July 2022 arXiv papers — page 135

Mihály Kovács, Eszter Sikolya

We investigate the parabolic Cauchy problem associated with quantum graphs including Lipschitz or polynomial type nonlinearities and additive Gaussian noise perturbed vertex conditions. The vertex conditions are the standard continuity and Kirchhoff assumptions in each vertex. In the case when only Kirchhoff conditions are perturbed, we can prove existence a

Dmitrii N. Maksimov, Andrey R. Kolovsky

We propose a simple, yet feasible, model for quantum transport of fermionic carriers across tight-binding chain connecting two reservoirs maintained at arbitrary temperatures and chemical potentials. The model allows for elementary derivation of the master equation for the reduced single particle density matrix in a closed form in both Markov and Born approx

Larissa Braz, Enrico Fregnan, Vivek Arora, Alberto Bacchelli

Background: Security regressions are vulnerabilities introduced in a previously unaffected software system. They often happen as a result of source code changes (e.g., a bug fix) and can have severe effects. Aims: To increase the understanding of security regressions. This is an important step in developing secure software engineering. Method: We perform an

Eddwi H. Hasdeo, Edvin G. Idrisov, Thomas L. Schmidt

We show that Coulomb drag in hydrodynamic bilayer systems leads to additional viscosity terms in the hydrodynamic equations, i.e., the drag and drag-Hall viscosities, besides the well-known kinematic and Hall viscosities. These new viscosity terms arise from a change of the stress tensor due to the interlayer Coulomb interactions. All four viscosity terms ar

Zhucheng Tu, Sarguna Janani Padmanabhan

We describe our two-stage system for the Multilingual Information Access (MIA) 2022 Shared Task on Cross-Lingual Open-Retrieval Question Answering. The first stage consists of multilingual passage retrieval with a hybrid dense and sparse retrieval strategy. The second stage consists of a reader which outputs the answer from the top passages returned by the f

Cassandra Milbradt, Dörte Kreher

We develop a cross-border market model for two countries based on a continuous trading mechanism, in which the transmission capacities that enable transactions between market participants from different countries are limited. Our market model can be described by a regime-switching process alternating between active and inactive regimes, in which cross-border

Minjia Shi, Na Liu, Jon-Lark Kim, Patrick Solé

A linear code is linear complementary dual (LCD) if it meets its dual trivially. LCD codes have been a hot topic recently due to Boolean masking application in the security of embarked electronics (Carlet and Guilley, 2014). Additive codes over $\F_4$ are $\F_4$-codes that are stable by codeword addition but not necessarily by scalar multiplication. An addit

Miltiadis Marios Katsakioris, Yiwei Zhou, Daniele Masato

Understanding the semantic meaning of tabular data requires Entity Linking (EL), in order to associate each cell value to a real-world entity in a Knowledge Base (KB). In this work, we focus on end-to-end solutions for EL on tabular data that do not rely on fact lookup in the target KB. Tabular data contains heterogeneous and sparse context, including column

Dino Festi, Bert van Geemen

In this paper, we show that a set of six square roots of homogeneous polynomials in four variables, related to a binary system of black holes studied by Stefan Weinzierl, is not rationalizable. We prove it by showing that the variety $X$ associated to the product of four of the six square roots is not unirational. In particular, we show that the smooth model

Christoph Muschielok

We show that explicit forms for certain polynomials~$\psi^{(a)}_m(n)$ with the property \[ \psi^{(a+1)}_m(n) = \sum_{\nu=1}^n \psi_m^{(a)}(\nu) \] can be found (here, $a,m,n\in\mathbb{N}_0$). We use these polynomials as a basis to express the monomials~$n^m$. Once the expansion coefficients are determined, we can express the $m$-th power sums~$S^{(a)}_m(n)$

Bjorge Meulemeester, David Martens

Continuous developments in data science have brought forth an exponential increase in complexity of machine learning models. Additionally, data scientists have become ubiquitous in the private market, academic environments and even as a hobby. All of these trends are on a steady rise, and are associated with an increase in power consumption and associated ca

Francisco Guillén-González, André Luiz Corrêa Vianna Filho

In the present work we propose and study a time discrete scheme for the following chemotaxis-consumption model (for any $s\ge 1$), $$ \partial_t u - \Delta u = - \nabla \cdot (u \nabla v), \quad \partial_t v - \Delta v = - u^s v \quad \hbox{in $(0,T)\times \Omega$,}$$ endowed with isolated boundary conditions and initial conditions, where $(u,v)$ model cell

Ruoyu Feng, Xin Jin, Zongyu Guo, Runsen Feng

Image Coding for Machines (ICM) aims to compress images for AI tasks analysis rather than meeting human perception. Learning a kind of feature that is both general (for AI tasks) and compact (for compression) is pivotal for its success. In this paper, we attempt to develop an ICM framework by learning universal features while also considering compression. We

Haoyun Li, Peiming Li, Jie Xu, Junting Chen

Channel knowledge map (CKM) has recently emerged to facilitate the placement and trajectory optimization for unmanned aerial vehicle (UAV) communications. This paper investigates a CKM-assisted multi-UAV wireless network, by focusing on the construction and utilization of CKMs for multi-UAV placement optimization. First, we consider the CKM construction prob

Anastasiia Zalogina, Luca Carletti, Aditya Tripathi, Hoo-Cheol Lee

Higher-order optical harmonics entered the realm of nanostructured solids being observed recently in optical gratings and metasurfaces with a subwavelength thickness. Structuring materials at the subwavelength scale allows for resonant enhancing of the efficiency of nonlinear processes and reducing the size of high-harmonic sources. Here we report the observ

Martina Conte, Nadia Loy

We propose a non-local model for contact guidance and steric hindrance depending on a single external cue, namely the extracellular matrix, that affects in a twofold way the polarization and speed of motion of the cells. We start from a microscopic description of the stochastic processes underlying the cell re-orientation mechanism related to the change of c

Tianrun Gao, Huihe Qiu, Lin Fu

The multi-resolution method, e.g., the Adaptive Particle Refinement (APR) method, has been developed to increase the local particle resolution and therefore the solution quality within a pre-defined refinement zone instead of using a globally uniform resolution for Smoothed Particle Hydrodynamics (SPH). However, sometimes, the targeted zone of interest can b

Maxime Herda, Antoine Zurek

In this paper we analyse a finite volume scheme for a nonlocal version of the Shigesada-Kawazaki-Teramoto (SKT) cross-diffusion system. We prove the existence of solutions to the scheme, derive qualitative properties of the solutions and prove its convergence. The proofs rely on a discrete entropy-dissipation inequality, discrete compactness arguments, and o

Fredrik Svanström, Fernando Alonso-Fernandez, Cristofer Englund

Automatic detection of flying drones is a key issue where its presence, especially if unauthorized, can create risky situations or compromise security. Here, we design and evaluate a multi-sensor drone detection system. In conjunction with standard video cameras and microphone sensors, we explore the use of thermal infrared cameras, pointed out as a feasible

Nihad Abuawwad, Manuel dos Santos Dias, Hazem Abusara, Samir Lounis

The discovery of two-dimensional (2D) van der Waals magnets opened unprecedented opportunities for the fundamental exploration of magnetism in quantum materials and the realization of next generation spintronic devices. Here, based on a multiscale modelling approach that combines first-principles calculations and a Heisenberg model supplied with ab-initio pa

Shangrong Yang, Chunyu Lin, Kang Liao, Yao Zhao

Numerous significant progress on fisheye image rectification has been achieved through CNN. Nevertheless, constrained by a fixed receptive field, the global distribution and the local symmetry of the distortion have not been fully exploited. To leverage these two characteristics, we introduced Fishformer that processes the fisheye image as a sequence to enha

V. V. Bobylev, A. T. Bajkova, G. M. Karelin

We have analyzed the kinematics of OB stars from the list by Xiang et al. (2021) that contains $\sim$13 000 single OB stars. For these stars there are photometric distance estimates and proper motions from the Gaia catalogue and line-of-sight velocities from the LAMOST catalogue. Based on a sample of single OB stars and using the photometric distances and pr

Benno Liebchen, Demian Levis

Chiral active matter comprises particles which can self-propel and self-rotate. Examples range from sperm cells and bacteria near walls to asymmetric colloids and pea-shaped Quincke rollers. In this perspective article we focus on recent developments in chiral active matter. After briefly discussing chiral active motion at a single particle level, we discuss

Erik Spånberg

In this paper, we present a method of maximum a posteriori estimation of parameters in dynamic factor models with incomplete data. We extend maximum likelihood expectation maximization iterations by Ba\'nbura & Modugno (2014) to penalized counterparts by applying parameter shrinkage in a Minnesota prior style fashion, also considering factors loading onto va

T. M. Mazzocchi, P. Gazzaneo, J. Lotze, E. Arrigoni

We study the spectral and transport properties of a Mott insulator driven by a static electric field into a non-equilibrium steady state. For the dissipation, we consider two mechanisms: Wide-band fermion reservoirs and phonons included within the Migdal approximation. The electron correlations are treated via non-equilibrium dynamical mean field theory with

J. Fernandes, J. Sá Silva, A. Rodrigues, F. Boavida

As the number of smart devices that surround us increases, so do the opportunities to leverage them to create socially- and context-aware systems. Smart devices can be used for better understanding human behaviour and its societal implications. As an example of a scenario in which the role of socially aware systems is crucial, consider the SARS-CoV-2 pandemi

L. Boonzaaier, S. Marques

This paper addresses the question: given a scalar group, can we determine all the additions that transform this scalar group into a (near-)field? A key approach to addressing this problem involves transporting (near-)field structures via multiplicative automorphisms. We compute the set of continuous multiplicative automorphisms of the real and complex fields

Ainkaran Santhirasekaram, Avinash Kori, Mathias Winkler, Andrea Rockall

The reliability of segmentation models in the medical domain depends on the model's robustness to perturbations in the input space. Robustness is a particular challenge in medical imaging exhibiting various sources of image noise, corruptions, and domain shifts. Obtaining robustness is often attempted via simulating heterogeneous environments, either heurist

Vésteinn Snæbjarnarson, Hafsteinn Einarsson

It can be challenging to build effective open question answering (open QA) systems for languages other than English, mainly due to a lack of labeled data for training. We present a data efficient method to bootstrap such a system for languages other than English. Our approach requires only limited QA resources in the given language, along with machine-transl

Avinash Kori, Ben Glocker, Francesca Toni

Most of the current explainability techniques focus on capturing the importance of features in input space. However, given the complexity of models and data-generating processes, the resulting explanations are far from being `complete', in that they lack an indication of feature interactions and visualization of their `effect'. In this work, we propose a nov

Ainkaran Santhirasekaram, Avinash Kori, Andrea Rockall, Mathias Winkler

Explanations for \emph{black-box} models help us understand model decisions as well as provide information on model biases and inconsistencies. Most of the current explainability techniques provide a single level of explanation, often in terms of feature importance scores or feature attention maps in input space. Our focus is on explaining deep discriminativ

Amit Maji, Atanu Manna, Ram Mohapatra

In this paper, we achieve new and improved numerical radius inequalities of operators defined on a Hilbert space by using Orlicz function and Hermite-Hadamard inequality. The upper bounds of various inequalities involving numerical radii have been obtained. Finally, we compute an upper bound of the numerical radius for block matrices of the form $\begin{bmat

Maryam Khanahmadi, Klaus Mølmer

Different hypotheses about a quantum system such as the logical state of a qubit or the value of physical interaction parameters can be investigated by the interaction with a probe field. Such fields may be prepared in particularly sensitive quantum states, and we can use quantum trajectories to model the stochastic measurement record and conditional evoluti

Isabelle Tanseri, Steffen Hagstotz, Sunny Vagnozzi, Elena Giusarma

We revisit cosmological constraints on the sum of the neutrino masses $\Sigma m_\nu$ from a combination of full-shape BOSS galaxy clustering [$P(k)$] data and measurements of the cross-correlation between Planck Cosmic Microwave Background (CMB) lensing convergence and BOSS galaxy overdensity maps [$C^{\kappa \text{g}}_{\ell}$], using a simple but theoretica

Andreas Crivellin, Martin Hoferichter

The anomalous magnetic moment of the muon displays a $4.2\sigma$ tension with the Standard-Model prediction, if $e^+e^-\to \text{hadrons}$ data are used for hadronic vacuum polarization. In these proceedings we review possible explanations of this anomaly in terms of heavy new particles. As the necessary effect is of the order of the electroweak Standard-Mod

Thomas Hickling, Abdelhafid Zenati, Nabil Aouf, Phillippa Spencer

The use of Deep Reinforcement Learning (DRL) schemes has increased dramatically since their first introduction in 2015. Though uses in many different applications are being found, they still have a problem with the lack of interpretability. This has bread a lack of understanding and trust in the use of DRL solutions from researchers and the general public. T

Luigi Fiorillo, Davide Pedroncelli, Valentina Agostini, Paolo Favaro

Study Objectives: Inter-scorer variability in scoring polysomnograms is a well-known problem. Most of the existing automated sleep scoring systems are trained using labels annotated by a single scorer, whose subjective evaluation is transferred to the model. When annotations from two or more scorers are available, the scoring models are usually trained on th

Weichen Fan, Jinghuan Chen, Jiabin Ma, Jun Hou

Image-to-image (I2I) translation is a challenging topic in computer vision. We divide this problem into three tasks: strongly constrained translation, normally constrained translation, and weakly constrained translation. The constraint here indicates the extent to which the content or semantic information in the original image is preserved. Although previous

Xianhua Yu, Dong Li

A potential 6G technology known as intelligent reflecting surface (IRS) has recently gained much attention from academia and industry. However, acquiring the optimized quantized phase shift (QPS) presents challenges for the IRS due to the phenomenon of signaling storms. In this paper, we attempt to solve the above problem by proposing two deep learning model

Seid H. Pourtakdoust, Amir H. Khodabakhsh

Derivation of the probability density evolution provides invaluable insight into the behavior of many stochastic systems and their performance. However, for most real-time applica-tions, numerical determination of the probability density evolution is a formidable task. The latter is due to the required temporal and spatial discretization schemes that render

Yukai Wang, Chunlei Peng, Decheng Liu, Nannan Wang

In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns. Existing face forgery detection methods based on frequency domain find that the GAN forged images have obvious grid-like visual artifacts in the frequency spectrum compared to the rea

Jiryo Komeda, Shigeki Matsutani, Emma Previato

The Weierstrass curve is a pointed curve $(X,\infty)$ with a numerical semigroup $H_X$, which is a normalization of the curve given by the Weierstrass canonical form, $y^r + A_{1}(x) y^{r-1} + A_{2}(x) y^{r-2} +\dots + A_{r-1}(x) y + A_{r}(x)=0$ where each $A_j$ is a polynomial in $x$ of degree $\leq j s/r$ for certain coprime positive integers $r$ and $s$,

Yu Li, Vivek Mishra, Yi Zhou, Fu-Chun Zhang

Superconductivity in strongly correlated electrons can emerge out from a normal state that is beyond the Landau's Fermi liquid paradigm, often dubbed as "non-Fermi liquid". While the theory for non-Fermi liquid is still not yet conclusive, a recent study on the exactly-solvable Hatsugai-Kohmoto (HK) model has suggested a non-Fermi liquid ground state whose G

Laida Kushnareva, Dmitri Piontkovski, Irina Piontkovskaya

We apply methods of topological analysis to the attention graphs, calculated on the attention heads of the BERT model ( arXiv:1810.04805v2 ). Our research shows that the classifier built upon basic persistent topological features (namely, Betti numbers) of the trained neural network can achieve classification results on par with the conventional classificati

Matti Henning, Jan Strohbeck, Michael Buchholz, Klaus Dietmayer

The advance towards higher levels of automation within the field of automated driving is accompanied by increasing requirements for the operational safety of vehicles. Induced by the limitation of computational resources, trade-offs between the computational complexity of algorithms and their potential to ensure safe operation of automated vehicles are often

Rui Yang, Ercai Chen, Xiaoyao Zhou

Borrowing the idea of topological pressure determining measure-theoretical entropy in topological dynamical systems, we establish a variational principle for upper metric mean dimension with potential in terms of upper measure-theoretical metric mean dimension of invariant measures. Moreover, the notion of equilibrium state is introduced to characterize thes

Ziyuan Zhao, Andong Zhu, Zeng Zeng, Bharadwaj Veeravalli

While deep models have shown promising performance in medical image segmentation, they heavily rely on a large amount of well-annotated data, which is difficult to access, especially in clinical practice. On the other hand, high-accuracy deep models usually come in large model sizes, limiting their employment in real scenarios. In this work, we propose a nov

Tudor Pădurariu, Yukinobu Toda

We begin the study of categorifications of Donaldson-Thomas invariants associated with Hilbert schemes of points on the three-dimensional affine space, which we call DT categories. The DT category is defined to be the category of matrix factorizations on the non-commutative Hilbert scheme with a super-potential whose critical locus is the Hilbert scheme of p

André Artelt, Barbara Hammer

Machine learning based decision making systems applied in safety critical areas require reliable high certainty predictions. For this purpose, the system can be extended by an reject option which allows the system to reject inputs where only a prediction with an unacceptably low certainty would be possible. While being able to reject uncertain samples is imp

Bertrand Lods, Mustapha Mokhtar-Kharroubi

The object of this paper is to provide a new and systematic tauberian approach to quantitative long time behaviour of $C_{0}$-semigroups $\left(\mathcal{V}(t)\right)_{t \geq0}$ in $L^{1}(\mathbb{T}^{d}\times \mathbb{R}^{d})$ governing conservative linear kinetic equations on the torus with general scattering kernel $ {k}(v,v')$ and degenerate (i.e. not bound

Matti Henning, Michael Buchholz, Klaus Dietmayer

Advances in the field of environment perception for automated agents have resulted in an ongoing increase in generated sensor data. The available computational resources to process these data are bound to become insufficient for real-time applications. Reducing the amount of data to be processed by identifying the most relevant data based on the agents' situ

Torgeir Dingsøyr, Diane Strode, Yngve Lindsjørn

Teamwork is critical in many industrial sectors. When creating complex software solutions, most companies and public institutions organize work in cross-functional teams and follow the principles of agile development. This approach to knowledge-intensive work seeks to empower team members, ensures that the most competent people make decisions, and manages un

Alex Kaltenbach, Marius Zeinhofer

We establish error estimates for the approximation of parametric $p$-Dirichlet problems deploying the Deep Ritz Method. Parametric dependencies include, e.g., varying geometries and exponents $p\in (1,\infty)$. Combining the derived error estimates with quantitative approximation theorems yields error decay rates and establishes that the Deep Ritz Method ret

Valentin Pelloin, Franck Dary, Nicolas Herve, Benoit Favre

We aim at improving spoken language modeling (LM) using very large amount of automatically transcribed speech. We leverage the INA (French National Audiovisual Institute) collection and obtain 19GB of text after applying ASR on 350,000 hours of diverse TV shows. From this, spoken language models are trained either by fine-tuning an existing LM (FlauBERT) or

Yurii Averboukh, Dmitry Khlopin

We study necessary optimality conditions for the deterministic mean field type free-endpoint optimal control problem. Our study relies on the Lagrangian approach that treats the mean field type control system as a crowd of infinitely many agents who are labeled by elements of some probability space. First, we derive the Pontryagin maximum principle in the La

Bo Li, Wang Gao, Qing Jiang

High-entropy alloys (HEAs) such as CrMnFeCoNi exhibit unconventional mechanical properties due to their compositional disorder. However, it remains a formidable challenge to estimate the local chemical-environment and magnetic effects of HEAs. Herein we identify the state-associated cohesive energy and band filling originated from the tight-binding and Fried

Joakim Hagel, Samuel Brem, Ermin Malic

Recent advances in the field of vertically stacked 2D materials have revealed a rich exciton landscape. In particular, it has been demonstrated that out-of-plane electrical fields can be used to tune the spectral position of spatially separated interlayer excitons. Other studies have shown that there is a strong hybridization of exciton states, resulting fro

Hun Jang, Massimo Porrati

A new supergravity D-term, not associated to gauged R-symmetry, was recently discovered and used to construct new supergravity models. In this paper we use a generalization of the new D-term that we used in previous works, to construct a supergravity model of slow-roll inflation with the observable sector of the minimal supersymmetric standard model. Supersy

Susie Xi Rao, Piriyakorn Piriyatamwong, Parijat Ghoshal, Sara Nasirian

The scientific publication output grows exponentially. Therefore, it is increasingly challenging to keep track of trends and changes. Understanding scientific documents is an important step in downstream tasks such as knowledge graph building, text mining, and discipline classification. In this workshop, we provide a better understanding of keyword and keyph

Sunan He, Taian Guo, Tao Dai, Ruizhi Qiao

Real-world recognition system often encounters the challenge of unseen labels. To identify such unseen labels, multi-label zero-shot learning (ML-ZSL) focuses on transferring knowledge by a pre-trained textual label embedding (e.g., GloVe). However, such methods only exploit single-modal knowledge from a language model, while ignoring the rich semantic infor

Alan Chan

We construct a model of expert prediction where predictions can influence the state of the world. Under this model, we show through theoretical and numerical results that proper scoring rules can incentivize experts to manipulate the world with their predictions. We also construct a simple class of scoring rules that avoids this problem.

Zewang Zhang, Yibin Zheng, Xinhui Li, Li Lu

This paper aims to introduce a robust singing voice synthesis (SVS) system to produce very natural and realistic singing voices efficiently by leveraging the adversarial training strategy. On one hand, we designed simple but generic random area conditional discriminators to help supervise the acoustic model, which can effectively avoid the over-smoothed spec

Deepak Kar, Wandile Nzuza, Sukanya Sinha

Semi-visible jets arise in strongly interacting dark sector, resulting in jets overlapping with the missing transverse momentum direction. The implementation of semi-visible jets is done using the Pythia Hidden Valley module to mimic the QCD sector showering in so-called dark shower. In this work, only heavy flavour Standard Model quarks are considered in da

Guilherme Grams, Rahul Somasundaram, Jerome Margueron, Elias Khan

We have extended the compressible liquid-drop model (CLDM) with a density-dependent surface term (eCLDM), which allows for a unified description of both the nuclear ground state energies and the incompressibility modulus in finite nuclei $K_A$. We analyse the role of the nuclear empirical parameters, e.g., $K_{sat}$, $Q_{sat}$, $L_{sym}$ and $K_{sym}$, which

Ziyuan Zhao, Jinxuan Hu, Zeng Zeng, Xulei Yang

With large-scale well-labeled datasets, deep learning has shown significant success in medical image segmentation. However, it is challenging to acquire abundant annotations in clinical practice due to extensive expertise requirements and costly labeling efforts. Recently, contrastive learning has shown a strong capacity for visual representation learning on

Liudmila Bishler

We discuss different invariants of knots and links that depend on a primitive root of unity. We clarify the definitions of existing invariants with the Reshetikhin-Turaev method, present the generalization of ADO invariants to $\mathcal{U}_q(sl_N)$ and highlight the connections between different invariants.

V. L. Kurichenko, D. Yu. Karpenkov, A. Yu. Degtyarenko

The exchange interaction between nanostructured components is an effective way to enhance the magnetic properties of materials. This effect is used in exchange-coupled magnetic composites, which properties are governed by synergetic impact of constituent phases. Texturing is one of the problems that needs to be solved in order for such composites to be used

Arthur Alexandre, Maxime Lavaud, Nicolas Fares, Elodie Millan

We study the diffusion of particles confined close to a single wall and in double-wall planar channel geometries where the local diffusivities depend on the distance to the boundaries. Displacement parallel to the walls is Brownian as characterized by its variance, but it is non-Gaussian having a non-zero fourth cumulant. Establishing a link with Taylor disp

Matthew Fayers

We compare the canonical bases of level-$1$ quantised Fock spaces in affine types $A^{(1)}$ and $A^{(2)}$, showing how to derive the canonical basis in type $A^{(2)}_{2n}$ from the the canonical basis in type $A^{(1)}_n$ in certain weight spaces. In particular, we derive an explicit formula for the canonical basis in extremal weight spaces, which correspond

Zhi Liu, Shaoyu Chen, Xiaojie Guo, Xinggang Wang

In this work, we propose PolarBEV for vision-based uneven BEV representation learning. To adapt to the foreshortening effect of camera imaging, we rasterize the BEV space both angularly and radially, and introduce polar embedding decomposition to model the associations among polar grids. Polar grids are rearranged to an array-like regular representation for

Xiaoqiang Wang, Zhonghua Sun, Cunsheng Ding

Negacyclic BCH codes are a subclass of neagcyclic codes and are the best linear codes in many cases. However, there have been very few results on negacyclic BCH codes. Let $q$ be an odd prime power and $m$ be a positive integer. The objective of this paper is to study negacyclic BCH codes with length $\frac{q^m-1}{2}$ and $\frac{q^m+1}{2}$ over the finite fi

Shaolin Ji, Rundong Xu

This paper focuses on finding approximate solutions to stochastic optimal control problems with control domains being not necessarily convex, where the state trajectory is subject to controlled stochastic differential equations. The control-dependent diffusions make the traditional method of successive approximations (MSA) insufficient to reduce the value of

Hamid Khoshfekr Rudsari, Mohammad Zoofaghari, Mladen Veletic, Jacob Bergsland

A closer look at nature has recently brought more interest in exploring and utilizing intra-body communication networks composed of cells as intrinsic, perfectly biocompatible infrastructures to deliver therapeutics. Naturally occurring cell-to-cell communication systems are being manipulated to release, navigate, and take up soluble cell-derived messengers

Jørgen Endal, Liviu I. Ignat, Fernando Quirós

We study the large-time behaviour of nonnegative solutions to the Cauchy problem for a nonlocal heat equation with a nonlinear convection term. The diffusion operator is the infinitesimal generator of a stable L\'evy process, which may be highly anisotropic. The initial data are assumed to be bounded and integrable. The mass of the solution is conserved alon

Asem Alaa, Erik Mayer, Mauricio Barahona

Early diagnosis of disease can lead to improved health outcomes, including higher survival rates and lower treatment costs. With the massive amount of information available in electronic health records (EHRs), there is great potential to use machine learning (ML) methods to model disease progression aimed at early prediction of disease onset and other outcom

Daniel J. Fresen

Following results of Kemperman and Pinelis, we show that if $X$ and $Y$ are real valued random variables such that $\mathbb{E}\left\vert Y\right\vert<\infty$ and for all non-decreasing convex $\varphi:\mathbb{R}\rightarrow [0,\infty)$, $\mathbb{E}\varphi(X)\leq\mathbb{E}\varphi(Y)$, then for all $s\in\mathbb{R}$ with $\mathbb{P}\left\{Y>s\right\}\neq 0$, $\m

Snehal Singh Tomar, A. N. Rajagopalan

With the advent of an increasing number of Augmented and Virtual Reality applications that aim to perform meaningful and controlled style edits on images of human faces, the impetus for the task of parsing face images to produce accurate and fine-grained semantic segmentation maps is more than ever before. Few State of the Art (SOTA) methods which solve this

Thomas Chatain, Neha Rino

The subject of this paper is to study conformance checking for timed models, that is, process models that consider both the sequence of events in a process as well as the timestamps at which each event is recorded. Time-aware process mining is a growing subfield of research, and as tools that seek to discover timing related properties in processes develop, s

Guangzhi Wang, Yangyang Guo, Yongkang Wong, Mohan Kankanhalli

Human-Object Interaction (HOI) detection has received considerable attention in the context of scene understanding. Despite the growing progress on benchmarks, we realize that existing methods often perform unsatisfactorily on distant interactions, where the leading causes are two-fold: 1) Distant interactions are by nature more difficult to recognize than c

Jaeik Jeon, Yeonggul Jang, Youngtaek Hong, Hackjoon Shim

Medical imaging, including MRI, CT, and Ultrasound, plays a vital role in clinical decisions. Accurate segmentation is essential to measure the structure of interest from the image. However, manual segmentation is highly operator-dependent, which leads to high inter and intra-variability of quantitative measurements. In this paper, we explore the feasibility

Daniel J. Fresen

We present order of magnitude estimates for the quantiles of non-negative linear combinations of non-negative random variables, as well as deviation inequalities for general linear combinations of independent random variables, under the assumption that all random variables satisfy the same power-type tail bound on $\mathbb{P}\{\left\vert X_i\right\vert>t\}$

Igor N. Karnaukhov

The Kondo insulator state (KIS) realized in the symmetric Anderson model at half filling is studied in the framework of a mean field approach. It is shown that the state of the Kondo insulator is realized in a lattice with a double cell and a gapped electron liquid behaves like a gapless Majorana spin liquid. The local moments of d-electrons form a static $Z

C. P. Folsom, R. Ignace, C. Erba, R. Casini

Magnetic fields are important for stellar photospheres and magnetospheres, influencing photospheric physics and sculpting stellar winds. Observations of stellar magnetic fields are typically made in the visible, although infrared observations are becoming common. Here we consider the possibility of directly detecting magnetic fields at ultraviolet (UV) wavel

Zhonghua Sun, Xiaoqiang Wang, Cunsheng Ding

In this paper, several families of irreducible constacyclic codes over finite fields and their duals are studied. The weight distributions of these irreducible constacyclic codes and the parameters of their duals are settled. Several families of irreducible constacyclic codes with a few weights and several families of optimal constacyclic codes are construct

Itaï Ben Yaacov

In this short note we compare the expressive power of real-valued continuous logic (or just continuous logic, in recent literature) with that of compact-valued continuous logic, proposed by Chang and Keisler. We conclude that the two logics have the same expressive power, and moreover, that this remains true if we replace the plethora of potential quantifier

T. T. Sergeev, A. A. Zyablovsky, E. S. Andrianov, Yu. E. Lozovik

Exceptional point (EP) is a spectral singularity in non-Hermitian systems. The passing over the EP leads to a phase transition, which endows the system with unconventional features that find a wide range of applications. However, the need of using the dissipation and amplification limits the possible applications of systems with the EP. In this work, we demo

Andreas Kraft, Jonas Schnitzer

In this review we give a detailed introduction to the theory of (curved) $L_\infty$-algebras and $L_\infty$-morphisms. In particular, we recall the notion of (curved) Maurer-Cartan elements, their equivalence classes and the twisting procedure. The main focus is then the study of the homotopy theory of $L_\infty$-algebras and $L_\infty$-modules. In particula

Elias Ramzi, Nicolas Audebert, Nicolas Thome, Clément Rambour

Image Retrieval is commonly evaluated with Average Precision (AP) or Recall@k. Yet, those metrics, are limited to binary labels and do not take into account errors' severity. This paper introduces a new hierarchical AP training method for pertinent image retrieval (HAP-PIER). HAPPIER is based on a new H-AP metric, which leverages a concept hierarchy to refin

Chuang Zhou, Yang Li, Li Ma, Jie Yang

More than Mbps secret key rate was demonstrated for continuous-variable quantum key distribution (CV-QKD) systems, but real-time postprocessing is not allowed, which is restricted by the throughput of the error correction decoding in postprocessing. In this paper, a high-throughput FPGA-based quasi-cyclic LDPC decoder is proposed and implemented to support M

Matthieu Alfaro, Romain Ducasse, Samuel Tréton

We consider the linear field-road system, a model for fast diffusion channels in population dynamics and ecology. This system takes the form of a system of PDEs set on domains of different dimensions, with exchange boundary conditions. Despite the intricate geometry of the problem, we provide an explicit expression for its fundamental solution and for the so

Georg Schönweger, Md Redwanul Islam, Niklas Wolff, Adrian Petraru

Thickness scaling of ferroelectricity in AlScN is a determining factor for its potential application in neuromorphic computing and memory devices. In this letter, we report on ultrathin (10 nm) Al0.72Sc0.28N films that are ferroelectrically switchable at room temperature. All-epitaxial Al0.72Sc0.28N/Pt heterostructures are grown by magnetron sputtering onto

Florian Viguier

In 1996, Rothstein and Laumon simultaneously constructed a Fourier-Mukai transform for D-modules over a locally noetherian base of characteristic 0. This functor induces an equivalence of categories between quasi-coherent sheaves of D-modules over an abelian variety A and quasicoherent sheaves of O-modules over its universal vectorial extension A. In this ar

Silvio Zanoli, Tomas Teijeiro, Giovanni Ansaloni, David Atienza

Background and Objective: Event-based analog-to-digital converters allow for sparse bio-signal acquisition, enabling local sub-Nyquist sampling frequency. However, aggressive event selection can cause the loss of important bio-markers, not recoverable with standard interpolation techniques. In this work, we leverage the self-similarity of the electrocardiogr

Hiroyuki Sakai, Hiroyuki Sato, Hideaki Iiduka

This paper presents the Hager-Zhang (HZ)-type Riemannian conjugate gradient method that uses the exponential retraction. We also present global convergence analyses of our proposed method under two kinds of assumptions. Moreover, we numerically compare our proposed methods with the existing methods by solving two kinds of Riemannian optimization problems on

David Pouvreau

For every couple (p;q) of strictly positive integers, the `` alternate congruo-harmonic '' series parametrized by (p;q), whose general term is (-1)^k/(pk+q), converges infra-linearly and very slowly. On the basis of a generalized continued fraction expansion of the partial rest of the series, this paper elaborates a family of algorithms which accelerate its

Tao Jin, Jia-Rui Li, Yu-Jie Tan, Cheng-Gang Shao

Short-range experiment with striped design of the test and source masses offers uniquely sensitive probes for Lorentz Violation. In our previous work, we proposed to combine the horizontally and vertically striped experiments to constrain the violating parameters. Here, we further point out adopting the vertically striped structure with the experimental setu

Qiang Niu, Hui Zhang, Youzhou Zhou

In this note, we extend the Vandermonde with Arnoldi method recently advocated by P. D. Brubeck, Y. Nakatsukasa and L. N. Trefethen to dealing with the confluent Vandermonde matrix. To apply the Arnoldi process, it is critical to find a Krylov subspace which generates the column space of the confluent Vandermonde matrix. A theorem is established for such Kry

Matthias Keller, Marius Nietschmann

We study the fractional Hardy inequality on the integers. We prove the optimality of the Hardy weight and hence affirmatively answer the question of sharpness of the constant.

Diego Guadagnoli, Patrick Koppenburg

Two topics have recently risen to prominence within the ongoing searches of beyond-Standard Model effects in $b$ and $c$ decays: observables that test lepton flavor universality (LFU) as well as lepton flavor violation (LFV). A coherent set of measurements suggests non-standard LFU effects. General arguments relate LFU to LFV, and the observed size of the fo

Sergey Alyatkin, Carles Milián, Yaroslav V. Kartashov, Kirill A. Sitnik

Vortices are topologically distinctive objects appearing as phase twists in coherent fields of optical beams and Bose-Einstein condensates. Structured networks and artificial lattices of coupled vortices could offer a powerful platform to study and simulate interaction mechanisms between constituents of condensed matter systems, such as antiferromagnetic int