November 2022 arXiv papers — page 150

Avishek Anand, Lijun Lyu, Maximilian Idahl, Yumeng Wang

Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems. Given the increasing use of complex machine learning models in search systems, explainability is essential in building and auditing responsible information retrieval models. This survey fills a vital gap in the otherwise to

Xiaoyu Geng, Qiang Guo, Shuaixiong Hui, Ming Yang

Tensor robust principal component analysis (TRPCA) is a classical way for low-rank tensor recovery, which minimizes the convex surrogate of tensor rank by shrinking each tensor singular value equally. However, for real-world visual data, large singular values represent more significant information than small singular values. In this paper, we propose a nonco

Hanna Abi Akl

In this paper, we present a new theoretical approach for enabling domain knowledge acquisition by intelligent systems. We introduce a hybrid model that starts with minimal input knowledge in the form of an upper ontology of concepts, stores and reasons over this knowledge through a knowledge graph database and learns new information through a Logic Neural Ne

Lande Ma, ZhaoKun Ma

We show two results of mean value problem, Smale's mean value problem is comprehensively solved in this paper.

Adam Skalski, Ivan G. Todorov, Lyudmila Turowska

Given two unital C*-algebras equipped with states and a positive operator in the enveloping von Neumann algebra of their minimal tensor product, we define three parameters that measure the capacity of the operator to align with a coupling of the two given states. Further we establish a duality formula that shows the equality of two of the parameters for oper

Michele Svanera, Mattia Savardi, Alberto Signoroni, Sergio Benini

Many clinical and research studies of the human brain require an accurate structural MRI segmentation. While traditional atlas-based methods can be applied to volumes from any acquisition site, recent deep learning algorithms ensure very high accuracy only when tested on data from the same sites exploited in training (i.e., internal data). The performance de

Zihao Li, Huangjun Zhu, Masahito Hayashi

This paper studies one-sided hypothesis testing under random sampling without replacement. That is, when $n+1$ binary random variables $X_1,\ldots, X_{n+1}$ are subject to a permutation invariant distribution and $n$ binary random variables $X_1,\ldots, X_{n}$ are observed, we have proposed randomized tests with a randomization parameter for the upper confid

Srishti Bhardwaj, T. Maitra

Two-dimensional multiferroic materials are highly sought after due to their huge potential for applications in nanoelectronic and spintronic devices. Here, we predict, based on first-principle calculations, a single phase {\it triferroic} where three ferroic orders; ferromagnetism, ferroelectricity and ferroelasticity, coexist simultaneously in hole doped Gd

Jean-Marie Lemercier, Julius Richter, Simon Welker, Timo Gerkmann

Diffusion-based generative models have had a high impact on the computer vision and speech processing communities these past years. Besides data generation tasks, they have also been employed for data restoration tasks like speech enhancement and dereverberation. While discriminative models have traditionally been argued to be more powerful e.g. for speech e

Shanfan Zhang, Wenjiao Zhang, Zhan Bu

Clustering is a fundamental problem in network analysis that finds closely connected groups of nodes and separates them from other nodes in the graph, while link prediction is to predict whether two nodes in a network are likely to have a link. The definition of both naturally determines that clustering must play a positive role in obtaining accurate link pr

Sarah Anderson, Boštjan Brešar, Sandi Klavžar, Kirsti Kuenzel

The orientable domination number, ${\rm DOM}(G)$, of a graph $G$ is the largest domination number over all orientations of $G$. In this paper, ${\rm DOM}$ is studied on different product graphs and related graph operations. The orientable domination number of arbitrary corona products is determined, while sharp lower and upper bounds are proved for Cartesian

Lindsey Deryckere, Seeun William Umboh

We initiate the study of online problems with set delay, where the delay cost at any given time is an arbitrary function of the set of pending requests. In particular, we study the online min-cost perfect matching with set delay (MPMD-Set) problem, which generalises the online min-cost perfect matching with delay (MPMD) problem introduced by Emek et al. (STO

Shaima Akbar, M. M Musthafa, Midhun C., Antony Joseph

The photo nuclear reaction cross section of $^{61}$Ni($\gamma$,xp) reaction have been measured by employing surrogate reaction technique. This indirect method is used for the first time to obtain the cross section of photo nuclear reaction. The compound nucleus $^{61}$Ni$^{*}$ was populated using the transfer reaction $^{59}$Co($^{6}$Li,$\alpha$) at E$_{lab}

David Sinclair

This paper compares the performance of a NN taking the output of a DCT (Discrete Cosine Transform) of an image patch with leNet for classifying MNIST hand written digits. The basis functions underlying the DCT bear a passing resemblance to some of the learned basis function of the Visual Transformer but are an order of magnitude faster to apply.

L. R. Bedin, M. Salaris, J. Anderson, M. Scalco

We present our final study of the white dwarf cooling sequence (WD CS) in the globular cluster NGC 6752. The investigation is the main goal of a dedicated Hubble Space Telescope large Program, for which all the observations are now collected. The WD CS luminosity function (LF) is confirmed to peak at m_F606W = 29.3+/-0.1, consistent within uncertainties with

Christian F. Nielsen, Robert Holtzapple, Mads M. Lund, Jeppe H. Surrow

We demonstrate experimentally that the trident process $e^-\rightarrow e^-e^+e^-$ in a strong external field, with a spatial extension comparable to the effective radiation length, is well understood theoretically. The experiment, conducted at CERN, probes values for the strong field parameter $\chi$ up to 2.4. Experimental data and theoretical expectations

Edit Mátyus, Dávid Ferenc, Péter Jeszenszki, Ádám Margócsy

Interactions in atomic and molecular systems are dominated by electromagnetic forces and the theoretical framework must be in the quantum regime. The physical theory for the combination of quantum mechanics and electromagnetism, quantum electrodynamics has been established by the mid-twentieth century, primarily as a scattering theory. To describe atoms and

Zong-Xing Xiong, Mao-Sheng Li, Zhu-Jun Zheng, Lvzhou Li

A set of orthogonal multipartite quantum states is said to be distinguishability-based genuinely nonlocal (also genuinely nonlocal, for abbreviation) if the states are locally indistinguishable across any bipartition of the subsystems. This form of multipartite nonlocality, although more naturally arising than the recently popular "strong nonlocality" in the

Ricardo Campos, Dan Petersen, Daniel Robert-Nicoud, Felix Wierstra

Over a field of characteristic zero, we show that the forgetful functor from the homotopy category of commutative dg algebras to the homotopy category of dg associative algebras is faithful. In fact, the induced map of derived mapping spaces gives an injection on all homotopy groups at any basepoint. We prove similar results both for unital and non-unital al

Xinxin Wang, Guanzhong Wang, Qingqing Dang, Yi Liu

Arbitrary-oriented object detection is a fundamental task in visual scenes involving aerial images and scene text. In this report, we present PP-YOLOE-R, an efficient anchor-free rotated object detector based on PP-YOLOE. We introduce a bag of useful tricks in PP-YOLOE-R to improve detection precision with marginal extra parameters and computational cost. As

A. Oguz Kislal, Alejandro Lancho, Giuseppe Durisi, Erik Ström

We propose a numerically efficient method for evaluating the random-coding union bound with parameter $s$ on the error probability achievable in the finite-blocklength regime by a pilot-assisted transmission scheme employing Gaussian codebooks and operating over a memoryless block-fading channel. Our method relies on the saddlepoint approximation, which, dif

Alex Kehagias, Davide Perrone, Antonio Riotto

We show that the linear perturbations of any spin field in the near-zone limit of the Kerr black hole are identical to those of an AdS$_2$ black hole which enjoys the same basic properties of the Kerr black hole. Thanks to this identification, we calculate the spectrum of the quasinormal modes and the Love numbers of Kerr black holes using an AdS$_2$/CFT$_1$

Martin Modrák, Angie H. Moon, Shinyoung Kim, Paul Bürkner

Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a new variant of SBC to alleviate several known problems. Our variant allows the user to in principle detect any possible issue with the posterior, while previously reported impleme

Markus Weißenhofer, Hannah Lange, Akashdeep Kamra, Sergiy Mankovsky

In the spirit of multi-scale modeling, we develop a theoretical framework for spin-lattice coupling that connects, on the one hand, to ab initio calculations of spin-lattice coupling parameters and, on the other hand, to the magneto-elastic continuum theory. The derived Hamiltonian describes a closed system of spin and lattice degrees of freedom and explicit

Fabio Rigat

Prior probabilities of clinical hypotheses are not systematically used for clinical trial design yet, due to a concern that poor priors may lead to poor decisions. To address this concern, a conservative approach to Bayesian trial design is illustrated here, requiring that the operational characteristics of the primary trial outcome are stronger than the pri

Thomas Leistner, Thomas Munn

We show that a compact Lorentzian locally symmetric space is geodesically complete if the Lorentzian factor in the local de Rham-Wu decomposition is of Cahen-Wallach type or if the maximal flat factor is one-dimensional and time-like. Our proof uses a recent result by Mehidi and Zeghib and an earlier result by Romero and S\'{a}nchez.

Saikat Bhattacharjee, Piyasi Biswas, Ashish Gupta, M. K. Pradhan

Elastic scattering angular distribution for weakly bound nucleus $^{6}$Li on the deformed rare earth $^{159}$Tb target nucleus has been measured at energies around the Coulomb barrier. The elastic scattering cross sections for this reaction consist of inelastic contributions from low lying excited states of $^{159}$Tb. The pure elastic cross-sections have be

Simran Preet Kaur, Manojit Ghose, Ananya Pathak, Rutuja Patole

Network-on-Chips (NoCs) have been widely employed in the design of multiprocessor system-on-chips (MPSoCs) as a scalable communication solution. NoCs enable communications between on-chip Intellectual Property (IP) cores and allow those cores to achieve higher performance by outsourcing their communication tasks. Mapping and Scheduling methodologies are key

Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos

Recent advances in coreset methods have shown that a selection of representative datapoints can replace massive volumes of data for Bayesian inference, preserving the relevant statistical information and significantly accelerating subsequent downstream tasks. Existing variational coreset constructions rely on either selecting subsets of the observed datapoin

Seungjae Lee, Ji-hoon Kim, Boon Kiat Oh

Stars that are tidally disrupted by the massive black hole (MBH) may contribute significantly to the growth of the MBH, especially in dense nuclear star clusters (NSCs). Yet, this tidal disruption accretion (TDA) of stars onto the MBH has largely been overlooked compared to the gas accretion (GA) channel in most numerical experiments until now. In this work,

Francesca Cairoli, Nicola Paoletti, Luca Bortolussi

We consider the problem of predictive monitoring (PM), i.e., predicting at runtime the satisfaction of a desired property from the current system's state. Due to its relevance for runtime safety assurance and online control, PM methods need to be efficient to enable timely interventions against predicted violations, while providing correctness guarantees. We

Hiroyuki Kitahata, Alexander S. Mikhailov

A novel mechanism of reaction-induced active molecular motion, not involving any kind of self-propulsion, is proposed and analyzed. Because of the momentum exchange with the surrounding solvent, conformational transitions in mechano-chemical enzymes are accompanied by motions of their centers of mass. As we show, in combination with rotational diffusion, suc

Sotatsu Otabe, Kentaro Komori, Ken-ichi Harada, Kaido Suzuki

Intracavity squeezing is a promising technique that may improve the sensitivity of gravitational wave detectors and cool optomechanical oscillators to the ground state. However, the photothermal effect may modify the occurrence of optomechanical coupling due to the presence of a nonlinear optical crystal in an optical cavity. We propose a novel method to pre

Cem Alpturk, Venkatraman Renganathan

We investigate the problem of risk averse robot path planning using the deep reinforcement learning and distributionally robust optimization perspectives. Our problem formulation involves modelling the robot as a stochastic linear dynamical system, assuming that a collection of process noise samples is available. We cast the risk averse motion planning probl

Alison C Hale, Jonathan M Read, Christopher P Jewell

In regard to infectious diseases socioeconomic determinants are strongly associated with differential exposure and susceptibility however they are seldom accounted for by standard compartmental infectious disease models. These associations are explored here with a novel compartmental infectious disease model which, stratified by deprivation and age, accounts

Davide Vadacchino, Ed Bennett, C. -J. David Lin, Deog Ki Hong

In this contribution, we report on our study of the properties of the Wilson flow and on the calculation of the topological susceptibility of $Sp(N_c)$ gauge theories for $N_c=2,\,4,\,6,\,8$. The Wilson flow is shown to scale according to the quadratic Casimir operator of the gauge group, as was already observed for $SU(N_c)$, and the commonly used scales $t

Tatsuya Chuman, Hitoshi Kiya

Privacy-preserving deep neural networks (DNNs) have been proposed for protecting data privacy in the cloud server. Although several encryption schemes for visually protection have been proposed for privacy-preserving DNNs, several attacks enable to restore visual information from encrypted images. On the other hand, it has been confirmed that the block-wise

Fabian Mies, Ansgar Steland

Analyzing large samples of high-dimensional data under dependence is a challenging statistical problem as long time series may have change points, most importantly in the mean and the marginal covariances, for which one needs valid tests. Inference for large covariance matrices is especially difficult due to noise accumulation, resulting in singular estimate

A. Ciach, O. Patsahan

Recently, underscreening in concentrated electrolytes was discovered in experiments and confirmed in simulations and theory. It was found that the correlation length of the charge-charge correlations, $\lambda_s$, satisfies the scaling relation $\lambda_s/\lambda_D\sim (a/\lambda_D)^n$, where $\lambda_D$ is the Debye screening length and $a$ is the ionic dia

A. Arezzo, S. Berretti

In recent years, Speech Emotion Recognition (SER) has been investigated mainly transforming the speech signal into spectrograms that are then classified using Convolutional Neural Networks pretrained on generic images and fine tuned with spectrograms. In this paper, we start from the general idea above and develop a new learning solution for SER, which is ba

S. Akshay, Hugo Bazille, Blaise Genest, Mihir Vahanwala

The Skolem problem is a long-standing open problem in linear dynamical systems: can a linear recurrence sequence (LRS) ever reach 0 from a given initial configuration? Similarly, the positivity problem asks whether the LRS stays positive from an initial configuration. Deciding Skolem (or positivity) has been open for half a century: the best known decidabili

Alison C. Hale, Charlotte Appleton, P. -J. M. Noble, Gina L. Pinchbeck

Confronted by a rapidly evolving health threat, such as an infectious disease outbreak, it is essential that decision-makers are able to comprehend the complex dynamics not just in space but also in the 4th dimension, time. In this paper this is addressed by a novel visualisation tool, referred to as the Dynamic Health Atlas web app, which is designed specif

Lukas Pensel, Stefan Kramer

Multi-relational databases are the basis of most consolidated data collections in science and industry today. Most learning and mining algorithms, however, require data to be represented in a propositional form. While there is a variety of specialized machine learning algorithms that can operate directly on multi-relational data sets, propositionalization al

L. B. Drissi, S. Lounis, E. H. Saidi

We develop a chiral anomalous fermion hamiltonian proposal to study the higher order topological (HOT) phase with chiral symmetry $\mathcal{C}$ fractionalized like $\mathcal{C}_{x}\mathcal{C}_{y}\mathcal{C}_{z}$. First, we solve the $\mathcal{C}$-chiral symmetry constraint for eight band models and describe those induced by the partial $\mathcal{C}_{i}$'s. T

Fuminori Honda, Shintaro Kobayashi, Naomi Kawamura, Saori Kawaguchi

We report on the crystal structure and electronic properties of the heavy fermion superconductor UTe2 at high pressure up to 11 GPa, as investigated by X-ray diffraction and electrical resistivity experiments. The X-ray diffraction measurements under high pressure using a synchrotron light source reveal anisotropic linear compressibility of the unit cell up

Takuya Morozumi, Apriadi Salim Adam, Yuta Kawamura, Albertus Hariwangsa Panuluh

We study the quark sector of the universal seesaw model with SU(2)$_L$ $\times$ SU(2)$_R$ $\times$ $U(1)$.The model incorporates the seesaw mechanism with the vector-like quarks (VLQs). The purpose of this work is to study the model with the effective theory. After integrating the heavy five VLQs, we derive the effective theory with four up-type quark and th

Albertus Hariwangsa Panuluh, Takuya Morozumi

Universal Seesaw Model is a model which explains the mass hierarchy of the quark sector. This model introduces vector-like quarks. The top quark mass is generated in the electroweak scale and the other quark mass is generated using a seesaw-like mechanism. The invariant theory helps construct a weak-basis invariant. We study the weak-basis invariant (WBI) us

Alison C Hale, Christopher P Jewell

An approach is introduced for comparing the estimated states of stochastic compartmental models for an epidemic or biological process with analytically obtained solutions from the corresponding system of ordinary differential equations (ODEs). Positive integer valued samples from a stochastic model are generated numerically at discrete time intervals using e

Patrice Ballester

The event questions men whether it is political, cultural or touristic. It has its own meaning as it starts something while showing a will, a new possibility to create, to meet and to surprise. The event is in fact an "advent that reaches everything" generally integrating itself into a long process or phase of the evolution of societies in terms of its socie

Antoine Aamarcha, Martin Caussanel, Hadrien Lanneau, Kevin Mege

Our work is at the crossroads of two categories of technologies. On the one hand, omnichannel digit services, to address the needs of users in the most seamless way. On the other hand, low code approaches, to build simply even complex software applications. In this twofold context, we propose DSUL (Digital Service Universal Language). It allows to build omni

Jona Maurer, Nicolai Tschuch, Stefan Krebs, Kankar Bhattacharya

Although electric power networks and district heating networks are physically coupled, they are not operated in a coordinated manner. With increasing penetration of renewable energy sources, a coordinated market-based operation of the two networks can yield significant advantages, as reduced need for grid reinforcements, by optimizing the power flows in the

Jeffrey Liu, Rajat Tandon, Uma Durairaj, Jiani Guo

YouTube is a popular video platform for sharing creative content and ideas, targeting different demographics. Adults, older children, and young children are all avid viewers of YouTube videos. Meanwhile, countless young-kid-oriented channels have produced numerous instructional and age appropriate videos for young children. However, inappropriate content for

Ercüment H. Ortaçgil

Using irreducible representations of semi simple Lie algebras, we construct Klein geometries of arbitrarily high order.

Tie Liu, Yuhong Fan, Yingna Su, Yang Guo

The separation of a filament and sigmoid is observed during an X1.4 flare on July 12, 2012 in solar active region 11520, but the corresponding magnetic field change is not clear. We construct a data-constrained magnetohydrodynamic simulation of the filament-sigmoid system with the flux rope insertion method and magnetic flux eruption code, which produces the

Gourab Kumar Sar, Dibakar Ghosh, Kevin O'Keeffe

We study a population of swarmalators (swarming/mobile oscillators) which run on a ring and are subject to random pinning. The pinning represents the tendency of particles to stick to defects in the underlying medium which competes with the tendency to sync / swarm. The result is rich collective behavior. A highlight is low dimensional chaos which in systems

Sakshi Chhabra, Ashutosh Kumar Singh

The cloud datacenter has numerous hosts as well as application requests where resources are dynamic. The demands placed on the resource allocation are diverse. These factors could lead to load imbalances, which affect scheduling efficiency and resource utilization. A scheduling method called Dynamic Resource Allocation for Load Balancing (DRALB) is proposed.

Alexandra Hadar, Natan Levy, Michael Winokur

Retained surgical bodies (RSB) are any foreign bodies left inside the patient after a medical procedure. RSB is often caused by human mistakes or miscommunication between medical staff during the procedure. Infection, medical complications, and even death are possible consequences of RSB, and it is a significant risk for patients, hospitals, and surgical sta

Fabio Carrara, Fabrizio Falchi, Maria Girardi, Nicola Messina

Thanks to recent advancements in numerical methods, computer power, and monitoring technology, seismic ambient noise provides precious information about the structural behavior of old buildings. The measurement of the vibrations produced by anthropic and environmental sources and their use for dynamic identification and structural health monitoring of buildi

Seyon Sivarajah, Lukas Heidemann, Alan Lawrence, Ross Duncan

We present Tierkreis, a higher-order dataflow graph program representation and runtime designed for compositional, quantum-classical hybrid algorithms. The design of the system is motivated by the remote nature of quantum computers, the need for hybrid algorithms to involve cloud and distributed computing, and the long-running nature of these algorithms. The

Geoffroy Horel

We produce a fully faithful functor from finite type nilpotent spaces to cosimplicial binomial rings, thus giving an algebraic model of integral homotopy types. As an application, we construct an integral version of the Grothendieck-Teichm\"uller group.

Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello

Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to support a wide variety of important applications. However, collaboration between these actors is difficult due to the heterogeneous nature of geospatial data modalities (e.g., multi-spectral images of various resolutions, timeserie

Wan-Ting Hsieh, Jeremy Lefort-Besnard, Hao-Chun Yang, Li-Wei Kuo

The ability to accurately detect onset of dementia is important in the treatment of the disease. Clinically, the diagnosis of Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) patients are based on an integrated assessment of psychological tests and brain imaging such as positron emission tomography (PET) and anatomical magnetic resonance imaging (M

X. X. Ren, B. Liu, Xian Zhang, Ping Li

Magnetic tunnel junction (MTJ) based on van der Waals (vdW) magnetic layers has been found to present excellent tunneling magnetoresistance (TMR) property, which has great potential applications in field sensing, non-volatile magnetic random access memories, and spin logics. Although MTJs composed of multilayer vdW magnetic homojunction have been extensively

Chris Jones, Karoline Wiesner

Mean field theory models of percolation on networks provide analytic estimates of network robustness under node or edge removal. We introduce a new mean field theory model based on generating functions that includes information about the tree-likeness of each node's local neighbourhood. We show that our new model outperforms all other generating function mod

Subhroneel Chakrabarti, Divyanshu Gupta, Arkajyoti Manna

AdS/CFT predicts that the value of the on-shell action for type IIB Supergravity (SUGRA) on $AdS_5 \times S^5$ background must be a non-zero number completely determined from the boundary theory. We examine this statement within Sen's formalism for type IIB SUGRA and find that consistency with AdS/CFT requires us to add a specific boundary term to the action

Mousomi Bhakta, Kanishka Perera, Firoj Sk

This paper deals with existence of solutions to the following fractional $p$-Laplacian system of equations \begin{equation*} %\tag{$\mathcal P$}\label{MAT1} \begin{cases} (-\Delta_p)^s u =|u|^{p^*_s-2}u+ \frac{\gamma\alpha}{p_s^*}|u|^{\alpha-2}u|v|^{\beta}\;\;\text{in}\;\Omega, (-\Delta_p)^s v =|v|^{p^*_s-2}v+ \frac{\gamma\beta}{p_s^*}|v|^{\beta-2}v|u|^{\alp

Shilpa Mohanakumar, Namkyu Lee, Simone Wiegand

In recent years, thermophoresis has emerged as a promising tool for quantifying biomolecular interactions. The underlying physical effect is still not understood. To gain deeper insight, we investigate whether non-equilibrium coefficients can be related to equilibrium properties. Therefore, we compare thermophoretic data measured by thermal diffusion forced

Soumyadip Das

We completely characterize the covers of connected orbifold curves which preserve slope stability of vector bundles under the pullback morphism. More precisely, given a cover $f \colon (Y,Q) \longrightarrow (X,P)$ of connected orbifold curves, we show that the maximal destabilizing sub-bundle of the pushforward sheaf $f_*\mathcal{O}_{(Y,Q)}$ defines the maxi

Partha Das Chowdhury, Mohammad Tahaei, Awais Rashid

Saltzer \& Schroeder's principles aim to bring security to the design of computer systems. We investigate SolarWinds Orion update and Log4j to unpack the intersections where observance of these principles could have mitigated the embedded vulnerabilities. The common principles that were not observed include \emph{fail safe defaults}, \emph{economy of mechani

Lattice Parton Collaboration, Jin-Chen He, Min-Huan Chu, Jun Hua

We present a first lattice QCD calculation of the unpolarized nucleon's isovector transverse-momentum-dependent parton distribution functions (TMDPDFs), which are essential to predict observables of multi-scale, semi-inclusive processes in the standard model. We use a $N_f=2+1+1$ MILC ensemble with valence clover fermions on a highly improved staggered quark

A. Zabrodin

We define the Dyson diffusion process on a curved smooth closed contour in the plane and derive the Fokker-Planck equation for probability density. Its stationary solution is shown to be the Boltzmann weight for the logarithmic gas confined on the contour.

Qinghong Zhao, Bing Wei

For two given graphs $F$ and $H$, the Ramsey number $R(F,H)$ is the smallest integer $N$ such that any red-blue edge-coloring of the complete graph $K_N$ contains a red $F$ or a blue $H$. When $F=H$, we simply write $R_2(H)$. For an positive integer $n$, let $K_{1,n}$ be a star with $n+1$ vertices, $F_n$ be a fan with $2n+1$ vertices consisting of $n$ triang

Wenhe Jia, Yilin Zhou, Xuhan Zhu, Mengjie Hu

Dense pose estimation is a dense 3D prediction task for instance-level human analysis, aiming to map human pixels from an RGB image to a 3D surface of the human body. Due to a large amount of surface point regression, the training process appears to be easy to collapse compared to other region-based human instance analyzing tasks. By analyzing the loss formu

Detai Xin, Sharath Adavanne, Federico Ang, Ashish Kulkarni

We present a multi-speaker Japanese audiobook text-to-speech (TTS) system that leverages multimodal context information of preceding acoustic context and bilateral textual context to improve the prosody of synthetic speech. Previous work either uses unilateral or single-modality context, which does not fully represent the context information. The proposed me

Karina Arias-Calluari, Theotime Colin, Tanya Latty, Mary Myerscough

A quantitative understanding of the dynamics of bee colonies is important to support global efforts to improve bee health and enhance pollination services. Traditional approaches focus either on theoretical models or data-centred statistical analyses. Here we argue that the combination of these two approaches is essential to obtain interpretable information

Wibson W. G. Silva, A. R. Rodrigues, José Holanda

The spin Hall effect is one of the most relevant effects in spintronics and the key to conversion from charge current into spin current. We report here a phenomenon, which appears in response to the spin Hall effect and represents the anti-polarization of the spin current due to the coupling between interfacial magnetic anisotropies. Such an effect produces

Yusuke Shinohara, Shinji Watanabe

Sequence transducers, such as the RNN-T and the Conformer-T, are one of the most promising models of end-to-end speech recognition, especially in streaming scenarios where both latency and accuracy are important. Although various methods, such as alignment-restricted training and FastEmit, have been studied to reduce the latency, latency reduction is often a

Hsuan-Jui Chen, Yen Meng, Hung-yi Lee

The sequence length along the time axis is often the dominant factor of the computation in speech processing. Works have been proposed to reduce the sequence length for lowering the computational cost in self-supervised speech models. However, different downstream tasks have different tolerance of sequence compressing, so a model that produces a fixed compre

Eiichi Bannai, Etsuko Bannai, Chin-Yen Lee, Ziqing Xiang

Finding the maximum cardinality of a $2$-distance set in Euclidean space is a classical problem in geometry. Lison\v{e}k in 1997 constructed a maximum $2$-distance set in $\mathbb R^8$ with $45$ points. That $2$-distance set constructed by Lison\v{e}k has a distinguished structure of a coherent configuration of type $(2,2;3)$ and is embedded in two concentri

Kalev Alpernas, Aurojit Panda, Mooly Sagiv

Elastic scaling is one of the central benefits provided by serverless platforms, and requires that they scale resource up and down in response to changing workloads. Serverless platforms scale-down resources by terminating previously launched instances (which are containers or processes). The serverless programming model ensures that terminating instances is

Daniele Bartoli, Matteo Bonini, Marco Timpanella

In this paper, we consider the affine variety codes obtained evaluating the polynomials $by=a_kx^k+\dots+a_1x+a_0$, $b,a_i\in\mathbb{F}_{q^r}$, at the affine $\F_{q^r}$-rational points of the Norm-Trace curve. In particular, we investigate the weight distribution and the set of minimal codewords. Our approach, which uses tools of algebraic geometry, is based

Lukas Körber, Christopher Heins, Tobias Hula, Joo-Von Kim

Magnons are elementary excitations in magnetic materials and undergo nonlinear multimode scattering processes at large input powers. In experiments and simulations, we show that the interaction between magnon modes of a confined magnetic vortex can be harnessed for pattern recognition. We study the magnetic response to signals comprising sine wave pulses wit

M. Barbisan, B. Zaniol, R. Pasqualotto

A test facility for the development of the Neutral Beam Injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H-/D- ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance o

John Bamberg, Michael Giudici, Jesse Lansdown, Gordon F. Royle

We classify, up to some notoriously hard cases, the rank 3 graphs which fail to meet either the Delsarte or the Hoffman bound. As a consequence, we resolve the question of separation for the corresponding rank 3 primitive groups and give new examples of synchronising, but not $\mathbb{Q}\mathrm{I}$, groups of affine type.

H Freytes

Algebraic quantum field theory, or AQFT for short, is a rigorous analysis of the structure of relativistic quantum mechanics. It is formulated in terms of a net of operator algebras indexed by regions of a Lorentzian manifold. In several cases the mentioned net is represented by a family of von Neumann algebras, concretely, type III factors. Local quantum fi

Vishal Upendran, Durgesh Tripathi, N. P. S. Mithun, Santosh Vadawale

The existence of the million-degree corona above the cooler photosphere is an unsolved problem in astrophysics. Detailed study of quiescent corona that exists regardless of the phase of the solar cycle may provide fruitful hints towards resolving this conundrum. However, the properties of heating mechanisms can be obtained only statistically in these regions

Zuohai Jiang, Lingling Kong, Shicheng Xu

It is known that a closed collapsed Riemannian $n$-manifold $(M,g)$ of bounded Ricci curvature and Reifenberg local covering geometry admits a nilpotent structure in the sense of Cheeger-Fukaya-Gromov with respect to a smoothed metric $g(t)$. We prove that a canonical nilpotent structure over a regular limit space that describes the collapsing of original me

Guangyu Wu, Anders Lindquist

This paper considers the problem of steering an arbitrary initial probability density function to an arbitrary terminal one, where the system dynamics is governed by a first-order linear stochastic difference equation. It is a generalization of the conventional stochastic control problem where the uncertainty of the system state is usually characterized by a

Bo Wang, Zhao Zhang, Mingbo Zhao, Xiaojie Jin

Mainstream image caption models are usually two-stage captioners, i.e., calculating object features by pre-trained detector, and feeding them into a language model to generate text descriptions. However, such an operation will cause a task-based information gap to decrease the performance, since the object features in detection task are suboptimal representa

Jingchang Zhuge, Huiyuan Liang, Yiming Zhang, Shichao Li

Aircraft taxiing conflict is a threat to the safety of airport operations, mainly due to the human error in control command infor-mation. In order to solve the problem, The aircraft taxiing deduction and conflict early warning method based on control order information is proposed. This method does not need additional equipment and operating costs, and is com

Rémi Abgrall

Computing the distance function to some surface or line is a problem that occurs very frequently. There are several ways of computing a relevant approximation of this function, using for example technique originating from the approximation of Hamilton Jacobi problems, or the fast sweeping method. Here we make a link with some elliptic problem and propose a v

Umesh V Dubey, Gopinath Sahoo

We give a condition which characterises those weight structures on a derived category which come from a Thomason filtration on the underlying scheme. Weight structures satisfying our condition will be called $\otimes ^c$-weight structures. More precisely, for a Noetherian separated scheme $X$, we give a bijection between the set of compactly generated $\otim

Romain Abraham, Jean-François Delmas, Michel Nassif

We study the maximal degree of (sub)critical L{\'e}vy trees which arise as the scaling limits of Bienaym{\'e}-Galton-Watson trees. We determine the genealogical structure of large nodes and establish a Poissonian decomposition of the tree along those nodes. Furthermore, we make sense of the distribution of the L{\'e}vy tree conditioned to have a fixed maxima

Guillaume Dujardin, Ingrid Lacroix-Violet, Anthony Nahas

This article introduces a new numerical method for the minimization under constraints of a discrete energy modeling multicomponents rotating Bose-Einstein condensates in the regime of strong confinement and with rotation. Moreover, we consider both segregation and coexistence regimes between the components. The method includes a discretization of a continuou

Yiheng Liu, Enjie Ge, Ning Qiang, Tianming Liu

Using functional magnetic resonance imaging (fMRI) and deep learning to explore functional brain networks (FBNs) has attracted many researchers. However, most of these studies are still based on the temporal correlation between the sources and voxel signals, and lack of researches on the dynamics of brain function. Due to the widespread local correlations in

Tabea Rebafka

The paper tackles the problem of clustering multiple networks, directed or not, that do not share the same set of vertices, into groups of networks with similar topology. A statistical model-based approach based on a finite mixture of stochastic block models is proposed. A clustering is obtained by maximizing the integrated classification likelihood criterio

Hanyi Hu, Long Zhang, Shuan Li, Zhi Liu

Financial frauds cause billions of losses annually and yet it lacks efficient approaches in detecting frauds considering user profile and their behaviors simultaneously in social network . A social network forms a graph structure whilst Graph neural networks (GNN), a promising research domain in Deep Learning, can seamlessly process non-Euclidean graph data

Dennis Schol, Maria Vlasiou, Bert Zwart

In this paper, we study the maximum waiting time $\max_{i\leq N}W_i(\cdot)$ in an $N$-server fork-join queue with heavy-tailed services as $N\to\infty$. The service times are the product of two random variables. One random variable has a regularly varying tail probability and is the same among all $N$ servers, and one random variable is Weibull distributed a

Anatoly Zhigljavsky, Jack Noonan

Let $(\mathcal{X},\rho)$ be a metric space and $\lambda$ be a Borel measure on this space defined on the $\sigma$-algebra generated by open subsets of $\mathcal{X}$; this measure $\lambda$ defines volumes of Borel subsets of $\mathcal{X}$. The principal case is where $\mathcal{X} = \mathbb{R}^d$, $\rho $ is the Euclidean metric, and $\lambda$ is the Lebesgue

Sanemichi Z. Takahashi, Eiichiro Kokubo, Shu-ichiro Inutsuka

We investigate the gravitational instability (GI) of dust-ring structures and the formation of planetesimals by their gravitational collapse. The normalized dispersion relation of a self-gravitating ring structure includes two parameters that are related to its width and line mass (the mass per unit length). We survey these parameters and calculate the growt