March 2023 arXiv papers — page 73

Obinna Abah, Collins O. Edet, Norshamsuri Ali, Berihu Teklu

We investigate the role of nonlinearity via optical parametric oscillator on the entropy production rate and quantum correlations in a hybrid optomechanical system. Specifically, we derive the modified entropy production rate of an optical parametric oscillator placed in the optomechanical cavity which is well described by the two-mode Gaussian state. We fin

Rinrada Jadsadaphongphaibool, Dadi Bi, Yansha Deng

The design and engineering of molecular communication (MC) components capable of processing chemical concentration signals is the key to unleashing the potential of MC for interdisciplinary applications. By controlling the signaling pathway and molecule exchange between cell devices, synthetic biology provides the MC community with tools and techniques to ac

W. E. V. Barker, M. P. Hobson, A. N. Lasenby

The short answer is $\textit{probably no}$. Specifically, this paper considers a recent body of work which suggests that general relativity requires neither the support of dark matter halos, nor unconventional baryonic profiles, nor any infrared modification, to be consistent after all with the anomalously rapid orbits observed in many galactic discs. In par

Francesco Bonaldi, Daniele A. Di Pietro, Jerome Droniou, Kaibo Hu

We develop in this work the first polytopal complexes of differential forms. These complexes, inspired by the Discrete De Rham and the Virtual Element approaches, are discrete versions of the de Rham complex of differential forms built on meshes made of general polytopal elements. Both constructions benefit from the high-level approach of polytopal methods,

Pablo Montero de Hijes, Salvatore Romano, Alexander Gorfer, Christoph Dellago

Molecular simulations employing empiric force fields have provided valuable knowledge about the ice growth process in the last decade. The development of novel computational techniques allows us to study this process, which requires long simulations of relatively large systems, with ab initio accuracy. In this work, we use a neural-network potential for wate

Jessica L. Ramsay, Daniel R. Kattnig

A popular hypothesis ascribes magnetoreception to a magnetosensitive recombination reaction of a pair of radicals in the protein cryptochrome. Many theoretical studies of this model have ignored inter-radical interactions, particularly the electron-electron dipolar coupling (EED), which have a detrimental effect on the magnetosensitivity. Here, we set out to

Jewel K. Ghosh, Elias Kiritsis, Francesco Nitti, Valentin Nourry

Classical gravity coupled to a CFT$_4$ (matter) is considered. The effect of the quantum dynamics of matter on gravity is studied around maximally symmetric spaces (flat, de Sitter and Anti de Sitter). The structure of the graviton propagator is modified and non-trivial poles appear due to matter quantum effects. The position and residues of such poles are m

Guoliang Wang, Yanlei Shang, Yong Chen

A critical challenge to image-text retrieval is how to learn accurate correspondences between images and texts. Most existing methods mainly focus on coarse-grained correspondences based on co-occurrences of semantic objects, while failing to distinguish the fine-grained local correspondences. In this paper, we propose a novel Scene Graph based Fusion Networ

Ziqiao Peng, Haoyu Wu, Zhenbo Song, Hao Xu

Speech-driven 3D face animation aims to generate realistic facial expressions that match the speech content and emotion. However, existing methods often neglect emotional facial expressions or fail to disentangle them from speech content. To address this issue, this paper proposes an end-to-end neural network to disentangle different emotions in speech so as

Sören Henning, Wilhelm Hasselbring

Context: The combination of distributed stream processing with microservice architectures is an emerging pattern for building data-intensive software systems. In such systems, stream processing frameworks such as Apache Flink, Apache Kafka Streams, Apache Samza, Hazelcast Jet, or the Apache Beam SDK are used inside microservices to continuously process massi

Yinuo Noah Yao, Perry Harabin, Morad Behandish, Ilenia Battiato

Accurate analytical and numerical modeling of multiscale systems is a daunting task. The need to properly resolve spatial and temporal scales spanning multiple orders of magnitude pushes the limits of both our theoretical models as well as our computational capabilities. Rigorous upscaling techniques enable efficient computation while bounding/tracking error

Peipei Li, Rui Wang, Huaibo Huang, Ran He

Face aging is an ill-posed problem because multiple plausible aging patterns may correspond to a given input. Most existing methods often produce one deterministic estimation. This paper proposes a novel CLIP-driven Pluralistic Aging Diffusion Autoencoder (PADA) to enhance the diversity of aging patterns. First, we employ diffusion models to generate diverse

M. R. Xie, J. G. Li, N. Michel, H. H. Li

Spectroscopic factors involving well bound nucleons in light nuclei are calculated with standard shell model, no-core shell model and Gamow shell model. Continuum coupling is included exactly in the Gamow shell model, due to the use of the Berggren basis, which contains bound, resonance and scattering states. Conversely, it is absent from standard and no-cor

Guangyu Wu, Anders Lindquist

Spectral density estimation is a core problem of system identification, which is an important research area of system control and signal processing. There have been numerous results on the design of spectral density estimators. However to our best knowledge, quantitative error analyses of the spectral density estimation have not been proposed yet. In real pr

Yun Wang, Zi-Qing Xia, Tian-Ci Zheng, Jia Ren

GRB 230307A is one of the brightest gamma-ray bursts detected so far. With the excellent observation of GRB 230307A by Fermi-GBM, we can reveal the details of prompt emission evolution. As found in high-time-resolution spectral analysis, the early low-energy spectral indices ($\alpha$) of this burst exceed the limit of synchrotron radiation ($\alpha=-2/3$),

Blerta Veseli, Sneha Singhania, Simon Razniewski, Gerhard Weikum

Structured knowledge bases (KBs) are a foundation of many intelligent applications, yet are notoriously incomplete. Language models (LMs) have recently been proposed for unsupervised knowledge base completion (KBC), yet, despite encouraging initial results, questions regarding their suitability remain open. Existing evaluations often fall short because they

Lianyu Wang, Meng Wang, Daoqiang Zhang, Huazhu Fu

As scientific and technological advancements result from human intellectual labor and computational costs, protecting model intellectual property (IP) has become increasingly important to encourage model creators and owners. Model IP protection involves preventing the use of well-trained models on unauthorized domains. To address this issue, we propose a nov

Jens Hoppe

By direct, elementary, considerations it is shown that the SU(2) x SO(d=2,3) invariant sector of the bosonic membrane matrix model is governed by (two, resp. three-dimensional) x^2 y^2 models

Lorenzo Laneve

Quantum Signal Processing (QSP) is a technique that can be used to implement a polynomial transformation $P(x)$ applied to the eigenvalues of a unitary $U$, essentially implementing the operation $P(U)$, provided that $P$ satisfies some conditions that are easy to satisfy. A rich class of previously known quantum algorithms were shown to be derived or reduce

Saffron Huang, Divya Siddarth

Many generative foundation models (or GFMs) are trained on publicly available data and use public infrastructure, but 1) may degrade the "digital commons" that they depend on, and 2) do not have processes in place to return value captured to data producers and stakeholders. Existing conceptions of data rights and protection (focusing largely on individually-

René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, Stella Graßhof

Denoising Diffusion Models (DDMs) have emerged as a strong competitor to Generative Adversarial Networks (GANs). However, despite their widespread use in image synthesis and editing applications, their latent space is still not as well understood. Recently, a semantic latent space for DDMs, coined `$h$-space', was shown to facilitate semantic image editing i

Kazumi Fukushima, Keito Obata, Soichiro Yamane, Yajian Hu

Superconductivity is caused by electron pairs that are canonically isotropic, whereas some exotic superconductors are known to exhibit non-trivial anisotropy stemming from unconventional pairings. However, superconductors with hexagonal symmetry, the highest rotational symmetry allowed in crystals, exceptionally have strong constraint that is called emergent

Jiří Adámek, Stefan Milius, Lawrence S. Moss

We present a collection of results that imply that an endofunctor on a category has a terminal coalgebra obtainable as a countable limit of its terminal-coalgebra chain. This holds for finitary endofunctors on locally finitely presentable categories under conditions on both the functor and the category. We adapt finiteness arguments that were originally adva

Yusuke Shimizu, Shonosuke Takeshita

We propose an SU(5) GUT model extended with two additional pairs of $\mathbf{10}$ representation vector-like fermions. The CDF collaboration $W$ boson mass anomaly is explained by using the VEV of a real $\mathrm{SU(2)_L}$ triplet scalar coming from the $\mathbf{24}$ representation Higgs. The vector-like fermions are decomposed partly into vector-like quark

Ivan Izmestiev, Roman Prosanov, Tianqi Wu

Let $S$ be the 2-sphere and $V \subset S$ be a finite set of at least three points. We show that for each function $\kappa: V \rightarrow (0, 2\pi)$ satisfying elementary necessary conditions, in each discrete conformal class of spherical cone-metrics there exists a unique metric realizing $\kappa$ as its discrete curvature. This can be seen as a discrete ve

Thakur Meenakshi, R. P. Sharma

Let $A$ be an additively cancellative semialgebra over an additively cancellative semifield $K$ as defined in [9]. For a given partial action $\alpha$ of a group $G$ on an algebra, the associativity of partial skew group ring together with the existence and uniqueness of enveloping (global) action were studied by M. Dokuchaev and R. Exel [2] which were exten

Wasim Akram, Debanjana Mitra, Neela Nataraj, Mythily Ramaswamy

In the first part of this article, we study feedback stabilization of a parabolic coupled system by using localized interior controls. The system is feedback stabilizable with exponential decay $-\omega<0$ for any $\omega>0$. A stabilizing control is found in feedback form by solving a suitable algebraic Riccati equation. In the second part, a conforming fin

Yuhao Chen, Xin Tan, Borui Zhao, Zhaowei Chen

Semi-supervised learning (SSL) has attracted enormous attention due to its vast potential of mitigating the dependence on large labeled datasets. The latest methods (e.g., FixMatch) use a combination of consistency regularization and pseudo-labeling to achieve remarkable successes. However, these methods all suffer from the waste of complicated examples sinc

Francesc Sabanés Zariquiey, Adrià Pérez, Maciej Majewski, Emilio Gallicchio

The accurate prediction of protein-ligand binding affinities is crucial for drug discovery. Alchemical free energy calculations have become a popular tool for this purpose. However, the accuracy and reliability of these methods can vary depending on the methodology. In this study, we evaluate the performance of a relative binding free energy protocol based o

Raffaele Mattera, Philipp Otto

This paper presents a novel dynamic network autoregressive conditional heteroscedasticity (ARCH) model based on spatiotemporal ARCH models to forecast volatility in the US stock market. To improve the forecasting accuracy, the model integrates temporally lagged volatility information and information from adjacent nodes, which may instantaneously spill across

Shunda Zhang, Jiachang Bi, Ruyi Zhang, Peiyi Li

Clarifying the electronic and magnetic properties of lutetium, lutetium dihydride, and lutetium oxide is very helpful to understand the emergent phenomena in lutetium-based compounds (such as room-temperature superconductivity). However, this kind of study is still scarce at present. Here, we report on the electronic and magnetic properties of lutetium metal

Khristine Haydukivska, Viktoria Blavatska, Jaroslaw Paturej

We study conformational properties of diluted dumbbell polymers which consist of two rings that are attached to both ends of a linear spacer segment by using analytical methods of field theory and bead-spring coarse-grained molecular dynamics simulations. We investigate the influence of the relative length of the spacer segment to the length of side rings on

Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer

We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. In doing so, we use the Lipschitz constant of the input-output mapping characterized by a CNN as a robustness measure. We base our parameterization on the Cayley transform that parameterizes orthogonal matrices and the contro

Mohammed Taariq Mowzer

We study the convergence of Bernstein type operators leading to two results. The first: The kernel $K_n$ of the Bernstein-Durrmeyer operator at each point $x \in (0, 1)$ $\unicode{x2013}$ that is $K_n(x, t) dt$ $\unicode{x2013}$ once standardised converges to the normal distribution. The second result computes the pointwise limit of a generalised Bernstein-D

Xavier Warin

We study news neural networks to approximate function of distributions in a probability space. Two classes of neural networks based on quantile and moment approximation are proposed to learn these functions and are theoretically supported by universal approximation theorems. By mixing the quantile and moment features in other new networks, we develop schemes

Tomas da Veiga, Giovanni Pittiglio, Michael Brockdorff, James H. Chandler

Localization of magnetically actuated medical robots is essential for accurate actuation, closed loop control and delivery of functionality. Despite extensive progress in the use of magnetic field and inertial measurements for pose estimation, these have been either under single external permanent magnet actuation or coil systems. With the advent of new magn

Wenyu Wang, Wu-Long Xu, Jin Min Yang, Bin Zhu

We present a comprehensive study on the self-interaction cross-section of puffy dark matter (DM) particles, which have a significant intrinsic size compared to their Compton wavelength. For such puffy DM self-interaction cross-section in the resonant and classical regimes, our study demonstrates the significance of the Yukawa potential and the necessity of p

Ruihai Wu, Chuanruo Ning, Hao Dong

Understanding and manipulating deformable objects (e.g., ropes and fabrics) is an essential yet challenging task with broad applications. Difficulties come from complex states and dynamics, diverse configurations and high-dimensional action space of deformable objects. Besides, the manipulation tasks usually require multiple steps to accomplish, and greedy p

Henrik Ejersbo, Kenneth Lausdahl, Mirgita Frasheri, Lukas Esterle

Digital Twins represent a new and disruptive technology, where digital replicas of (cyber)-physical systems operate for long periods of time alongside their (cyber)-physical counterparts, with enabled bi-directional communication between them. However promising, the development of digital twins is a non-trivial problem, since what can initially be adequate m

Yuxuan Shi, Lingxiao Yang, Wangpeng An, Xiantong Zhen

The channel attention mechanism is a useful technique widely employed in deep convolutional neural networks to boost the performance for image processing tasks, eg, image classification and image super-resolution. It is usually designed as a parameterized sub-network and embedded into the convolutional layers of the network to learn more powerful feature rep

Manon Felix, Davide La Vecchia, Hang Liu, Yiming Ma

This paper is written for a Festschrift in honour of Professor Marc Hallin and it proposes some developments on quantile regression. We connect our investigation to Marc's scientific production and we present some theoretical and methodological advances for quantiles estimation in non standard settings. We split our contributions in two parts. The first part

Aadityan Ganesh, Prajakta Nimbhorkar, Pratik Ghosal, Vishwa Prakash HV

Allocation of scarce healthcare resources under limited logistic and infrastructural facilities is a major issue in the modern society. We consider the problem of allocation of healthcare resources like vaccines to people or hospital beds to patients in an online manner. Our model takes into account the arrival of resources on a day-to-day basis, different c

Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu

Although many recent works have investigated generalizable NeRF-based novel view synthesis for unseen scenes, they seldom consider the synthetic-to-real generalization, which is desired in many practical applications. In this work, we first investigate the effects of synthetic data in synthetic-to-real novel view synthesis and surprisingly observe that model

Shumin Pang, Dongwei Wu, Aleksander Gurlo, Jens Kurreck

Additively manufactured hollow strut bioceramic scaffolds present a promising strategy towards enhanced performance in patient-tailored bone tissue engineering. The channels in such scaffolds offer pathways for nutrient and cell transport and facilitate effective osseointegration and vascularization. In this study, we report an approach for the slurry based

Evgeny Sevost'yanov

The article is devoted to the study of mappings that distort the modulus of families of paths by the Poletsky inequality type. At boundary points of a domain, we have obtained the H\"{o}lder inequality for such mappings, provided that their characteristic has finite integral averages over infinitesimal balls. In the manuscript, we have separately considered

Michael Filler, Benjamin Reinhardt

It may be possible to reinvent how microelectronics are made using a two step process: (1) Synthesizing modular, nanometer-scale components -- transistors, sensors, and other devices -- and suspending them in a liquid "ink" for storage or transport; (2) Using a 3D-printer-like machine to create circuits by placing and wiring the components. Developments in n

Changsheng Lv, Mengshi Qi, Xia Li, Zhengyuan Yang

In this paper, we propose a novel model called SGFormer, Semantic Graph TransFormer for point cloud-based 3D scene graph generation. The task aims to parse a point cloud-based scene into a semantic structural graph, with the core challenge of modeling the complex global structure. Existing methods based on graph convolutional networks (GCNs) suffer from the

Holger Nobach

To derive the auto-covariance function from a sampled and time-limited signal or the cross-covariance function from two such signals, the mean values must be estimated and removed from the signals. If no a priori information about the correct mean values is available and the mean values must be derived from the time series themselves, the estimates will be b

Keigo Habara, Ellen Hidemi Fukuda, Nobuo Yamashita

The extensive-form game has been studied considerably in recent years. It can represent games with multiple decision points and incomplete information, and hence it is helpful in formulating games with uncertain inputs, such as poker. We consider an extended-form game with two players and zero-sum, i.e., the sum of their payoffs is always zero. In such games

Christian Berger, Signe Schwarz-Rüsch, Arne Vogel, Kai Bleeke

With the advancement of blockchain systems, many recent research works have proposed distributed ledger technology~(DLT) that employs Byzantine fault-tolerant~(BFT) consensus protocols to decide which block to append next to the ledger. Notably, BFT consensus can offer high performance, energy efficiency, and provable correctness properties, and it is thus c

Ali Süleyman Üstünel

We construct a perturbation of identity type mapping on an abstract Wiener space where the Cameron-Martin space has an orthonormal basis indexed by the jumps a one dimensional semimartingale. We then derive a change of variables formula and a degree type result for this map.

Mahdi Izadi, Emad Chaparian, Elizabeth Trudel, Ian Frigaard

Squeeze cementing is a process used to repair leaking oil and gas wells, in which a cement slurry is driven under pressure to fill an uneven leakage channel. This results in a Hele-Shaw type flow problem involving a yield stress fluid. We solve the flow problem using an augmented Lagrangian approach and advect forward the fluid concentrations until the flow

Emil Riis Hansen, Thomas Dyhre Nielsen, Thomas Mulvad, Mads Nibe Strausholm

Predicting patients hospital length of stay (LOS) is essential for improving resource allocation and supporting decision-making in healthcare organizations. This paper proposes a novel approach for predicting LOS by modeling patient information as sequences of events. Specifically, we present a transformer-based model, termed Medic-BERT (M-BERT), for LOS pre

Ahmed H. Shahin, Yan Zhuang, Noha El-Zehiry

Accurate and safe catheter ablation procedures for patients with atrial fibrillation require precise segmentation of cardiac structures in Intracardiac Echocardiography (ICE) imaging. Prior studies have suggested methods that employ 3D geometry information from the ICE transducer to create a sparse ICE volume by placing 2D frames in a 3D grid, enabling train

Yinpeng Dong, Caixin Kang, Jinlai Zhang, Zijian Zhu

3D object detection is an important task in autonomous driving to perceive the surroundings. Despite the excellent performance, the existing 3D detectors lack the robustness to real-world corruptions caused by adverse weathers, sensor noises, etc., provoking concerns about the safety and reliability of autonomous driving systems. To comprehensively and rigor

Roberto Balbinot, Alessandro Fabbri

We consider a Reissner-Nordstr\"om black hole formed by the collapse of a charged null shell. The renormalised expectation values of the energy momentum tensor operator for a massless scalar field propagating in the 2D section of this spacetime are given. We then analyse the across the horizon correlations of the related energy density operator for free fall

Jinrong Hu, Qiongfang Mao, Sinan Wang

In this paper, we derive the continuity of solutions to the $L_{p}$ torsional Minkowski problem for $p>1$. It is shown that the weak convergence of the $L_{p}$ torsional measure implies the convergence of the sequence of the corresponding convex bodies in the Hausdorff metric. Furthermore, continuity of the solution to the $L_{p}$ torsional Minkowski problem

Thomas Wahl, Joséphine Riedinger, Michel Duprez, Axel Hutt

Mental disorders (MD) are among the top most demanding challenges in world-wide health. According to the World Health Organization, the burden of MDs continues to grow with significant impact on health and major social and human rights. A large number of MDs exhibit pathological rhythms, which serve as the disorders characteristic biomarkers. These rhythms a

Ryota Ura, Takuya Hashimoto, Akio K. Inoue, Dario Fadda

We present integral field, far-infrared (FIR) spectroscopy of Mrk 54, a local Lyman Continuum Emitter (LCE), obtained with FIFI-LS on the Stratospheric Observatory for Infrared Astronomy. This is only the second time, after Haro 11, that [C II] 158 $\mu$m and [O III] 88 $\mu$m spectroscopy of the known LCEs have been obtained. We find that Mrk 54 has a stron

M. Liu, K. Issautier, M. Moncuquet, N. Meyer-Vernet

The Quasi-thermal noise (QTN) technique is a reliable tool to yield accurate measurements of the electron parameters in the solar wind. We apply this method on Parker Solar Probe (PSP) observations to derive the total electron temperature ($T_e$) from the linear fit of the high-frequency part of the QTN spectra acquired by the RFS/FIELDS instrument, and pres

Haohao Sun, Yilong Zhang, Peng Chen, Haixia Wang

As a non-invasive optical imaging technique, optical coherence tomography (OCT) has proven promising for automatic fingerprint recognition system (AFRS) applications. Diverse approaches have been proposed for OCT-based fingerprint presentation attack detection (PAD). However, considering the complexity and variety of PA samples, it is extremely challenging t

Hiroaki Kusunose, Rikuto Oiwa, Satoru Hayami

We have developed a symmetry-adapted modeling procedure for molecules and crystals. By using the completeness of multipoles to express spatial and time-reversal parity-specific anisotropic distributions, we can generate systematically the complete symmetry-adapted multipole basis set to describe any of electronic degrees of freedom in isolated cluster system

S. Muthuvel, R. Venkatraman

In this paper, we deal with the quartic Diophantine equation $X^4-Y^4=R^2-S^2$ to present its infinitely many integer solutions.

Zhengliang Liu, Yue Huang, Xiaowei Yu, Lu Zhang

The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy. HIPAA (Health Insurance Portability and Accountability Act) mandates removing re-identifying information before the dissemination of medical records. Thus, effective and efficient solutions for de-identifying

G. Favole, V. Gonzalez-Perez, Y. Ascasibar, P. Corcho-Caballero

Nebular emission lines are powerful diagnostics for the physical processes at play in galaxy formation and evolution. Moreover, emission-line galaxies (ELGs) are one of the main targets of current and forthcoming spectroscopic cosmological surveys. We investigate the contributions to the line luminosity functions (LFs) of different galaxy populations in the

Yun-Shi Dai, Peng-Fei Dai, Wei-Xing Zhou

This paper combines the Copula-CoVaR approach with the ARMA-GARCH-skewed Student-t model to investigate the tail dependence structure and extreme risk spillover effects between the international agricultural futures and spot markets, taking four main agricultural commodities, namely soybean, maize, wheat, and rice as examples. The empirical results indicate

Jun Jia, Valeriy Novikov, Tulio Brito Brasil, Emil Zeuthen

We experimentally demonstrate quantum behavior of a macroscopic atomic spin oscillator in the acoustic frequency range. Quantum back-action of the spin measurement, ponderomotive squeezing of light, and oscillator spring softening are observed at spin oscillation frequencies down to 6 kHz. Quantum noise sources characteristic of spin oscillators operating in

Antonio Macaluso, Matthias Klusch, Stefano Lodi, Claudio Sartori

Quantum Machine Learning has the potential to improve traditional machine learning methods and overcome some of the main limitations imposed by the classical computing paradigm. However, the practical advantages of using quantum resources to solve pattern recognition tasks are still to be demonstrated. This work proposes a universal, efficient framework that

Marcel Herzog, Patrizia Longobardi, Mercede Maj

Let $G$ be a group. Write $G^{*}=G\setminus \{1\}$. An element $x$ of $G^{*}$ will be called deficient if $ \langle x\rangle < C_G(x)$ and it will be called non-deficient if $\langle x\rangle = C_G(x).$ If $x\in G$ is deficient (non-deficient), then the conjugacy class $x^G$ of $x$ in $G$ will be also called deficient (non-deficient). Let $j$ be a non-negati

Matteo Iovino, Jonathan Styrud, Pietro Falco, Christian Smith

In modern industrial collaborative robotic applications, it is desirable to create robot programs automatically, intuitively, and time-efficiently. Moreover, robots need to be controlled by reactive policies to face the unpredictability of the environment they operate in. In this paper we propose a framework that combines a method that learns Behavior Trees

Nantel Bergeron, Noémie Cartier, Cesar Ceballos, Vincent Pilaud

We show that for any permutation $\omega$, the increasing flip graph on acyclic pipe dreams with exiting permutation $\omega$ is a lattice quotient of the interval $[e,\omega]$ of the weak order. We then discuss conjectural generalizations of this result to acyclic facets of subword complexes on arbitrary finite Coxeter groups.

Eva Sextl, Rolf-Peter Kudritzki, H. Jabran Zahid, I-Ting Ho

We investigate the mass-metallicity relationship of star forming galaxies by analysing the absorption line spectra of $\sim$200,000 galaxies in the Sloan Digital Sky Survey. The galaxy spectra are stacked in bins of stellar mass and a population synthesis technique is applied yielding metallicities, ages and star formation history of the young and old stella

Baishun Wang, Jun Zhou

The solutions of traditional fractional differential equations neither satisfy group property nor generate dynamical systems, so the study on hyperbolicity is in blank. Relying on the new proposed conformable fractional derivative, we investigate dichotomy of conformable fractional equations, including structure of solutions of linear systems, Mittag-Leffler

H. H. Li, Q. Yuan, J. G. Li, M. R. Xie

Isospin-symmetry breaking is responsible for the energy difference of excited states in mirror nuclei. It also influences the coefficient of the isobaric multiplet mass equation. In the present work, we extensively investigate isospin-symmetry breaking in medium mass nuclei within ab initio frameworks. For this, we employ the ab initio valence-space in-mediu

Anilkumar Parsi, Marcell Bartos, Amber Srivastava, Sebastien Gros

A novel perspective on the design of robust model predictive control (MPC) methods is presented, whereby closed-loop constraint satisfaction is ensured using recursive feasibility of the MPC optimization. Necessary and sufficient conditions are derived for recursive feasibility, based on the effects of model perturbations and disturbances occurring at one ti

Yangfu Li, Jiapan Gan, Xiaodan Lin

Conventional time-delay neural networks (TDNNs) struggle to handle long-range context, their ability to represent speaker information is therefore limited in long utterances. Existing solutions either depend on increasing model complexity or try to balance between local features and global context to address this issue. To effectively leverage the long-term

Hao Wang, Euijoon Ahn, Jinman Kim

Supervised deep learning methods have achieved considerable success in medical image analysis, owing to the availability of large-scale and well-annotated datasets. However, creating such datasets for whole slide images (WSIs) in histopathology is a challenging task due to their gigapixel size. In recent years, self-supervised learning (SSL) has emerged as a

Luis Miguel Pinho

Real-time systems applications usually consist of a set of concurrent activities with timing-related properties. Developing these applications requires programming paradigms that can effectively handle the specification of concurrent activities and timing constraints, as well as controlling their execution on a particular platform. The prevailing trend for h

Gennadi Malaschonok, Alla Sidko

A new runtime environment for the execution of recursive matrix algorithms on a supercomputer with distributed memory is proposed. It is designed both for dense and sparse matrices. The environment ensures decentralized control of the computation process. As an example of a block recursive algorithm, the Cholesky factorization of a symmetric positive definit

Takis Angelides, Lena Funcke, Karl Jansen, Stefan Kühn

Simulations of lattice gauge theories with tensor networks and quantum computing have so far mainly focused on staggered fermions. In this paper, we use matrix product states to study Wilson fermions in the Hamiltonian formulation and present a novel method to determine the additive mass renormalization. Focusing on the single-flavor Schwinger model as a ben

Armin Pirastehzad, Arjan van der Schaft, Bart Besselink

We introduce $(\gamma,\delta)$-similarity, a notion of system comparison that measures to what extent two stable linear dynamical systems behave similarly in an input-output sense. This behavioral similarity is characterized by measuring the sensitivity of the difference between the two output trajectories in terms of the external inputs to the two potential

Michael Kiermaier, Alfred Wassermann

In 1985, Janko and Tran Van Trung published an algorithm for constructing symmetric designs with prescribed automorphisms. This algorithm is based on the equations by Dembowski (1958) for tactical decompositions of point-block incidence matrices. In the sequel, the algorithm has been generalized and improved in many articles. In parallel, higher incidence ma

Francesco Farina, Mike Arpaia, Harpal Khing, Jonas Vetterle

The optimal portfolio size for a venture capital (VC) fund is a topic often debated, but there is no consensus on the best strategy. This is because it is a function of many factors. It is not easy to find a general formula that can be applied to all situations, and it largely depends on the goal of the fund. In this report, we will go through the different

Xiuhu Zhao, Jinxing Li, Mingjun Huang, Satoshi Aya

Circular dichroism is a technologically important phenomenon contrasting the absorption and resultant emission properties between left- and right-handed circularly polarized light. While the chiral handedness of systems mainly determines the mechanism of the circular dichroism in linear optics, the counterpart in the nonlinear optical regime is nontrivial. H

Xinglong Luo, Kunming Luo, Ao Luo, Zhengning Wang

We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels. Previous datasets are created by either capturing real scenes by event cameras or synthesizing from images with pasted foreground objects. The former case can produce real event

Rajah P. Nutakki, Ludovic D. C. Jaubert, Lode Pollet

The centred pyrochlore lattice is a novel geometrically frustrated lattice, realized in the metal-organic framework Mn(ta)$_2$ (arXiv:2203.08780) where the basic unit of spins is a five site centred tetrahedron. Here, we present an in-depth theoretical study of the $J_1-J_2$ classical Heisenberg model on this lattice, using a combination of mean-field analyt

Binbin Wang, Mingming Li, Zhixiong Zeng, Jingwei Zhuo

Retrieving relevant items that match users' queries from billion-scale corpus forms the core of industrial e-commerce search systems, in which embedding-based retrieval (EBR) methods are prevailing. These methods adopt a two-tower framework to learn embedding vectors for query and item separately and thus leverage efficient approximate nearest neighbor (ANN)

Shumin Pang, Dongwei Wu, Haotian Yang, Franz Kamutzki

Effective scaffolds for bone tissue-engineering are those that combine adequate mechanical and chemical performance with osseointegrative, angiogenetic and anti-bacterial modes of bioactivity. To address these requirements via a combined approach, we additively manufactured square strut scaffolds by robocasting precipitation-derived strontium/copper co-subst

Subith Kumar, Anirban Ghosh, Chahat Kaushik, Arash Shiri

Historically, infinity was long considered a vague concept - boundless, endless, larger than the largest - without any quantifiable mathematical foundation. This view changed in the 1800s through the pioneering work of Georg Cantor showing that infinite sets follow their own seemingly paradoxical mathematical rules. In 1924, David Hilbert highlighted the str

Ishfaq A. Rather, Kauan D. Marquez, Grigoris Panotopoulos, Ilidio Lopes

We investigate the effect of $\Delta$ baryons on the radial oscillations of neutron and hyperon stars, employing a density-dependent relativistic mean-field model. The spin-$3/2$ baryons are described by the Rarita-Schwinger Lagrangian density. The baryon-meson coupling constants for the spin-3/2 decuplet and the spin-1/2 baryonic octet are calculated using

Li Yi

Generating lyrics and poems is one of the essential downstream tasks in the Natural Language Processing (NLP) field. Current methods have performed well in some lyrics generation scenarios but need further improvements in tasks requiring fine control. We propose a novel method for generating ancient Chinese lyrics (Song Ci), a type of ancient lyrics that inv

Kirill Polovnikov, Bogdan Slavov

Chromosomes are crumpled polymer chains further folded into a sequence of stochastic loops via loop extrusion. While extrusion has been verified experimentally, the particular means by which the extruding complexes bind DNA polymer remains controversial. Here we analyze the behaviour of the contact probability function for a crumpled polymer with loops for t

Fida Mohammad Thoker, Hazel Doughty, Cees Snoek

We propose a self-supervised method for learning motion-focused video representations. Existing approaches minimize distances between temporally augmented videos, which maintain high spatial similarity. We instead propose to learn similarities between videos with identical local motion dynamics but an otherwise different appearance. We do so by adding synthe

Zhenbin Cao, Changxing Miao

Almost everywhere convergence on the solution of Schr\"odinger equation is an important problem raised by Carleson, which was essentially solved by Du-Guth-Li and Du-Zhang. In this note, we obtain the sharp pointwise convergence on the Schr\"odinger operator along one class of curves.

Krzysztof Barczynski, Louise Harra, Conrad Schwanitz, Nils Janitzek

The origin of the slow solar wind is still an open issue. One possibility that has been suggested is that upflows at the edge of an active region can contribute to the slow solar wind. We aim to explain how the plasma upflows are generated, which mechanisms are responsible for them, and what the upflow region topology looks like. We investigated an upflow re

Terence L. van Zyl

Meta-learning, decision fusion, hybrid models, and representation learning are topics of investigation with significant traction in time-series forecasting research. Of these two specific areas have shown state-of-the-art results in forecasting: hybrid meta-learning models such as Exponential Smoothing - Recurrent Neural Network (ES-RNN) and Neural Basis Exp

Nathan Hubens, Victor Delvigne, Matei Mancas, Bernard Gosselin

The advent of sparsity inducing techniques in neural networks has been of a great help in the last few years. Indeed, those methods allowed to find lighter and faster networks, able to perform more efficiently in resource-constrained environment such as mobile devices or highly requested servers. Such a sparsity is generally imposed on the weights of neural

Uwe Naumann, Erik Schneidereit, Simon Maertens, Markus Towara

All known elimination techniques for (first-order) algorithmic differentiation (AD) rely on Jacobians to be given for a set of relevant elemental functions. Realistically, elemental tangents and adjoints are given instead. They can be obtained by applying software tools for AD to the parts of a given modular numerical simulation. The novel generalized face e

Francesco Andreoli, Bennet Windt, Stefano Grava, Gian Marcello Andolina

All known optical materials have an index of refraction of order unity. Despite the tremendous implications that an ultrahigh index could have for optical technologies, little research has been done on why the refractive index of materials is universally small, and whether this observation is fundamental. Here, we investigate the index of an ordered arrangem

Nan Yang, Xuanyu Chen, Charles Z. Liu, Dong Yuan

Latest federated learning (FL) methods started to focus on how to use unlabeled data in clients for training due to users' privacy concerns, high labeling costs, or lack of expertise. However, current Federated Semi-Supervised/Self-Supervised Learning (FSSL) approaches fail to learn large-scale images because of the limited computing resources of local clien