classically correlated measures accessible through passive common randomness, and thus attain a quantum advantage in decentralised control. In this two part series of articles, we investigate the decision theoretic origins of the quantum advantage wit

Paul Zheng, Emilie Chouzenoux, Laurent Duval

Denoising, detrending, deconvolution: usual restoration tasks, traditionally decoupled. Coupled formulations entail complex ill-posed inverse problems. We propose PENDANTSS for joint trend removal and blind deconvolution of sparse peak-like signals. It blends a parsimonious prior with the hypothesis that smooth trend and noise can somewhat be separated by lo

Saeid K. Dehkordi, Peter Jung, Philipp Walk, Dennis Wieruch

In this work, we propose a waveform based on Modulation on Conjugate-reciprocal Zeros (MOCZ) originally proposed for short-packet communications in [1], as a new Integrated Sensing and Communication (ISAC) waveform. Having previously established the key advantages of MOCZ for noncoherent and sporadic communication, here we leverage the optimal auto-correlati

E. E. Vdovin, M. T. Greenaway, Yu. N. Khanin, S. V. Morozov

Insights into the fundamental properties of graphene's Dirac-Weyl fermions have emerged from studies of electron tunnelling transistors in which an atomically thin layer of hexagonal boron nitride (hBN) is sandwiched between two layers of high purity graphene. Here, we show that when a single defect is present within the hBN tunnel barrier, it can inject

Sofia Strukova, Rubén Gaspar Marco, José A. Ruipérez-Valiente, Félix Gómez Mármol

In our generation, there is an undoubted rise in the use of social media and specifically photo and video sharing platforms. These sites have proved their ability to yield rich data sets through the users' interaction which can be used to perform a data-driven evaluation of capabilities. Nevertheless, this study reveals the lack of suitable data sets in

Nandan Pakhira, Rajib Mahato

Field emission effect is the emission of electrons from a cold metallic surface in the presence of an electric field. The emission current exponentially depends on the work function of the metallic surface. In this work we consider the role of work function distribution on the field emission current. The work function distribution can arise due to nano-scale

Alexey Protopopov

K-complexes are an important marker of brain activity and are used both in clinical practice to perform sleep scoring, and in research. However, due to the size of electroencephalography (EEG) records, as well as the subjective nature of K-complex detection performed by somnologists, it is reasonable to automate K-complex detection. Previous works in this fi

Sadra Jazayeri, Sébastien Renaux-Petel, Denis Werth

Massive particles produced during inflation leave specific signatures in soft limits of correlation functions of primordial fluctuations. When the Goldstone boson of broken time translations acquires a reduced speed of sound, implying that de Sitter boosts are strongly broken, we introduce a novel discovery channel to detect new physics during inflation, cal

Geoffrey Beck, David Lannes, Lisl Weynans

The goal of this work is to study waves interacting with partially immersed objects allowed to move freely in the vertical direction, and in a regime in which the propagation of the waves is described by the one dimensional Boussinesq-Abbott system. The problem can be reduced to a transmission problem for this Boussinesq system, in which the transmission con

Gerrit E. Elsinga, Takashi Ishihara, J. C. R. Hunt

The Richardson scaling law states that the mean square separation of a fluid particle pair grows according to t3 within the inertial range and at intermediate times. The theories predicting this scaling regime assume that the pair separation is within the inertial range and that the dispersion is local, meaning that only eddies at the scale of the separation

Matti Jarvinen

The gauge/gravity duality, combined with information from lattice QCD, nuclear theory, and perturbative QCD, can be used to constrain the equation of state of hot and dense QCD. I discuss an approach based on the holographic V-QCD model. I start by reviewing the results from the construction of the V-QCD baryon as a soliton of the gauge fields in the model.

E. M. Amazo-Gómez, J. D. Alvarado-Gómez, K. Poppenhaeger, G. A. J. Hussain

A comprehensive multi-wavelength campaign has been carried out to probe stellar activity and variability in the young Sun-like star $ι$-Horologii. We present the results from long-term spectropolarimetric monitoring of the system by using the ultra-stable spectropolarimeter/velocimeter HARPS at the ESO 3.6-m telescope. Additionally, we included high-precisio

Yuzhou Fang, Chao Zhang

We deal with a wide class of generalized nonlocal $p$-Laplace equations, so-called nonlocal $G$-Laplace equations, in the Heisenberg framework. Under natural hypotheses on the $N$-function $G$, we provide a unified approach to investigate in the spirit of De Giorgi-Nash-Moser theory, some local properties of weak solutions to such kind of problems, involving

Michael Mommert, Nicolas Kesseli, Joëlle Hanna, Linus Scheibenreif

Deep learning methods have proven to be a powerful tool in the analysis of large amounts of complex Earth observation data. However, while Earth observation data are multi-modal in most cases, only single or few modalities are typically considered. In this work, we present the ben-ge dataset, which supplements the BigEarthNet-MM dataset by compiling freely a

Mattia Alberto Ubertini, Angelo Rosa

We present Monte Carlo computer simulations for melts of semiflexible randomly knotted and randomly concatenated ring polymers on the fcc lattice and in slit confinement. Through systematic variation of the slit width at fixed melt density, we first explore the influence of confinement on single-chain conformations and inter-chain interactions. We demonstrat

Alberto Montefusco, Luzie Helfmann, Toluwani Okunola, Stefanie Winkelmann

This article addresses reaction networks in which spatial and stochastic effects are of crucial importance. For such systems, particle-based models allow us to describe all microscopic details with high accuracy. However, they suffer from computational inefficiency if particle numbers and density get too large. Alternative coarse-grained-resolution models re

Meirav Amram, Shinzo Bannai, Taketo Shirane, Uriel Sinichkin

In this paper, we continue the study of the embedded topology of plane algebraic curves. We study the realization space of conic line arrangements of degree $7$ with certain fixed combinatorics and determine the number of connected components. This is done by showing the existence of a Zariski pair having these combinatorics, which we identified as a $π_1$-e

P. S. Jørgensen, L. Besley, A. M. Slyamov, A. Diaz

We demonstrate a technique that allows highly surface sensitive imaging of nanostructures on planar surfaces over large areas, providing a new avenue for research in materials science, especially for \textit{in situ} applications. The capabilities of hard X-ray grazing incidence ptychography combine aspects from imaging, reflectometry and grazing incidence s

Thijs Albers, Stijn Delnoij, Nico Schramma, Maziyar Jalaal

Many classes of active matter develop spatial memory by encoding information in space, leading to complex pattern formation. It has been proposed that spatial memory can lead to more efficient navigation and collective behaviour in biological systems and influence the fate of synthetic systems. This raises important questions about the fundamental properties

W. G. D. P. Silva, J. Cernicharo, S. Schlemmer, N. Marcelino

Based on a novel laboratory method, 14 mm-wave lines of the molecular ion H$_2$CCCH$^+$ have been measured in high resolution, and the spectroscopic constants of this asymmetric rotor determined with high accuracy. Using the Yebes 40 m and IRAM 30 m radio telescopes, we detect four lines of H$_2$CCCH$^+$ towards the cold dense core TMC-1. With a dipole momen

Benjamin Bergougnoux, Jakub Gajarský, Grzegorz Guśpiel, Petr Hliněný

Twin-width is a structural width parameter introduced by Bonnet, Kim, Thomassé and Watrigant [FOCS 2020]. Very briefly, its essence is a gradual reduction (a contraction sequence) of the given graph down to a single vertex while maintaining limited difference of neighbourhoods of the vertices, and it can be seen as widely generalizing several other tradition

R. A. J. Eyles-Ferris, R. L. C. Starling

The LOFAR Two-Metre Sky Survey (LoTSS) is an invaluable new tool for investigating the properties of sources at low frequencies and has helped to open up the study of galaxy populations in this regime. In this work, we perform a search for host galaxies of gamma-ray bursts (GRBs). We use the relative density of sources in Data Release 2 of LoTSS to define th

Duc-Manh Nguyen

Let $\mathbb{P}Ω^d\mathcal{M}_{0,n}(κ)$, where $κ=(k_1,\dots,k_n)$, be a stratum of (projectivized) $d$-differentials in genus $0$. We prove a recursive formula which relates the volume of $\mathbb{P}Ω^d\mathcal{M}_{0,n}(κ)$ to the volumes of other strata of lower dimensions in the case where none of the $k_i$ is divisible by $d$. As an application, we give

Huan Li, Jingxuan Huang, Zesong Fei

The factor graph (FG) based iterative detection is considered an effective and practical method for multiple-input and multiple-out (MIMO), particularly massive MIMO (m-MIMO) systems. However, the convergence analysis for the FG-based iterative MIMO detection is insufficient, which is of great significance to the performance evaluation and algorithm design o

Feng Zhou, Antonio Cicone, Haomin Zhou

The decomposition of non-stationary signals is an important and challenging task in the field of signal time-frequency analysis. In the recent two decades, many signal decomposition methods led by the empirical mode decomposition, which was pioneered by Huang et al. in 1998, have been proposed by different research groups. However, they still have some limit

Khoi Ly, Chong-Chan Kim, Robert Shepherd

As an alternative approach to ionic data transmission with hydrogel as substrate, this work explores the possible applications of liquid electrolyte filling cavity of a stretchable, flexible elastomeric tubing, which is the primary ingredient used in redox flow battery systems. While hydrogel-based ionic impedance characterization and its data communication

Jiri Smetana, Chiara Di Fronzo, Anthony Amorosi, Denis Martynov

Compact Michelson interferometers are well positioned to replace existing displacement sensors in the readout of seismometers and suspension systems, such as those used in contemporary gravitational-wave detectors. Here, we continue our previous investigation of a customised compact displacement sensor built by SmarAct, which operated on the principle of dee

Elia Rizzetto, Arcangelo Massari, Ivan Heibi, Silvio Peroni

The paper introduces a tool prototype that combines SHACL's capabilities with ad-hoc validation functions to create a controlled and user-friendly form interface for producing valid RDF data. The proposed tool is developed within the context of the OpenCitations Data Model (OCDM) use case. The paper discusses the current status of the tool, outlines the

Anne van der Linden, Ralph F. G. Meulenbroeks, Wouter R. van Joolingen

Digital educational games have demonstrated large variations in learning outcomes and transfer. Furthermore, educational games are usually embedded in a larger educational setting. This case study evaluates in detail a lesson around an educational game designed to foster transfer. The game, Newtons Race, is an intrinsically integrated game on Newtonian mecha

Jiao Zhang, Hongtao Zhang, Xuelei Chen, Fengquan Wu

Peak sidelobe level reduction (PSLR) is crucial in the application of large-scale array antenna, which directly determines the radiation performance of array antenna. We study the PSLR of subarray level aperiodic arrays and propose three array structures: dislocated subarrays with uniform elements (DSUE), uniform subarrays with random elements (USRE), disloc

Chen Chen, Yufei Wang, Aixin Sun, Bing Li

Knowledge Graph Completion (KGC) often requires both KG structural and textual information to be effective. Pre-trained Language Models (PLMs) have been used to learn the textual information, usually under the fine-tune paradigm for the KGC task. However, the fine-tuned PLMs often overwhelmingly focus on the textual information and overlook structural knowle

Shuyi Wang, Tie Hu, Shichuan Wang, Ming Zhao

Imaging polarimetry based on dielectric metasurface is well-known for its ultra-compactness and high integration. However, previous works suffer from low energy efficiency, limited restrictions on choice of target polarization states, or inability to focus light. Here, by inverse design, we numerically demonstrate a multi-foci metalens-based polarimetry that

Joshua T. Majekodunmi, M. Bhuyan, Raj Kumar

The cluster dynamics of radioactive nuclei decaying to neighbouring daughter nuclei of the double magic $^{132}$Sn and $^{208}$Pb is investigated using the relativistic mean-field (RMF) approach with NL3$^*$ parameter set within the preformed cluster-decay model (PCM). The novel feature of the present study is the application of the newly derived preformatio

Swagata Roy, Johannes P. Dürholt, Thomas S. Asche, Federico Zipoli

The reactivity of silicates in an aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of chemical reactions can provide insight at the molecular level, balancing accuracy and scale in reactive simulati

Peng Tang, Yang Nan, Tobias Lasser

Many skin lesion analysis (SLA) methods recently focused on developing a multi-modal-based multi-label classification method due to two factors. The first is multi-modal data, i.e., clinical and dermoscopy images, which can provide complementary information to obtain more accurate results than single-modal data. The second one is that multi-label classificat

Róger W. P. da Silva, Diego Eckhard

Data-driven direct methods are still growing in popularity almost three decades after they were introduced. These methods use data collected from the process to identify optimal controller's parameters with little knowledge about the process itself. However, most of those works focus on the problem of reference tracking, whereas many of the problems face

Paul Pfeiffer, Wolfgang Spitzer

We consider fermionic ground states of the Landau Hamiltonian, $H_B$, in a constant magnetic field of strength $B>0$ in $\mathbb R^2$ at some fixed Fermi energy $μ>0$, described by the Fermi projection $P_B:= 1(H_B\le μ)$. For some fixed bounded domain $Λ\subset \mathbb{R}^2$ with boundary set $\partialΛ$ and an $L>0$ we restrict these ground states spatiall

Sebastien Boucksom, Mattias Jonsson

We introduce a synthetic approach to global pluripotential theory, covering in particular the case of a compact Kähler manifold and that of a projective Berkovich space over a non-Archimedean field. We define and study the space of measures of finite energy, introduce twisted energy and free energy functionals thereon, and show that coercivity of these funct

M. H. M. Rashid

The Euclidean operator radius of two bounded linear operators in the Hilbert $C^*$-module over $\A$ is given some precise bounds. Their relationship to recent findings in the literature that offer precise upper and lower bounds on the numerical radius of linear operators is also established.

Man Yao, Jiakui Hu, Zhaokun Zhou, Li Yuan

Spiking Neural Networks (SNNs) provide an energy-efficient deep learning option due to their unique spike-based event-driven (i.e., spike-driven) paradigm. In this paper, we incorporate the spike-driven paradigm into Transformer by the proposed Spike-driven Transformer with four unique properties: 1) Event-driven, no calculation is triggered when the input o

Rohan Jinturkar

Although there is widespread recognition of racial bias in US law, it is unclear how such bias appears in the language of law, namely judicial opinions, and whether it varies across time period or region. Building upon approaches for measuring implicit racial bias in large-scale corpora, we approximate GloVe word embeddings for over 6 million US federal and

F. Aharonian, F. Ait Benkhali, J. Aschersleben, H. Ashkar

In July 2021, PKS 1510-089 exhibited a significant flux drop in the high-energy gamma-ray (by a factor 10) and optical (by a factor 5) bands and remained in this low state throughout 2022. Similarly, the optical polarization in the source vanished, resulting in the optical spectrum being fully explained through the steady flux of the accretion disk and the b

Mohee Datta Gupta

Pressure sensors are popular in a large variety of industries. For some applications, it is critical for these sensors to come in a flexible form factor. With the development of new synthetic polymers and novel fabrication techniques, flexible pressure sensing arrays are more easily accessible and can serve a variety of applications. As part of this disserta

Victor See, Julia Roquette, Louis Amard, Sean Matt

The magnetic activity level of low-mass stars is known to vary as a function of the physical properties of the star. Many studies have shown that the stellar mass and rotation are both important parameters that determine magnetic activity levels. In contrast, the impact of a star's chemical composition on magnetic activity has received comparatively litt

Bayu Dharmaputra, Sergey Shcherbanev, Bruno Schuermans, Nicolas Noiray

This study demonstrates the stabilization of a sequential combustor with Nanosecond Repetitively Pulsed Discharges (NRPD). A constant pressure sequential combustor offers key advantages compared to a conventional combustor, in particular, a higher fuel flexibility and a wider operational range. However, thermoacoustic instabilities remain a barrier to furthe

Liekang Zeng, Xu Chen, Peng Huang, Ke Luo

Graph Neural Networks (GNNs) have gained growing interest in miscellaneous applications owing to their outstanding ability in extracting latent representation on graph structures. To render GNN-based service for IoT-driven smart applications, traditional model serving paradigms usually resort to the cloud by fully uploading geo-distributed input data to remo

Guy Berger, Aviv Navon, Ethan Fetaya

In computer vision and machine learning, a crucial challenge is to lower the computation and memory demands for neural network inference. A commonplace solution to address this challenge is through the use of binarization. By binarizing the network weights and activations, one can significantly reduce computational complexity by substituting the computationa

Taras Parashchuk, Oleksandr Cherniushok, Raul Cardoso-Gil, Janusz Tobola

Cu-based argyrodites have gained much attention as a new class of thermoelectric materials for energy harvesting. However, the phase transition occurring in these materials and low energy conversion performance limited their broad application in thermoelectric converters. In this work, we disclose a newly discovered highly efficient Cu8SiSxSe6-x argyrodite w

Mitsuaki Hirasawa, Konstantinos N. Anagnostopoulos, Takehiro Azuma, Kohta Hatakeyama

The Lorentzian type IIB matrix model is a promising candidate for a non-perturbative formulation of superstring theory. However, it was recently found that a Euclidean space-time appears in the conventional large-$N$ limit. In this work, we study the model with a Lorentz invariant mass term which can be considered as an IR regulator. By performing complex La

Dimosthenis Antypas, Jose Camacho-Collados

The automatic detection of hate speech online is an active research area in NLP. Most of the studies to date are based on social media datasets that contribute to the creation of hate speech detection models trained on them. However, data creation processes contain their own biases, and models inherently learn from these dataset-specific biases. In this pape

Pratibha Verma, Ankik Kumar Giri

We take into account a coagulation model that simulates a distinct kind of dynamics. In this model, two particles collide to produce a single particle, but the resulting particle decreases in size, allowing each particle to be fully identified by its size. It is demonstrated that the corresponding evolving integral partial differential equation has solutions

Hyeon-Chang Jeon, In-Chang Baek, Cheong-mok Bae, Taehwa Park

The balance of game content significantly impacts the gaming experience. Unbalanced game content diminishes engagement or increases frustration because of repetitive failure. Although game designers intend to adjust the difficulty of game content, this is a repetitive, labor-intensive, and challenging process, especially for commercial-level games with exten

Kaique Matias de Andrade Roberto, Hugo Luiz Mariano

The goal of this work is twofold: (i) to provide a detailed analysis of some categories of inductive graded ring - a concept introduced in [DM98] in order to provide a solution of Marshall's signature conjecture in the algebraic theory of quadratic forms; (ii) apply this analysis to deepen the connections between the category of special hyperfields ([dAR

Javier de la Rosa, Rolv-Arild Braaten, Per Egil Kummervold, Freddy Wetjen

In this paper, we present several baselines for automatic speech recognition (ASR) models for the two official written languages in Norway: Bokmål and Nynorsk. We compare the performance of models of varying sizes and pre-training approaches on multiple Norwegian speech datasets. Additionally, we measure the performance of these models against previous state

Raju Kalita, Atul Saxena

We use Random Matrix Theory (RMT) to describe the eigenvalue spacing of Meghalaya's historical monthly average temperature ($T_{avg}$) in grids. For that, the Nearest Neighbor Spacings ($S_i$) of the eigenvalues of the correlation matrices were found out for 1428 consecutive eigenvalue pair differences. It is found that the distribution of $S_i$ follows

Weijian Luo, Hao Jiang, Tianyang Hu, Jiacheng Sun

Energy-Based Models (EBMs) have been widely used for generative modeling. Contrastive Divergence (CD), a prevailing training objective for EBMs, requires sampling from the EBM with Markov Chain Monte Carlo methods (MCMCs), which leads to an irreconcilable trade-off between the computational burden and the validity of the CD. Running MCMCs till convergence is

Yicheng Xu, Yixiao Zhu, Xiaobo Zeng, Mengfan Fu

We propose a multicarrier modulation-based digital radio-over-fibre system achieving unequal bit protection by bit and power allocation for subcarriers. A theoretical SNR gain of 16.1 dB is obtained in the AWGN channel and the simulation results show a 13.5 dB gain in the bandwidth-limited case.

Ye Liu, Stefan Ultes, Wolfgang Minker, Wolfgang Maier

Spoken dialogue systems (SDSs) have been separately developed under two different categories, task-oriented and chit-chat. The former focuses on achieving functional goals and the latter aims at creating engaging social conversations without special goals. Creating a unified conversational model that can engage in both chit-chat and task-oriented dialogue is

Parveen, Jitender Kumar

S. Bera (Line graph characterization of power graphs of finite nilpotent groups, \textit{Communication in Algebra}, 50(11), 4652-4668, 2022) characterized finite nilpotent groups whose power graphs and proper power graphs are line graphs. In this paper, we extend the results of above mentioned paper to arbitrary finite groups. Also, we correct the correspond

Farhad Rezazadeh, Hatim Chergui, Luis Alonso, Christos Verikoukis

Sixth-generation (6G) network slicing is the backbone of future communications systems. It inaugurates the era of extreme ultra-reliable and low-latency communication (xURLLC) and pervades the digitalization of the various vertical immersive use cases. Since 6G inherently underpins artificial intelligence (AI), we propose a systematic and standalone slice te

Y Zheng, H. R. Qin, S. N. Miao, N. C. Xin

We reported the realization of a $^{174}\mathrm{Yb}^+$-$^{113}\mathrm{Cd}^+$ bi-species Coulomb crystal comprising $^{174}\mathrm{Yb}^+$ ions as coolant and verified its potential for application as a $^{113}\mathrm{Cd}^+$ microwave frequency standard employing sympathetic cooling.The two species of massive ions stably trapped in a Paul trap make up this lar

Jonas-Dario Troles, Richard Nieding, Sonia Simons, Ute Schmid

Climate crisis and correlating prolonged, more intense periods of drought threaten tree health in cities and forests. In consequence, arborists and foresters suffer from increasing workloads and, in the best case, a consistent but often declining workforce. To optimise workflows and increase productivity, we propose a novel open-source end-to-end approach th

Zeev Nutov

We consider the following two variants of the Capacitated $k$-Edge Connected Subgraph} (Cap-k-ECS) problem. Near Min-Cuts Cover: Given a graph $G=(V,E)$ with edge costs and $E_0 \subseteq E$, find a min-cost edge set $J \subseteq E \setminus E_0$ that covers all cuts with at most $k-1$ edges of the graph $G_0=(V,E_0)$. We obtain approximation ratio $k-λ_0+1+

Ran Gu, Shuaichao Wang

Given two $k$-uniform hypergraphs $F$ and $G$, we say that $G$ has an $F$-covering if for every vertex in $G$ there is a copy of $F$ covering it. For $1\leq i\leq k-1$, the minimum $i$-degree $δ_i(G)$ of $G$ is the minimum integer such that every $i$ vertices are contained in at least $δ_i(G)$ edges. Let $c_i(n,F)$ be the largest minimum $i$-degree among all

Andreas Göldi, Roman Rietsche

This paper delves into an advanced implementation of Chain-of-Thought-Prompting in Large Language Models, focusing on the use of tools (or "plug-ins") within the explicit reasoning paths generated by this prompting method. We find that tool-enabled conversational agents often become sidetracked, as additional context from tools like search engines or

David Afonso Delgado, Tanausú del Pino Alemán, Javier Trujillo Bueno

We investigate theoretically the circular polarization signals induced by the Zeeman effect in the Fe II lines of the 279.3-280.7 nm spectral range of the CLASP2 space experiment and their suitability to infer solar magnetic fields. To this end, we use a comprehensive Fe II atomic model to solve the problem of the generation and transfer of polarized radiati

Dingjun Wu, Jing Zhang, Xinmei Huang

The knowledge-augmented deep learning paradigm refers to a paradigm in which domain knowledge is identified and integrated into deep models. Conventional methods typically employ task-specific approaches to gather external knowledge from various sources. In contrast, large language models are extensively pre-trained and can serve as a comprehensive source of

Gregor Betz, Vera Chekan, Tamara Mchedlidze

Mutual coherence is a measure of similarity between two opinions. Although the notion comes from philosophy, it is essential for a wide range of technologies, e.g., the Wahl-O-Mat system. In Germany, this system helps voters to find candidates that are the closest to their political preferences. The exact computation of mutual coherence is highly time-consum

Xiaoshui Lin, Ming Gong, Guang-Can Guo

Mobility edge (ME) has played an essential role in disordered models. However, while this concept has been well established in disordered single-particle models, its existence in disordered many-body models is still under controversy. Here, a general approach based on coupling between extended and localized states in their overlapped spectra for ME is presen

Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Yu

Random Walk is a basic algorithm to explore the structure of networks, which can be used in many tasks, such as local community detection and network embedding. Existing random walk methods are based on single networks that contain limited information. In contrast, real data often contain entities with different types or/and from different sources, which are

Max Althön, Markus Exner, Richard Blättner, Herwig Ott

We report on the observation of two vibrational series of pure trilobite rubidium Rydberg molecules. They are created via three-photon photoassociation and lie energetically more than 15 GHz below the atomic 22$F$ state of rubidium. In agreement with theoretical calculations, we find an almost perfect harmonic oscillator behavior of six vibrational states. W

Hsin-Lun Li

The voter model consists of a set of agents whose opinion is a binary variable. At each time step, an agent along with a social neighbor is selected and the agent imitates the social neighbor at the next time step. In this paper, we study a variant of the voter model: an imitation model based on the majority. The agent imitates the selected social neighbor i

Soumya Chakrabarti

We show that the transformation of a time-evolving spherically symmetric metric tensor into a Painleve-Gullstrand-Lemaitre form brings forth a few curious consequences. The time evolution describes a non-singular gravitational collapse, leading to a bounce and dispersal of all the clustered matter, or a wormhole geometry for certain initial conditions. The n

Samy Tafasca, Anshul Gupta, Jean-Marc Odobez

Gaze behaviors such as eye-contact or shared attention are important markers for diagnosing developmental disorders in children. While previous studies have looked at some of these elements, the analysis is usually performed on private datasets and is restricted to lab settings. Furthermore, all publicly available gaze target prediction benchmarks mostly con

Zsófia Nagy, Sunkyung Park, Péter Ábrahám, Ágnes Kóspál

FU Orionis objects (FUors) are eruptive young stars, which exhibit outbursts that last from decades to a century. Due to the duration of their outbursts, and to the fact that only about two dozens of such sources are known, information on the end of their outbursts is limited. Here we analyse follow-up photometry and spectroscopy of Gaia21elv, a young stella

A. I. Krasnov, P. S. Pankin, G. A. Romanenko, V. S. Sutormin

A photonic crystal microcavity with the liquid crystal resonant layer tunable by heating has been implemented. The multiple vanishing resonant lines corresponding to optical bound states in the continuum are observed. The abrupt behaviour of the resonant linewidth near the vanishing point can be used for temperature sensing.

Nidhi Gahlian

We study higher order linear differential equation $y^{(k)}+A_1(z)y=0$ with $k\geq2$, where $A_1=A+h$, $A$ is a transcendental entire function of finite order with $\frac{1}{2}\leq μ(A)<1$ and $h\neq0$ is an entire function with $ρ(h)<μ(A)$. Then it is shown that, if $f^{(k)}+A(z)f=0$ has a solution $f$ with $λ(f)<μ(A)$ then exponent of convergence of zeros

Andi Bodnariu, Kristoffer Lindensjö

We consider a continuous time stochastic dynamic game between a stopper (Player $1$, the \textit{owner} of an asset yielding an income) and a controller (Player $2$, the \textit{manager} of the asset), where the manager is either effective or non-effective. An effective manager can choose to exert low or high effort which corresponds to a high or a low posit

Andrey Polyakov, Miroslav Krstic

A static non-linear homogeneous feedback for a fixed-time stabilization of a linear time-invariant (LTI) system is designed in such a way that the settling time is assigned exactly to a prescribed constant for all nonzero initial conditions. The constant convergence time is achieved due to a dependence of the feedback gain of the initial state of the system.

Sebastian Frey, Marco Guermandi, Simone Benatti, Victor Kartsch

Wearable biosignal processing applications are driving significant progress toward miniaturized, energy-efficient Internet-of-Things solutions for both clinical and consumer applications. However, scaling toward high-density multi-channel front-ends is only feasible by performing data processing and machine Learning (ML) near-sensor through energy-efficient

Olivier Lindamulage De Silva, Vineeth Satheeskumar Varma, Ming Cao, Irinel-Constantin Morarescu

A Stackelberg duopoly model in which two firms compete to maximize their market share is considered. The firms offer a service/product to customers that are spread over several geographical regions (e.g., countries, provinces, or states). Each region has its own characteristics (spreading and recovery rates) of each service propagation. We consider that the

Paul Kremer, Hriday Bavle, Jose Luis Sanchez-Lopez, Holger Voos

Path planning is a basic capability of autonomous mobile robots. Former approaches in path planning exploit only the given geometric information from the environment without leveraging the inherent semantics within the environment. The recently presented S-Graphs constructs 3D situational graphs incorporating geometric, semantic, and relational aspects betwe

Sebastian Schäfer, François Willot, Mansoureh Norouzi Rad, Stephen T. Kelly

The properties of porous glasses and their field of application strongly depend on the characteristics of the void space. Understanding the relationship between their porous structure and failure behaviour can contribute to the development of porous glasses with long-term reliability optimized for specific applications. In the present work, we used X-ray com

Zitao Chen, Karthik Pattabiraman

Machine learning (ML) models are vulnerable to membership inference attacks (MIAs), which determine whether a given input is used for training the target model. While there have been many efforts to mitigate MIAs, they often suffer from limited privacy protection, large accuracy drop, and/or requiring additional data that may be difficult to acquire. This wo

Nikita Remnev, Sergei Obiedkov, Ekaterina Rakhilina, Ivan Smirnov

Grammatical error correction is one of the fundamental tasks in Natural Language Processing. For the Russian language, most of the spellcheckers available correct typos and other simple errors with high accuracy, but often fail when faced with non-native (L2) writing, since the latter contains errors that are not typical for native speakers. In this paper, w