July 2022 arXiv papers — page 44

Deep Singh, Maheshanand Bhaintwal

Negabent functions were introduced as a generalization of bent functions, which have applications in coding theory and cryptography. In this paper, we have extended the notion of negabent functions to the functions defined from $\mathbb{Z}_q^n$ to $\mathbb{Z}_{2q}$ ($2q$-negabent), where $q \geq 2$ is a positive integer and $\mathbb{Z}_q$ is the ring of inte

Yassine Hamoudi

We describe a simple quantum algorithm for preparing $K$ copies of an $N$-dimensional quantum state whose amplitudes are given by a quantum oracle. Our result extends a previous work of Grover, who showed how to prepare one copy in time $O(\sqrt{N})$. In comparison with the naive $O(K\sqrt{N})$ solution obtained by repeating this procedure~$K$ times, our alg

Filip Janasz, Horst-Michel Prasser, Detlef Suckow, Andrey Mityakov

In this paper we present the developments in heat flux measurements using gradient heat flux sensors (GHFS). The GHFS is a sensor made of artificially created material with anisotropic thermo-electrical properties. Its properties including small size, robustness and low response time make it a valuable addition for characterizing heat flux in space-limited g

Francisca Pessanha, Gizem Sogancioglu

We propose an informed baseline to help disentangle the various contextual factors of influence in this type of case studies. For this purpose, we analysed the correlation between the given metadata and the self-assigned personality trait scores and developed a model based solely on this information. Further, we compared the performance of this informed base

Leoni Breth, Johann Fischbacher, Alexander Kovacs, Harald Özelt

First Order Reversal Curve (FORC) diagrams are a popular tool in geophysics and materials science for the characterization of magnetic particles of natural and synthetic origin. However, there is still a lot of controversy about the rigorous interpretation of the origin of certain features in a FORC diagram. In this study, we analyze FORCs computed by microm

Alain Blaustein, Emeric Bouin

In this paper we focus on a spatially extended FitzHugh-Nagumo model with interactions. In the regime where strong and local interactions dominate, we quantify how the probability density of neurons concentrates into a Dirac distribution. Previous work investigating this question have provided relative bounds in integrability spaces. Using a Hopf-Cole framew

Stuart Ingleby, Paul Griffin, Terry Dyer, Marcin Mrozowski

Self-oscillating atomic magnetometers, in which the precession of atomic spins in a magnetic field is driven by resonant modulation, offer high sensitivity and dynamic range. Phase-coherent feedback from the detected signal to the applied modulation creates a resonant spin maser system, highly responsive to changes in the background magnetic field. Here we s

Nushkia Chamba, Johan H. Knapen, Diane Black

Scientific writing is an important skill for a career as a professional astrophysicist. Very few researchers, however, receive any formal training in how to write scientific research papers of high quality in an efficient manner. This paper (Paper I) is the first of a two-part self-help guide in scientific writing to address this skills gap. Paper I focuses

Vasco Lopes, Miguel Santos, Bruno Degardin, Luís A. Alexandre

Neural Architecture Search (NAS) methods have been successfully applied to image tasks with excellent results. However, NAS methods are often complex and tend to converge to local minima as soon as generated architectures seem to yield good results. This paper proposes GEA, a novel approach for guided NAS. GEA guides the evolution by exploring the search spa

Luca Franzoi, Riccardo Montalto

In this paper we investigate the inviscid limit $\nu \to 0$ for time-quasi-periodic solutions of the incompressible Navier-Stokes equations on the two-dimensional torus ${\mathbb T}^2$, with a small time-quasi-periodic external force. More precisely, we construct solutions of the forced Navier Stokes equation, bifurcating from a given time quasi-periodic sol

Victor Gallego-Fontenla, Juan C. Vidal, Manuel Lama

Changes, planned or unexpected, are common during the execution of real-life processes. Detecting these changes is a must for optimizing the performance of organizations running such processes. Most of the algorithms present in the state-of-the-art focus on the detection of sudden changes, leaving aside other types of changes. In this paper, we will focus on

Prativa Pritimita, Urjit A. Yajnik, Nitali Dash, Sudhanwa Patra

We derive the lower bound on absolute scale of lightest neutrino mass for normal hierarchy and inverted hierarchy pattern of light neutrinos by studying the new physics contributions to charged lepton flavour violating decays and neutrinoless double beta decay in the framework of a TeV scale left-right symmetric model. Neutrino mass is generated in the model

Yuqing Zhao, Divya Saxena, Jiannong Cao

Managing heterogeneous datasets that vary in complexity, size, and similarity in continual learning presents a significant challenge. Task-agnostic continual learning is necessary to address this challenge, as datasets with varying similarity pose difficulties in distinguishing task boundaries. Conventional task-agnostic continual learning practices typicall

Laurens D. M. Peters, Tanner Culpitt, Erik I. Tellgren, Trygve Helgaker

The Berry connection and curvature are key components of electronic structure calculations for atoms and molecules in magnetic fields. They ensure the correct translational behavior of the effective nuclear Hamiltonian and the correct center-of-mass motion during molecular dynamics in these environments. In this work, we demonstrate how these properties of t

Giovanni Angelini, Giuseppe Cavaliere, Enzo D'Innocenzo, Luca De Angelis

In this paper we propose a new time-varying econometric model, called Time-Varying Poisson AutoRegressive with eXogenous covariates (TV-PARX), suited to model and forecast time series of counts. {We show that the score-driven framework is particularly suitable to recover the evolution of time-varying parameters and provides the required flexibility to model

Konstantinos Panagiotou, Matija Pasch

There is a vast body of recent literature on the reliability of communication through noisy channels, the recovery of community structures in the stochastic block model, the limiting behavior of the free entropy in spin glasses and the solution space structure of constraint satisfaction problems. At first glance, these topics ranging across several disciplin

Christian Joppi, Geri Skenderi, Marco Cristani

We propose a data-centric pipeline able to generate exogenous observation data for the New Fashion Product Performance Forecasting (NFPPF) problem, i.e., predicting the performance of a brand-new clothing probe with no available past observations. Our pipeline manufactures the missing past starting from a single, available image of the clothing probe. It sta

Rüdiger Ehlers, Sven Schewe

While finite automata have minimal DFAs as a simple and natural normal form, deterministic omega-automata do not currently have anything similar. One reason for this is that a normal form for omega-regular languages has to speak about more than acceptance - for example, to have a normal form for a parity language, it should relate every infinite word to some

Prajwol Kumar Nakarmi, Jakob Sternby, Ikram Ullah

False base stations -- IMSI catchers, Stingrays -- are devices that impersonate legitimate base stations, as a part of malicious activities like unauthorized surveillance or communication sabotage. Detecting them on the network side using 3GPP standardized measurement reports is a promising technique. While applying predetermined detection rules works well w

Pierre Raillard, Lorenzo Cristoni, Andrew Walden, Roberto Lazzari

Artificial intelligence-based analysis of lung ultrasound imaging has been demonstrated as an effective technique for rapid diagnostic decision support throughout the COVID-19 pandemic. However, such techniques can require days- or weeks-long training processes and hyper-parameter tuning to develop intelligent deep learning image analysis models. This work f

Andreas Lymperis

Motivated by the exciting features and a recent proposed general form of the function of non-metricity scalar Q, we investigate the cosmological implications in $f(Q)$ gravity, through the resulting effective dark energy sector, extracting analytical expressions for the dark energy density, equation-of-state parameter and the deceleration parameters. We show

Zachary MC Baum, Yipeng Hu, Dean C Barratt

Neural networks have been proposed for medical image registration by learning, with a substantial amount of training data, the optimal transformations between image pairs. These trained networks can further be optimized on a single pair of test images - known as test-time optimization. This work formulates image registration as a meta-learning algorithm. Suc

Zhi-Hong Li, Han-Qing Shi, Hai-Qing Zhang

AdS/CFT correspondence is a "first-principle" tool to study the strongly coupled many-body systems. While it has been extensively applied to investigate the continuous symmetry breaking dynamics, the discrete symmetry breaking dynamics are rarely investigated. In this paper, the model of kink formation in a strongly coupled one-dimensional chain is realized

Zachary MC Baum, Tamas Ungi, Christopher Schlenger, Yipeng Hu

Free Point Transformer (FPT) has been proposed as a data-driven, non-rigid point set registration approach using deep neural networks. As FPT does not assume constraints based on point vicinity or correspondence, it may be trained simply and in a flexible manner by minimizing an unsupervised loss based on the Chamfer Distance. This makes FPT amenable to real

Victor Péron

In this work we derive a WKB expansion for the electromagnetic fields solution of the time-harmonic Maxwell equations set in a domain with a thin layer. As a by-product of this expansion we obtain new second order asymptotic models with generalized impedance transmission conditions that turn out to depend on the mean curvature of the boundary of the subdomai

Manjeet Kaur, Krishan Kumar Chauhan, Tanya Aggarwal, Pushkar Bharadwaj

Fasteners play a critical role in securing various parts of machinery. Deformations such as dents, cracks, and scratches on the surface of fasteners are caused by material properties and incorrect handling of equipment during production processes. As a result, quality control is required to ensure safe and reliable operations. The existing defect inspection

Maria De-Arteaga, Stefan Feuerriegel, Maytal Saar-Tsechansky

The extensive adoption of business analytics (BA) has brought financial gains and increased efficiencies. However, these advances have simultaneously drawn attention to rising legal and ethical challenges when BA inform decisions with fairness implications. As a response to these concerns, the emerging study of algorithmic fairness deals with algorithmic out

A. M. Baldini, H. Benmansour, G. Cavoto, F. Cei

The ultra-low mass cylindrical drift chamber designed for the MEG II experiment is a challenging apparatus made of 1728 phi = 20 micron gold plated tungsten sense wires, 7680 phi = 40 micron and 2496 phi = 50 micron silver plated aluminum field wires. Because of electrostatic stability requirements all the wires have to be stretched at mechanical tensions of

A. Alonso-Izquierdo, D. Miguélez-Caballero, L. M. Nieto, J. Queiroga-Nunes

In this paper the interaction between the shape modes of the wobbling kinks arising in the family of two-component MSTB scalar field theory models is studied. The spectrum of the second order small kink fluctuation in this model has two localized vibrational modes associated to longitudinal and orthogonal fluctuations with respect to the kink orbit. It has b

Thanh Nguyen, Chau Pham, Khoi Nguyen, Minh Hoai

We tackle a new task of few-shot object counting and detection. Given a few exemplar bounding boxes of a target object class, we seek to count and detect all objects of the target class. This task shares the same supervision as the few-shot object counting but additionally outputs the object bounding boxes along with the total object count. To address this c

Hao Jia

We study the dynamics of the two dimensional Navier Stokes equations linearized around a strictly monotonic shear flow on $\mathbb{T}\times\mathbb{R}$. The main task is to understand the associated Rayleigh and Orr-Sommerfeld equations, under the natural assumption that the linearized operator around the monotonic shear flow in the inviscid case has no discr

Matteo Cavaleri, Alfredo Donno, Stefano Spessato

We introduce a switching operation, inspired by the Godsil-McKay switching, in order to obtain pairs of $G$-cospectral gain graphs, that are gain graphs cospectral with respect to every representation of the gain group $G$. For instance, for two signed graphs, this notion of cospectrality is equivalent to the cospectrality of their signed adjacency matrices

Yunlong Ran, Jing Zeng, Shibo He, Lincheng Li

Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying them to autonomous 3D reconstruction, where a robot is required to explore a scene and plan a view path for the reconstruction, has not been studied. In this paper, we explore for t

Alex W. Robinson, Daniel Nicholls, Jack Wells, Amirafshar Moshtaghpour

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we

Myungjun Kim

In this paper, various Miller-compensated amplifiers are analyzed by using the two-port feedback analysis together with the root-locus diagram. The proposed analysis solves problems of Miller theorem/approximation that fail to predict a pole-splitting and that require an impractical assumption that an initial lower frequency pole before connecting a Miller c

Fei Dai, Yawen Chen, Zhiyi Huang, Haibo Zhang

Communication efficiency plays an important role in accelerating the distributed training of Deep Neural Networks (DNN). All-reduce is the crucial communication primitive to reduce model parameters in distributed DNN training. Most existing all-reduce algorithms are designed for traditional electrical interconnect systems, which cannot meet the communication

Yiqing Gu, Qisi Wang, Hongliang Wo, Zheng He

The structurally simplest high-temperature superconductor FeSe exhibits an intriguing superconducting nematic paramagnetic phase with unusual spin excitation spectra that are different from typical spin waves; thus, determining its effective magnetic exchange interactions is challenging. Here we report neutron scattering measurements of spin fluctuations of

Rong Wang, Na-Na Ma, Tao-Feng Wang

In this paper, we examine the hypothesis that the nuclear EMC effect comes merely from the N-N SRC pairs inside the nucleus and that the properties of N-N SRC pair are universal among the various nuclei, using the conventional $x$-rescaling model for the EMC effect. With the previously determined effective mass of the short-range correlated nucleon and the n

Simran Tinani

Several cryptographic protocols constructed based on less-known algorithmic problems, such as those in non-commutative groups, group rings, semigroups, etc., which claim quantum security, have been broken through classical reduction methods within their specific proposed platforms. A rigorous examination of the complexity of these algorithmic problems is the

Benjamin Boutin, Pierre Le Barbenchon, Nicolas Seguin

In this paper, we present a numerical strategy to check the strong stability (or GKS-stability) of one-step explicit totally upwind schemes in 1D with numerical boundary conditions. The underlying approximated continuous problem is the one-dimensional advection equation. The strong stability is studied using the Kreiss-Lopatinskii theory. We introduce a new

E. Chan, J. Pásztorová, R. D. Johnson, M. Songvilay

MnSb$_{2}$O$_{6}$ is based on the structural chiral $P$321 space group #150 where the magnetic Mn$^{2+}$ moments ($S=5/2$, $L\approx 0$) order antiferromagnetically at $T_\mathrm{N}=12$ K. Unlike the related iron based langasite (Ba$_3$NbFe$_3$Si$_2$O$_{14}$) where the low temperature magnetism is based on a proper helix characterized by a time-even pseudosc

Qi'an Guan, Zheng Yuan

In this article, we prove a weighted version of Saitoh's conjecture. As an application, we prove a weighted version of Saitoh's conjecture for higher derivatives.

Santiago Badia, Jesús Bonilla, Juan Vicente Gutiérrez-Santacreu

This paper aims to develop numerical approximations of the Keller--Segel equations that mimic at the discrete level the lower bounds and the energy law of the continuous problem. We solve these equations for two unknowns: the organism (or cell) density, which is a positive variable, and the chemoattractant density, which is a nonnegative variable. We propose

Anastasija Nikiforova

A hackathon is known as a form of civic innovation in which participants representing citizens can point out existing problems or social needs and propose a solution. Given the high social, technical, and economic potential of open government data, the concept of open data hackathons is becoming popular around the world. This concept has become popular in La

Yash Gondhalekar, Margarita Safonova, Snehanshu Saha

Image restoration in astronomy has been considered a vital step in many ground-based observational programs that often suffer from sub-optimal seeing due to atmospheric turbulence, distortion of stellar shapes due to instrumental aberrations, trailing, and other issues. It holds importance for various tasks: improved astrometry, deblending of overlapping sou

Alkim Bozkurt, Han Zhao, Chaitali Joshi, Henry G. LeDuc

Controlling long-lived mechanical oscillators in the quantum regime holds promises for quantum information processing. Here, we present an electromechanical system capable of operating in the GHz-frequency band in a silicon-on-insulator platform. Relying on a novel driving scheme based on an electrostatic field and high-impedance microwave cavities based on

Amin Ghodousiana, Sara Zal

In this paper, we investigate direct solution of FRE and compare their results with expected real consequences. We give an applied example formulated by a FRE problem and show that FRE defined by maximum t-conorm and an arbitrary t-norm can yield different interpretations for our example. A necessary condition and a sufficient condition are presented that gu

Yonghao Dang, Jianqin Yin, Shaojie Zhang, Jiping Liu

Estimating human poses from videos is critical in human-computer interaction. Joints cooperate rather than move independently during human movement. There are both spatial and temporal correlations between joints. Despite the positive results of previous approaches, most focus on modeling the spatial correlation between joints while only straightforwardly in

Lars Schmarje, Stefan Reinhold, Timo Damm, Eric Orwoll

Osteoporosis is a common disease that increases fracture risk. Hip fractures, especially in elderly people, lead to increased morbidity, decreased quality of life and increased mortality. Being a silent disease before fracture, osteoporosis often remains undiagnosed and untreated. Areal bone mineral density (aBMD) assessed by dual-energy X-ray absorptiometry

Zhaoyue Xia, Jun Du, Yong Ren

The distributed subgradient method (DSG) is a widely discussed algorithm to cope with large-scale distributed optimization problems in the arising machine learning applications. Most exisiting works on DSG focus on ideal communication between the cooperative agents such that the shared information between agents is exact and perfect. This assumption, however

Xiujun Wang, Sannian Song, Haomin Wang, Tianqi Guo

Nonvolatile phase change random access memory (PCRAM) is regarded as one of promising candidates for emerging mass storage in the era of Big Data. However, relatively high programming energy hurdles the further reduction of power consumption in PCRAM. Utilizing narrow edge-contact of graphene can effectively reduce the active volume of phase change material

Yuki Ito, Tomohiko Nakamura, Shoichi Koyama, Hiroshi Saruwatari

We propose a method of head-related transfer function (HRTF) interpolation from sparsely measured HRTFs using an autoencoder with source position conditioning. The proposed method is drawn from an analogy between an HRTF interpolation method based on regularized linear regression (RLR) and an autoencoder. Through this analogy, we found the key feature of the

Benjamin Rutkowski, Shoo Seto

We establish an explicit lower bound of the first eigenvalue of the Laplacian on K\"ahler manifolds based off the comparison results of Li and Wang. The lower bound will depend on the diameter, dimension, holomorphic sectional curvature and orthogonal Ricci curvature.

K. Urbanowski

We try to find conditions, the fulfillment of which allows a universe born in a metastable false vacuum state to survive and not to collapse. The conditions found are in the form of inequalities linking the depending on time $t$ instantaneous decay rate ${\it\Gamma}(t)$ of the false vacuum state and the Hubble parameter $H(t)$. Properties of the decay rate o

Jun Liu

Let $I$ and $J$ be two intervals, and let $f, g: I \rightarrow \mathbb{R}$. If for any points $a$ and $b$ in $I$ and any positive numbers $p$ and $q$ such that $p + q = 1$, we have \begin{align} \nonumber p f(a) + q f(b) + g(pa + qb) \in J, \end{align} then for any points $x_{1}, \ldots, x_{n}$ in $I$ and any positive numbers $\lambda_{1}, \ldots, \lambda_{n

H. Beuther, F. Wyrowski, K. M. Menten, J. M. Winters

Context: While star formation on large molecular cloud scales and on small core and disk scales has been investigated intensely over the past decades, the connection of the large-scale interstellar material with the densest small-scale cores has been a largely neglected field. Methods: Using NOEMA and the IRAM 30\,m telescope, we mapped large areas (640\,arc

David Roesel, Maksim Eremchev, Chetan S. Poojari, Jochen S. Hub

Unassisted ion transport through lipid membranes plays a crucial role in many cell functions without which life would not be possible, yet the precise mechanism behind the process remains unknown due to its molecular complexity. Here, we demonstrate a direct link between membrane potential fluctuations and divalent ion transport. High-throughput wide-field s

Simon Roby

With each resonance of the Laplacian acting on the compactly supported sections of a homogeneous vector bundle over a Riemannian symmetric space of the non-compact type, One can associate a residue representation. The purpose of this paper is to study them. The symmetric space is assumed to have rank-one but the irreducible representation {\tau} of K definin

M. Abreu, M. Funk, D. Labbate, F. Romaniello

A graph $G$ admiting a $2$-factor is \textit{pseudo $2$-factor isomorphic} if the parity of the number of cycles in all its $2$-factors is the same. In [M. Abreu, A.A. Diwan, B. Jackson, D. Labbate and J. Sheehan. Pseudo $2$-factor isomorphic regular bipartite graphs. Journal of Combinatorial Theory, Series B, 98(2) (2008), 432-444.] some of the authors of t

Mathieu Pont, Jules Vidal, Julien Tierny

This paper presents a computational framework for the Principal Geodesic Analysis of merge trees (MT-PGA), a novel adaptation of the celebrated Principal Component Analysis (PCA) framework [87] to the Wasserstein metric space of merge trees [92]. We formulate MT-PGA computation as a constrained optimization problem, aiming at adjusting a basis of orthogonal

Fei He, Naiyu Gao, Jian Jia, Xin Zhao

Video object detection has been an important yet challenging topic in computer vision. Traditional methods mainly focus on designing the image-level or box-level feature propagation strategies to exploit temporal information. This paper argues that with a more effective and efficient feature propagation framework, video object detectors can gain improvement

Jiaxing Huang, Tuen Wai Ng

In this paper, we prove a Second Main Theorem for holomorphic mappings in a disk whose image intersects some families of nonlinear hypersurfaces (totally geodesic hypersurfaces with respect to a meromorphic connection) in the complex projective space $\mathbb{P}^k$. This is a generalization of Cartan's Second Main Theorem. As a consequence, we establish a un

Tianzhe Huang, Qixiang Chen, Jinhua Huang, Yuehui Lu

Daytime radiative coolers cool objects below the air temperature without any electricity input, while most of them are limited by a silvery or whitish appearance. Colored daytime radiative coolers (CDRCs) with diverse colors, scalable manufacture, and sub-ambient cooling have not been achieved. We introduce a polymer-Tamm photonic structure to enable a high

Felix Wilsch

Separation of scales in quantum field theories is essential when studying the low-energy phenomenology of a given UV model. To this end, it is necessary to construct an effective field theory containing only the light degrees of freedom and matching it to the full theory, ensuring that both describe the same low-energy dynamics. Performing this matching beyo

Hang Ye, Wentao Zhu, Chunyu Wang, Rujie Wu

While the voxel-based methods have achieved promising results for multi-person 3D pose estimation from multi-cameras, they suffer from heavy computation burdens, especially for large scenes. We present Faster VoxelPose to address the challenge by re-projecting the feature volume to the three two-dimensional coordinate planes and estimating X, Y, Z coordinate

Apurba Das, Satyendra Kumar Mishra

A relative Rota-Baxter algebra is a generalization of a Rota-Baxter algebra. Relative Rota-Baxter algebras are closely related to dendriform algebras. In this paper, we introduce bimodules over a relative Rota-Baxter algebra that fits with the representations of dendriform algebras. We define the cohomology of a relative Rota-Baxter algebra with coefficients

Guanyu Zhang, Beichen Sun, Yuehan Qi, Yang Liu

Multi-sensor fusion is widely used in the environment perception system of the autonomous vehicle. It solves the interference caused by environmental changes and makes the whole driving system safer and more reliable. In this paper, a novel visible and near-infrared fusion method based on texture information is proposed to enhance unstructured environmental

Ekram Alam, Abu Sufian, Paramartha Dutta, Marco Leo

Human fall is one of the very critical health issues, especially for elders and disabled people living alone. The number of elder populations is increasing steadily worldwide. Therefore, human fall detection is becoming an effective technique for assistive living for those people. For assistive living, deep learning and computer vision have been used largely

Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architecture search or knowledge distillation. Recently, an autoencoder trained on a model zoo was able to learn a hyper-representation, which captures intrinsic and extrinsic properties of

Chiara Balestra, Carlo Maj, Emmanuel Mueller, Andreas Mayr

Gene set collections are a common ground to study the enrichment of genes for specific phenotypic traits. Gene set enrichment analysis aims to identify genes that are over-represented in gene sets collections and might be associated with a specific phenotypic trait. However, as this involves a massive number of hypothesis testing, it is often questionable wh

Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé, Makoto Yamada

Recent developments in self-supervised learning give us the possibility to further reduce human intervention in multi-step pipelines where the focus evolves around particular objects of interest. In the present paper, the focus lays in the nuclei in histopathology images. In particular we aim at extracting cellular information in an unsupervised manner for a

Hannaneh Akrami, Bhaskar Ray Chaudhury, Martin Hoefer, Kurt Mehlhorn

We study the problem of allocating a set of indivisible goods among a set of agents with \emph{2-value additive valuations}. In this setting, each good is valued either $1$ or $p/q$, for some fixed co-prime numbers $p,q\in \mathbb{N}$ such that $1\leq q < p$. Our goal is to find an allocation maximizing the \emph{Nash social welfare} (\NSW), i.e., the geomet

Zhiwei Yang, Peng Wu, Jing Liu, Xiaotao Liu

Existing methods for anomaly detection based on memory-augmented autoencoder (AE) have the following drawbacks: (1) Establishing a memory bank requires additional memory space. (2) The fixed number of prototypes from subjective assumptions ignores the data feature differences and diversity. To overcome these drawbacks, we introduce DLAN-AC, a Dynamic Local A

Jose J. Valero-Mas, Antonio Javier Gallego, Pablo Alonso-Jiménez, Xavier Serra

Prototype Generation (PG) methods are typically considered for improving the efficiency of the $k$-Nearest Neighbour ($k$NN) classifier when tackling high-size corpora. Such approaches aim at generating a reduced version of the corpus without decreasing the classification performance when compared to the initial set. Despite their large application in multic

Paul Hüttl, Patrik Knopf, Tim Laux

We investigate a phase-field version of the Faber--Krahn theorem based on a phase-field optimization problem introduced in Garcke et al. [ESAIM Control Optim. Calc. Var. 29 (2023), Paper No. 10] formulated for the principal eigenvalue of the Dirichlet--Laplacian. The shape, that is to be optimized, is represented by a phase-field function mapping into the in

S. Y. Wang, Y. Wang, S. H. Yan, C. Wang

In two-dimensional (2D) ferromagnets, anisotropy is essential for the magnetic ordering as dictated by the Mermin-Wagner theorem. But when competing anisotropies are present, the phase transition becomes nontrivial. Here, utilizing highly sensitive susceptometry of scanning superconducting quantum interference device microscopy, we probe the spin correlation

Riccardo Bonalli, Clara Leparoux, Bruno Hérissé, Frédéric Jean

Statistical linearization has recently seen a particular surge of interest as a numerically cheap method for robust control of stochastic differential equations. Although it has already been successfully applied to control complex stochastic systems, accessibility and controllability properties of statistical linearization, which are key to make the robust c

S. Francesconi, A. Raymond, R. Duhamel, P. Filloux

We demonstrate a chip-integrated semiconductor source that combines polarization and frequency entanglement, allowing the generation of entangled biphoton states in a hybrid degree of freedom without postmanipulation. Our AlGaAs device is based on type-II spontaneous parametric down-conversion (SPDC) in a counterpropagating phase-matching scheme, in which th

Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy

Deep learning (DL) plays a more and more important role in our daily life due to its competitive performance in industrial application domains. As the core of DL-enabled systems, deep neural networks (DNNs) need to be carefully evaluated to ensure the produced models match the expected requirements. In practice, the \emph{de facto standard} to assess the qua

Li Shen, Yuning Wei, Yangzhu Wang

How to handle time features shall be the core question of any time series forecasting model. Ironically, it is often ignored or misunderstood by deep-learning based models, even those baselines which are state-of-the-art. This behavior makes their inefficient, untenable and unstable. In this paper, we rigorously analyze three prevalent but deficient/unfounde

Tristan Laidlow, Michael Bloesch, Wenbin Li, Stefan Leutenegger

While dense visual SLAM methods are capable of estimating dense reconstructions of the environment, they suffer from a lack of robustness in their tracking step, especially when the optimisation is poorly initialised. Sparse visual SLAM systems have attained high levels of accuracy and robustness through the inclusion of inertial measurements in a tightly-co

Paolo Braca, Leonardo M. Millefiori, Augusto Aubry, Stefano Marano

We study the performance -- and specifically the rate at which the error probability converges to zero -- of Machine Learning (ML) classification techniques. Leveraging the theory of large deviations, we provide the mathematical conditions for a ML classifier to exhibit error probabilities that vanish exponentially, say $\sim \exp\left(-n\,I + o(n) \right)$,

F. Šebek, F. Walter, M. Wolf

The VRI light curves were measured for the low-mass eclipsing binary V608 Cam as a part of our long-term observational project for studying of eclipsing binaries with a short orbital period. The Tess light curve solution in Phoebe results to the detached configuration, where the temperature of primary component was fixed to $T_1 = 5300$ K according to Gaia r

Kazuhide Shigemi, Shoichi Koyama, Tomohiko Nakamura, Hiroshi Saruwatari

A sound field estimation method based on a physics-informed convolutional neural network (PICNN) using spline interpolation is proposed. Most of the sound field estimation methods are based on wavefunction expansion, making the estimated function satisfy the Helmholtz equation. However, these methods rely only on physical properties; thus, they suffer from a

Konstantinos Panagiotis Alexandridis, Jiankang Deng, Anh Nguyen, Shan Luo

Major advancements have been made in the field of object detection and segmentation recently. However, when it comes to rare categories, the state-of-the-art methods fail to detect them, resulting in a significant performance gap between rare and frequent categories. In this paper, we identify that Sigmoid or Softmax functions used in deep detectors are a ma

Dongning Liu, Jingyuan Liu, Xiaosong Ren, Xue Feng

The entanglement distribution network connects remote users through sharing entanglement resources, which is essential for realizing quantum internet. We proposed a controllable entanglement distribution network (c-EDN) based on a silicon quantum photonic chip. The entanglement resources were generated by a quantum light source array based on spontaneous fou

Aditya Arie Nugraha, Kouhei Sekiguchi, Mathieu Fontaine, Yoshiaki Bando

This paper describes a practical dual-process speech enhancement system that adapts environment-sensitive frame-online beamforming (front-end) with help from environment-free block-online source separation (back-end). To use minimum variance distortionless response (MVDR) beamforming, one may train a deep neural network (DNN) that estimates time-frequency ma

Song Li, Temurbek Mirzaev, Ahmadjon A. Abdujabbarov, Daniele Malafarina

We consider a black hole mimicker given by an exact solution of the stationary and axially symmetric field equations in vacuum known as the $\delta$-Kerr metric. We study its optical properties based on a ray-tracing code for photon motion and characterize the apparent shape of the shadow of the compact object and compare it with the Kerr black hole. For the

Rui-Ying Mao, Da Wang, Qiang-Hua Wang

We revisit the Hall effect and magnetoresistivity by incorporating the anisotropic scattering caused by apical oxygen vacancies in overdoped La-based cuprates. The theoretical calculations within the Fermi liquid picture agree well with a handful of anomalous magneto-transport data, better than the results using an isotropic scattering rate alone. In particu

Jonathan Bourne, Andrea Ingianni, Rex McKenzie

The UK, particularly London, is a global hub for money laundering, a significant portion of which uses domestic property. However, understanding the distribution and characteristics of offshore domestic property in the UK is challenging due to data availability. This paper attempts to remedy that situation by enhancing a publicly available dataset of UK prop

Narasimha Kumar, Satyabrat Sahoo

In this article, we study the non-trivial primitive solutions of a certain type for the Diophantine equations $x^p+y^p=2^rz^p$ and $x^p+y^p=z^2$ of prime exponent $p$, $r \in \mathbb{N}$, over a totally real field $K$. Then for $r=2,3$, we study the non-trivial primitive solutions over $\mathcal{O}_K$ for the equation $x^p+y^p=2^rz^p$ of prime exponent $p$.

Mahmoud Hamandi, Lakmal Seneviratne, Yahya Zweiri

This paper presents a theoretical study on the ability of multi-rotor aerial vehicles (MRAVs) with tiltable propellers to achieve and sustain static hovering at different orientations. To analyze the ability of MRAVs with tiltable propellers to achieve static hovering, a novel linear map between the platform's control inputs and applied forces and moments is

S. N. Danshin, V. N. Gavrin, V. V. Gorbachev, T. V. Ibragimova

The production of the artificial 51Cr neutrino source with activity > 3 MCi for the experiment BEST is presented. This procedure consisted of making a 50Cr target and irradiating it with thermal neutrons in a nuclear reactor SM-3. The production of a target in the form of disks with a thickness of 4 mm and a diameter of 84 and 88 mm included enrichment (to 9

Deng Wang

The recently released Type Ia supernovae (SNe Ia) sample, Pantheon+, is an updated version of Pantheon and has very important cosmological implications. To explore the origin of the enhanced constraining power and internal correlations of datasets in different redshifts, we perform a comprehensively tomographic analysis of the Pantheon+ sample without and wi

Naoki Kimura, Priti, Yasutaka Kono, Pativate Pipatpakorn

Hyperfine-structures of highly charged ions (HCIs) are favourable spectroscopic targets for exploring fundamental physics as well as nuclear properties. Recent proposals of HCI atomic clocks highlight their importance, especially for many-electron HCIs, and they have been theoretically investigated by refining atomic-structure calculations. Nonetheless, no e

M. Claverol, C. Hernando, M. Maureso, M. Mora

A dominating set of a graph $G$ is a subset $D$ of vertices such that every vertex not in $D$ is adjacent to at least one vertex in $D$. A dominating set $D$ is paired if the subgraph induced by its vertices has a perfect matching, and semipaired if every vertex in $D$ is paired with exactly one other vertex in $D$ that is within distance 2 from it. The pair

Yuri Nakayama, Yuka Takedomi, Towa Suda, Takeaki Uno

Vaccines are promising tools to control the spread of COVID-19. An effective vaccination campaign requires government policies and community engagement, sharing experiences for social support, and voicing concerns to vaccine safety and efficiency. The increasing use of online social platforms allows us to trace large-scale communication and infer public opin

Simon C. Harris, Sandra Palau, Juan Carlos Pardo

We investigate the genealogy of a sample of $k\geq1$ particles chosen uniformly without replacement from a population alive at large times in a critical discrete-time Galton-Watson process in a varying environment (GWVE). We will show that subject to an explicit deterministic time-change involving only the mean and variances of the varying offspring distribu

Gabriele Bogo, Yingkun Li

In this paper, we study the diagonal restrictions of certain Hilbert theta series for a totally real field $F$, and prove that they span the corresponding space of elliptic modular forms when the $F$ is quadratic or cubic. Furthermore, we give evidence of this phenomenon when $F$ is quartic, quintic and sextic.

F. Aharonian, H. Ashkar, M. Backes, V. Barbosa Martins

Young massive stellar clusters are extreme environments and potentially provide the means for efficient particle acceleration. Indeed, they are increasingly considered as being responsible for a significant fraction of cosmic rays (CRs) accelerated within the Milky Way. Westerlund 1, the most massive known young stellar cluster in our Galaxy is a prime candi