March 2023 arXiv papers — page 117

Emmanouil Giannakakis, Sina Khajehabdollahi, Anna Levina

The evolutionary balance between innate and learned behaviors is highly intricate, and different organisms have found different solutions to this problem. We hypothesize that the emergence and exact form of learning behaviors is naturally connected with the statistics of environmental fluctuations and tasks an organism needs to solve. Here, we study how diff

Qian Yang, Paul J. Green, Chelsea L. MacLeod, Richard M. Plotkin

Extremely variable quasars can also show strong changes in broad-line emission strength and are known as changing-look quasars (CLQs). To study the CLQ transition mechanism, we present a pilot sample of CLQs with X-ray observations in both the bright and faint states. From a sample of quasars with bright-state archival SDSS spectra and (Chandra or XMM-Newton

Bikash Das, Subrata Ghosh, Shamashis Sengupta, Pascale Auban-Senzier

Manipulation of long-range order in two-dimensional (2D) van der Waals (vdW) magnetic materials (e.g., CrI$_3$, CrSiTe$_3$ etc.), exfoliated in few-atomic layer, can be achieved via application of electric field, mechanical-constraint, interface engineering, or even by chemical substitution/doping. Usually, active surface oxidation due to the exposure in the

Shimal Yonuis Abdulhadi, Raghad Nawaf Gergees, Ghazwan Qasim Hasan

Suillus species, in general, are edible mushrooms, and environmentally important that are associated mostly with pine trees in the tropics regions. These fungi considered a remarkable source of phenolic compounds that play a crucial role as antioxidants which may reduce the risk of most human chronic diseases such as cancer, diabetes, asthma, atherosclerosis

Antoine Rignon-Bret

I give a simple proof of the physical process first law of black hole thermodynamics including charged black holes, in which all perturbations are computed on the horizon.

Eyal Baruch, Izhak Bucher

Nonlinear systems and interaction forces are pervasive in many scientific fields, such as nanoscale metrology and materials science, but their accurate identification is challenging due to their complex behaviour and inaccessibility of measured domains. This problem intensifies for continuous systems undergoing distributed, coupled interactions, such as in t

Setu Kumar Basak, Lorenzo Neil, Bradley Reaves, Laurie Williams

According to GitGuardian's monitoring of public GitHub repositories, the exposure of secrets (API keys and other credentials) increased two-fold in 2021 compared to 2020, totaling more than six million secrets. However, no benchmark dataset is publicly available for researchers and tool developers to evaluate secret detection tools that produce many false po

Samuel Grunblatt, Nicholas Saunders, Daniel Huber, Daniel Thorngren

Hot Neptunes, gaseous planets smaller than Saturn ($\sim$ 3-8 R$_\oplus$) with orbital periods less than 10 days, are rare. Models predict this is due to high-energy stellar irradiation stripping planetary atmospheres over time, often leaving behind only rocky planetary cores. We present the discovery of a 6.2 R$_\oplus$(0.55 R$_\mathrm{J}$), 19.2 M$_\oplus$

Philippe Weitz, Viktoria Sartor, Balazs Acs, Stephanie Robertson

Computational pathology methods have the potential to improve access to precision medicine, as well as the reproducibility and accuracy of pathological diagnoses. Particularly the analysis of whole-slide-images (WSIs) of immunohistochemically (IHC) stained tissue sections could benefit from computational pathology methods. However, scoring biomarkers such as

Andrea Agazzi, Jianfeng Lu, Sayan Mukherjee

We analyze Elman-type Recurrent Reural Networks (RNNs) and their training in the mean-field regime. Specifically, we show convergence of gradient descent training dynamics of the RNN to the corresponding mean-field formulation in the large width limit. We also show that the fixed points of the limiting infinite-width dynamics are globally optimal, under some

Michael Morrow, Uwe Nagel

Given a sequence of related modules $M_n$ defined over a sequence of related polynomial rings, one may ask how to simultaneously compute a finite Gr\"obner basis for each $M_n$. Furthermore, one may ask how to simultaneously compute the module of syzygies of each $M_n$. In this paper we address both questions. Working in the setting of OI-modules over a Noet

Yuchen Ge, Janosch Ortmann, Walter Rei

Opportunity cost matrices are interesting in the context of scenario reduction. We provide new algorithms, based on ideas from algebraic geometry, to efficiently compute the opportunity cost matrix using computational algebraic geometry. We demonstrate the efficacy of our algorithms by computing opportunity cost matrices for two stochastic integer programs.

Bob Holdom

We obtain the $\beta$-functions for the two dimensionless couplings of a 4d renormalizable scalar field theory with cubic and quartic 4-derivative interactions. Both couplings can be asymptotically free in the UV, and in some cases also in the IR. This theory illustrates the meaning of unitarity in the presence of a negative norm state. A perturbative calcul

Tianzhen Zhang, Valeria Sheina, Sergio Vlaic, Stéphane Pons

The recent application of topological quantum chemistry to rhombohedral bismuth established the non-trivial band structure of this material. This is a 2$^{nd}$order topological insulator characterized by the presence of topology-imposed hinge-states. The spatial distribution of hinge-states and the possible presence of additional symmetry-protected surface-s

Teddy Lazebnik, Liron Simon-Keren

Data encoding is a common and central operation in most data analysis tasks. The performance of other models downstream in the computational process highly depends on the quality of data encoding. One of the most powerful ways to encode data is using the neural network AutoEncoder (AE) architecture. However, the developers of AE cannot easily influence the p

Maha Asiri, Mohamed Y. Eltabakh

Imperfect databases are very common in many applications due to various reasons ranging from data-entry errors, transmission or integration errors, and wrong instruments' readings, to faulty experimental setups leading to incorrect results. The management and query processing of imperfect databases is a very challenging problem as it requires incorporating t

Adam Bouland, Aditi Dandapani, Anupam Prakash

Stochastic processes play a fundamental role in physics, mathematics, engineering and finance. One potential application of quantum computation is to better approximate properties of stochastic processes. For example, quantum algorithms for Monte Carlo estimation combine a quantum simulation of a stochastic process with amplitude estimation to improve mean e

Pengfei Shan, Ningning Wang, Xiquan Zheng, Qingzheng Qiu

The lutetium dihydride LuH2 is stable at ambient conditions. Here we show that its color undergoes sequential changes from dark blue at ambient pressure to pink at ~2.2 GPa and then to bright red at ~4 GPa upon compression in a diamond anvil cell. Such a pressure-induced color change in LuH2 is reversible and it is very similar to that recently reported in t

Jesse Stern

In this work, we study the number of finite tiles $A\subset\mathbb{Z}^{d}$ of size $\alpha$ that translationally tile a finite $C\subset\mathbb{Z}^{d}$. We consider two tiles $A$ and $A'$ to be congruent if and only if one can be transformed into the other via some translation. We make several significant contributions to the study of this problem. For any $

Shuntaro Tani, Yohei Kobayashi

We investigated femtosecond laser ablation dynamics using THz time-domain spectroscopy. To clarify the breakdown dynamics of materials, we focused on the motion of charged particles and measured the terahertz waves emitted during laser ablation. We revealed that the Coulomb force dominated the ablation process. Furthermore, comparisons of the experimental re

Haichuan Li, Liguo Zhou, Zhenshan Bing, Marzana Khatun

Several autonomous driving strategies have been applied to autonomous vehicles, especially in the collision avoidance area. The purpose of collision avoidance is achieved by adjusting the trajectory of autonomous vehicles (AV) to avoid intersection or overlap with the trajectory of surrounding vehicles. A large number of sophisticated vision algorithms have

Cesar A. Ipanaque Zapata, Fernando R. Chu Rivera

In this paper, we introduce the notion of transversal topological complexity (TTC) for a smooth manifold $X$ with respect to a submanifold of codimension 1 together with basic results about this numerical invariant. In addition, we present several examples of explicit transversal algorithms.

Haichuan Li, Liguo Zhou, Alois Knoll

Autonomous driving has been an active area of research and development, with various strategies being explored for decision-making in autonomous vehicles. Rule-based systems, decision trees, Markov decision processes, and Bayesian networks have been some of the popular methods used to tackle the complexities of traffic conditions and avoid collisions. Howeve

Christos Sourdis

We prove the uniqueness of solutions to the Dafermos regularization viscous wave fan profiles for Riemann solutions of scalar hyperbolic conservation laws. We emphasize that our results are not restricted to the small self-similar viscosity regime. We rely on suitable adaptations of Serrin's sweeping principle and the sliding method from the qualitative theo

Aparajita Bhattacharyya, Ahana Ghoshal, Ujjwal Sen

We explore a small quantum refrigerator consisting of three qubits, each of which is kept in contact with an environment. We consider two settings: one is when there is necessarily transient cooling and the other is when both steady-state and transient coolings prevail. Our primary focus, however, is on the transient cooling phenomena. We show that in the tr

Hugo Aimar, Federico Morana

In this brief note we aim to provide, through a well known class of singular densities in harmonic analysis, a simple approach to the fact that the homogeneity of the universe on scales of the order of a hundred millions light years is completely compatible with the fine-scale condensation of matter and energy. We give precise and quantitative definitions of

Siddharth Singi, Zhanpeng He, Alvin Pan, Sandip Patel

In a Human-in-the-Loop paradigm, a robotic agent is able to act mostly autonomously in solving a task, but can request help from an external expert when needed. However, knowing when to request such assistance is critical: too few requests can lead to the robot making mistakes, but too many requests can overload the expert. In this paper, we present a Reinfo

Tiancheng Li, Ruibo Yan, Kai Da, Hongqi Fan

This paper proposes a heterogenous density fusion approach to scalable multisensor multitarget tracking where the inter-connected sensors run different types of random finite set (RFS) filters according to their respective capacity and need. These diverse RFS filters result in heterogenous multitarget densities that are to be fused with each other in a prope

Luca F. Di Cerbo, Luigi Lombardi

We prove the Singer conjecture for varieties with semismall Albanese map and residually finite fundamental group.

K. B. Nakshatrala, K. Adhikari

One of the ways natural and synthetic systems regulate temperature is via circulating fluids through vasculatures embedded within their bodies. Because of the flexibility and availability of proven fabrication techniques, vascular-based thermal regulation is attractive for thin microvascular systems. Although preliminary designs and experiments demonstrate t

Chunyu Guo, A. Alexandradinata, Carsten Putzke, Amelia Estry

We thank G.P. Mikitik and Yu.V. Sharlai for contributing this note and the cordial exchange about it. First and foremost, we note that the aim of our paper is to report a methodology to diagnose topological (semi)metals using magnetic quantum oscillations. Thus far, such diagnosis has been based on the phase offset of quantum oscillations, which is extracted

Anwesh Ray

Let $p\geq 5$ be a prime number. We consider the Iwasawa $\lambda$-invariants associated to modular Bloch-Kato Selmer groups, considered over the cyclotomic $\mathbb{Z}_p$-extension of $\mathbb{Q}$. Let $g$ be a $p$-ordinary cuspidal newform of weight $2$ and trivial nebentype. We assume that the $\mu$-invariant of $g$ vanishes, and that the image of the res

Yuanhao Cai, Hao Bian, Jing Lin, Haoqian Wang

When enhancing low-light images, many deep learning algorithms are based on the Retinex theory. However, the Retinex model does not consider the corruptions hidden in the dark or introduced by the light-up process. Besides, these methods usually require a tedious multi-stage training pipeline and rely on convolutional neural networks, showing limitations in

Tetsu Masuda, Naoto Okubo, Teruhisa Tsuda

A cluster algebra is an algebraic structure generated by operations of a quiver (a directed graph) called the mutations and their associated simple birational mappings. By using a graph-combinatorial approach, we present a systematic way to derive a tropical, i.e. subtraction-free birational, representation of Weyl groups from cluster algebras. Our results p

Sergio Salvía Fernández, Xing Gao, Silvia Cassanelli, Stephan Bron

Experimental insight in the nanoscale dynamics underlying switching in novel memristive devices is limited owing to the scarcity of techniques that can probe the electronic structure of these devices. Scattering scanning near-field optical microscopy is a relatively novel approach to probe the optical response of materials with a spatial resolution well belo

Veronica Danesi, Ugo Locatelli, Marco Sansottera

We investigate the long-term dynamics of HD60532, an extrasolar system hosting two giant planets orbiting in a 3:1 mean motion resonance. We consider an average approximation at order one in the masses which results (after the reduction of the constants of motion) in a resonant Hamiltonian with two libration angles. In this framework, the usual algorithms co

Job Boerma, Aleh Tsyvinski, Ruodu Wang, Zhenyuan Zhang

This paper introduces an assignment model with concave costs of skill gaps, which arise generally when firms mitigate costs of mismatch as in Stigler (1939) and Laffont and Tirole (1986, 1991). Concave costs of skill gaps imply that the output function is neither supermodular nor submodular. We thus introduce a tractable model that interpolates between the p

A. L. Agore, A. Chirvasitu, G. Militaru

We prove that the category of solutions of the set-theoretic Yang-Baxter equation of Frobenius-Separability (FS) type is equivalent to the category of pointed Kimura semigroups. As applications, all involutive, idempotent, nondegenerate, surjective, finite order, unitary or indecomposable solutions of FS type are classified. For instance, if $|X| = n$, then

Sayan Banerjee, Prabhanka Deka, Mariana Olvera-Cravioto

We present new results on community recovery based on the PageRank Nibble algorithm on a sparse directed stochastic block model (dSBM). Our results are based on a characterization of the local weak limit of the dSBM and the limiting PageRank distribution. This characterization allows us to estimate the probability of misclassification for any given connectio

Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee

Combining machine learning and constrained optimization, Predict+Optimize tackles optimization problems containing parameters that are unknown at the time of solving. Prior works focus on cases with unknowns only in the objectives. A new framework was recently proposed to cater for unknowns also in constraints by introducing a loss function, called Post-hoc

Hao Chen, Jiaze Wang, Kun Shao, Furui Liu

Trajectory prediction has been a crucial task in building a reliable autonomous driving system by anticipating possible dangers. One key issue is to generate consistent trajectory predictions without colliding. To overcome the challenge, we propose an efficient masked autoencoder for trajectory prediction (Traj-MAE) that better represents the complicated beh

Mahdi Zaman, Md Saifuddin, Mahdi Razzaghpour, Yaser Fallah

Cellular Vehicle-to-Everything (C-V2X) is a frontier in the evolution of distributed communication introduced in 3GPP release 14 to advanced use cases. While research efforts continue to optimize the accessible bandwidth for transportation ecosystem, a bottom up analysis from the application layer perspective is necessary prior to deployment, as it can expos

Dana Azouri, Oz Granit, Michael Alburquerque, Yishay Mansour

We propose a reinforcement-learning algorithm to tackle the challenge of reconstructing phylogenetic trees. The search for the tree that best describes the data is algorithmically challenging, thus all current algorithms for phylogeny reconstruction use various heuristics to make it feasible. In this study, we demonstrate that reinforcement learning can be u

María Florencia Acosta, Hugo Aimar, Ivana Gómez, Federico Morana

In this note we explore the structure of the diffusion metric of Coifman-Lafon determined by fractional dyadic Laplacians. The main result is that, for each ${t>0}$, the diffusion metric is a function of the dyadic distance, given in $\mathbb{R}^+$ by $\delta(x,y) = \inf\{|I|: I \text{ is a dyadic interval containing } x \text{ and } y\}$. Even if these func

Roberto de A. Capistrano Filho, Fernando Gallego, Vilmos Komornik

We study the asymptotic behavior of the solutions of the time-delayed higher-order dispersive nonlinear differential equation \begin{equation*} u_t(x,t)+Au(x,t) +\lambda_0(x) u(x,t)+\lambda(x) u(x,t-\tau )=0 \end{equation*} where \begin{equation*} Au=(-1)^{j+1}\partial_x^{2j+1}u+(-1)^m\partial_x^{2m}u+ \frac{1}{p+1}\partial_xu^{p+1} \end{equation*} with $m\l

Shubhrasish Mukherjee, Didhiti Bhattacharya, Samit Kumar Ray, Atindra Nath Pal

The possibility of creating heterostructure of two-dimensional (2D) materials has emerged as a viable route towards realizing novel optoelectronic devices. However, the low light absorption due to their small absorption cross section, limits their realistic application. While light-matter interaction mediated by strong exciton-plasmon coupling has been demon

Kwabena Nuamah, Alan Bundy

Recent developments in support for constructing knowledge graphs have led to a rapid rise in their creation both on the Web and within organisations. Added to existing sources of data, including relational databases, APIs, etc., there is a strong demand for techniques to query these diverse sources of knowledge. While formal query languages, such as SPARQL,

Junfeng Qiao, Giovanni Pizzi, Nicola Marzari

Maximally-localized Wannier functions (MLWFs) are a powerful and broadly used tool to characterize the electronic structure of materials, from chemical bonding to dielectric response to topological properties. Most generally, one can construct MLWFs that describe isolated band manifolds, e.g. for the valence bands of insulators, or entangled band manifolds,

Bruno Kahn, with an appendix by Cyril Demarche

We prove all conjectures from chapter 7 of Yves Andr\'e's book on motives in the case of products of elliptic curves. The proofs given here are simpler and more uniform than the previous proofs in known cases.

Xue Jiang, Yihong Dong, Lecheng Wang, Zheng Fang

Although large language models (LLMs) have demonstrated impressive ability in code generation, they are still struggling to address the complicated intent provided by humans. It is widely acknowledged that humans typically employ planning to decompose complex problems and schedule solution steps prior to implementation. To this end, we introduce planning int

Sean Holman, Vasiliki Torega

This work concerns inverse boundary value problems for the time-harmonic Maxwell's equations on differential $1-$forms. We formulate the boundary value problem on a $3-$dimensional compact and simply connected Riemannian manifold $M$ with boundary $\partial M$ endowed with a Riemannian metric $g$. Assuming that the electric permittivity $\varepsilon$ and mag

Bin Cai, Hanlin Li, Yifan Wu, Xin Tao

Magnetic field line curvature (FLC) scattering is a collisionless scattering mechanism that arises when a particle's gyro-radius is comparable to the magnetic field line's curvature radius, resulting in the breaking of the conservation of the first adiabatic invariant. Studies in recent years have explored the implications of FLC scattering on the precipitat

Jan Jakubův, Karel Chvalovský, Zarathustra Goertzel, Cezary Kaliszyk

As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60\% of the Mizar theorems in the hammer setting. We also automatically prove 75\% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale expe

Amjad Sohail, Zaheer Abbas, Rizwan Ahmed, Aamir Shahzad

Gaussian quantum steering is a type of quantum correlation in which two entangled states exhibit asymmetry. We present an efficient theoretical scheme for controlling quantum steering and enhancing entanglement in a Laguerre-Gaussian (LG) rotating cavity optomechanical system with an optical parametric amplifier (OPA) driven by coherent light. The numerical

Supun B. Attanayake, Amit Chanda, Thomas Hulse, Raja Das

The inherent existence of multi phases in iron oxide nanostructures highlights the significance of them being investigated deliberately to understand and possibly control the phases. Here, the effects of annealing at 250 0C with a variable duration on the bulk magnetic and structural properties of high aspect ratio bi-phase iron oxide nanorods with ferrimagn

Jingshun Liu, Feng Wang, Meifang Huang, Yun Zhang

This paper systematically studies the changes in the microstructure and magnetic properties of CoFeSiBNb$_3$ metallic microfibers before and after AC annealing. The influence of current intensity on the magneto-impedance (MI) effect of the microfibers was analyzed and the microstructure changes of the microfibers before and after annealing were explored by m

Yuchun Miao, Lefei Zhang, Liangpei Zhang, Dacheng Tao

Diffusion models have recently received a surge of interest due to their impressive performance for image restoration, especially in terms of noise robustness. However, existing diffusion-based methods are trained on a large amount of training data and perform very well in-distribution, but can be quite susceptible to distribution shift. This is especially i

Carlos Navia, Marcel de Oliveira, Andre Nepomuceno

We look for a diurnal anisotropy in the cosmic ray flow, using the Mexico-City Neutron Monitor (NM) detector, due to the Earth's orbital motion and predicted by Compton-Getting (C-G) in 1935, as a first-order relativistic effect. The Mexico-City NM's geographic latitude is not very high ($19.33^{\circ}$N), and it has a high cutoff geomagnetic rigidity (8.2 G

Yiqun Lin, Zhongjin Luo, Wei Zhao, Xiaomeng Li

Sparse-view cone-beam CT (CBCT) reconstruction is an important direction to reduce radiation dose and benefit clinical applications. Previous voxel-based generation methods represent the CT as discrete voxels, resulting in high memory requirements and limited spatial resolution due to the use of 3D decoders. In this paper, we formulate the CT volume as a con

Mikhail Dubinin, Elena Fedotova

A non-minimal approximation for effective masses of light and heavy neutrinos in the framework of a type-I seesaw mechanism with three generations of sterile Majorana neutrinos which recover the symmetry between quarks and leptons is considered. The main results are: (a) the next-order corrections to the effective mass matrix of heavy neutrinos due to terms

Min Zhang, Zifeng Zhuang, Zhitao Wang, Donglin Wang

Gradient-based meta-learning (GBML) algorithms are able to fast adapt to new tasks by transferring the learned meta-knowledge, while assuming that all tasks come from the same distribution (in-distribution, ID). However, in the real world, they often suffer from an out-of-distribution (OOD) generalization problem, where tasks come from different distribution

Zahir Belhadi

Recently, Belhadi and al. (2014) developed a new approach to quantize classical soluble systems based on the calculation of brackets among fundamental variables using the constants of integration (CI method). In this paper, we will apply this approach in some exactly soluble constrained Hamiltonian systems. We will complete our work with some applications in

Yi Wang, Jiaze Wang, Jinpeng Li, Zixu Zhao

Data augmentation is an effective regularization strategy for mitigating overfitting in deep neural networks, and it plays a crucial role in 3D vision tasks, where the point cloud data is relatively limited. While mixing-based augmentation has shown promise for point clouds, previous methods mix point clouds either on block level or point level, which has co

Chuang Li, Shaochong Zhu, Peitong He, Yingying Wang

We experimentally demonstrate a nano-scale stochastic Stirling heat engine operating in the underdamped regime. The setup involves an optically levitated silica particle that is subjected to a power-varying optical trap and periodically coupled to a cold/hot reservoir via switching on/off active feedback cooling. We conduct a systematic investigation of the

Bohan Li, Shaowei Cai

Satisfiability Modulo Theories (SMT) has significant application in various domains. In this paper, we focus on quantifier-free Satisfiablity Modulo Real Arithmetic, referred to as SMT(RA), including both linear and non-linear real arithmetic theories. As for non-linear real arithmetic theory, we focus on one of its important fragments where the atomic const

Zahir Belhadi

In this paper, we present an approach to quantize singular systems. This is an extension of the constant integration method (Belhadi et al. (2014)) which is applicable only for the case of exactly solvable systems. In our approach, we determine Dirac brackets at the initial instant with the help of Taylor expansion, and using their covariance, we deduce the

Shima Foolad, Kourosh Kiani

Incorporating prior knowledge can improve existing pre-training models in cloze-style machine reading and has become a new trend in recent studies. Notably, most of the existing models have integrated external knowledge graphs (KG) and transformer-based models, such as BERT into a unified data structure. However, selecting the most relevant ambiguous entitie

Bin Yan, Yi Jiang, Jiannan Wu, Dong Wang

All instance perception tasks aim at finding certain objects specified by some queries such as category names, language expressions, and target annotations, but this complete field has been split into multiple independent subtasks. In this work, we present a universal instance perception model of the next generation, termed UNINEXT. UNINEXT reformulates dive

Haonan Han, Rui Yang, Shuyan Li, Runze Hu

Interactive devices with touch screen have become commonly used in various aspects of daily life, which raises the demand for high production quality of touch screen glass. While it is desirable to develop effective defect detection technologies to optimize the automatic touch screen production lines, the development of these technologies suffers from the la

Michael Thobias Schmid, Jean-Baptiste Morée, Ryui Kaneko, Youhei Yamaji

We numerically analyze superconductivity (SC) in the cuprate superconductors by using ab initio effective Hamiltonians consisting of the antibonding combination of Cu $3d_{x^2-y^2}$ and O $2p_{\sigma}$ orbitals. We perform variational Monte Carlo calculations for the four carrier doped cuprates with diverse experimental optimal SC critical temperature $T_{c}

Elena Giammatteo, Alexander Heinlein, Matthias Schlottbom

In this work we propose and analyze an extension of the approximate component mode synthesis (ACMS) method to the heterogeneous Helmholtz equation. The ACMS method has originally been introduced by Hetmaniuk and Lehoucq as a multiscale method to solve elliptic partial differential equations. The ACMS method uses a domain decomposition to separate the numeric

Xinye Wanyan, Sachith Seneviratne, Shuchang Shen, Michael Kirley

Since large number of high-quality remote sensing images are readily accessible, exploiting the corpus of images with less manual annotation draws increasing attention. Self-supervised models acquire general feature representations by formulating a pretext task that generates pseudo-labels for massive unlabeled data to provide supervision for training. While

Evanthia Papadopoulou

Any system of bisectors (in the sense of abstract Voronoi diagrams) defines an arrangement of simple curves in the plane. We define Voronoi-like graphs on such an arrangement, which are graphs whose vertices are locally Voronoi. A vertex $v$ is called locally Voronoi, if $v$ and its incident edges appear in the Voronoi diagram of three sites. In a so-called

Yukun Guo, Abdul Wahab, Xianchao Wang

The reconstruction of multipolar acoustic or electromagnetic sources from their far-field signature plays a crucial role in numerous applications. Most of the existing techniques require dense multi-frequency data at the Nyquist sampling rate. The availability of a sub-sampled grid contributes to the null space of the inverse source-to-data operator, which c

Xiangying Chen

Matroids and semigraphoids are discrete structures abstracting and generalizing linear independence among vectors and conditional independence among random variables, respectively. Despite the different nature of conditional independence from linear independence, deep connections between these two areas are found and still undergoing active research. In this

Xiu-Juan Li, Wen-Long Zhang, Shuang-Xi Yi, Yu-Peng Yang

The prompt phase of gamma-ray burst (GRB) contains essential information regarding the physical nature and central engine, which are as yet unknown. In this paper, we investigate the self-organized criticality (SOC) phenomena in GRB prompt phase as done in X-ray flares of GRBs. We obtain the differential and cumulative distributions of 243 short GRB pulses,

Mickaël Buchet, Bianca B. Dornelas, Michael Kerber

For a finite set of balls of radius $r$, the $k$-fold cover is the space covered by at least $k$ balls. Fixing the ball centers and varying the radius, we obtain a nested sequence of spaces that is called the $k$-fold filtration of the centers. For $k=1$, the construction is the union-of-balls filtration that is popular in topological data analysis. For larg

Hendrik Kähler, Robert Winkler, Holger Arthaber, Harald Plank

Nanoelectromechanical systems (NEMS) have proven outstanding performance in the detection of small masses down to single proton sensitivity. To obtain a high enough throughput for the application in practical mass spectrometry, NEMS resonators have to be arranged in two-dimensional (2D) arrays. However, all state-of-the-art electromechanical transduction met

Islam Debicha, Benjamin Cochez, Tayeb Kenaza, Thibault Debatty

Due to the numerous advantages of machine learning (ML) algorithms, many applications now incorporate them. However, many studies in the field of image classification have shown that MLs can be fooled by a variety of adversarial attacks. These attacks take advantage of ML algorithms' inherent vulnerability. This raises many questions in the cybersecurity fie

Mathieu Renault, Siamak Mehrkanoon

The accuracy and explainability of data-driven nowcasting models are of great importance in many socio-economic sectors reliant on weather-dependent decision making. This paper proposes a novel architecture called Small Attention Residual UNet (SAR-UNet) for precipitation and cloud cover nowcasting. Here, SmaAt-UNet is used as a core model and is further equ

Zhengrui Ma, Chenze Shao, Shangtong Gui, Min Zhang

Non-autoregressive translation (NAT) reduces the decoding latency but suffers from performance degradation due to the multi-modality problem. Recently, the structure of directed acyclic graph has achieved great success in NAT, which tackles the multi-modality problem by introducing dependency between vertices. However, training it with negative log-likelihoo

Ahmed Patwa, Muhammad Mahboob Ur Rahman, Tareq Y. Al-Naffouri

Heart murmurs provide valuable information about mechanical activity of the heart, which aids in diagnosis of various heart valve diseases. This work does automatic and accurate heart murmur detection from phonocardiogram (PCG) recordings. Two public PCG datasets (CirCor Digiscope 2022 dataset and PCG 2016 dataset) from Physionet online database are utilized

Antonio Di Noia, Gianluca Mastrantonio, Giovanna Jona Lasinio

Building on Dryden et al. (2021), this note presents the Bayesian estimation of a regression model for size-and-shape response variables with Gaussian landmarks. Our proposal fits into the framework of Bayesian latent variable models and allows a highly flexible modelling framework.

Chen Xu, Sirui Chen, Jun Xu, Weiran Shen

In this paper, we address the issue of recommending fairly from the aspect of providers, which has become increasingly essential in multistakeholder recommender systems. Existing studies on provider fairness usually focused on designing proportion fairness (PF) metrics that first consider systematic fairness. However, sociological researches show that to mak

Sahil Tyagi, Prateek Sharma

While the pay-as-you-go nature of cloud virtual machines (VMs) makes it easy to spin-up large clusters for training ML models, it can also lead to ballooning costs. The 100s of virtual machine sizes provided by cloud platforms also makes it extremely challenging to select the ``right'' cloud cluster configuration for training. Furthermore, the training time

Tsung-Chih Lai, Jiun-Hua Su

This paper proposes a nonparametric estimator of the counterfactual copula of two outcome variables that would be affected by a policy intervention. The proposed estimator allows policymakers to conduct ex-ante evaluations by comparing the estimated counterfactual and actual copulas as well as their corresponding measures of association. Asymptotic propertie

Egor Chistov, Nikita Alutis, Dmitriy Vatolin

Stereoscopic videos can contain color mismatches between the left and right views due to minor variations in camera settings, lenses, and even object reflections captured from different positions. The presence of color mismatches can lead to viewer discomfort and headaches. This problem can be solved by transferring color between stereoscopic views, but trad

Fangyi Zhang, Peter Corke

Finger-tip tactile sensors are increasingly used for robotic sensing to establish stable grasps and to infer object properties. Promising performance has been shown in a number of works for inferring adjectives that describe the object, but there remains a question about how each taxel contributes to the performance. This paper explores this question with em

Dmitry Anchishkin

A quantum generalization of the Cooper-Fry recipe is proposed. The single-particle spectrum arising from relativistic collisions of particles and nuclei is calculated within the thermal quantum field theory framework. The starting point of consideration is the solution of the initial-value problem of particle emission from a space-like hypersurface. In the f

Esther Derman, Yevgeniy Men, Matthieu Geist, Shie Mannor

Robust Markov decision processes (MDPs) aim to handle changing or partially known system dynamics. To solve them, one typically resorts to robust optimization methods. However, this significantly increases computational complexity and limits scalability in both learning and planning. On the other hand, regularized MDPs show more stability in policy learning

Roberto Garrappa, Andrea Giusti

We investigate the properties of some recently developed variable-order differential operators involving order transition functions of exponential type. Since the characterisation of such operators is performed in the Laplace domain it is necessary to resort to accurate numerical methods to derive the corresponding behaviours in the time domain. In this rega

Weiquan Liu, Minghao Liu, Shijun Zheng, Cheng Wang

Although 3D point cloud classification neural network models have been widely used, the in-depth interpretation of the activation of the neurons and layers is still a challenge. We propose a novel approach, named Relevance Flow, to interpret the hidden semantics of 3D point cloud classification neural networks. It delivers the class Relevance to the activate

Ralph Stömmer

In economy, markets are denoted as efficient when it is impossible to systematically generate profits which outperform the average. In the past years, the concept has been tested in other domains such as the growing sports betting market. Surprisingly, despite its large size and its level of maturity, sports betting shows traits of inefficiency. The anomalie

Amit Kumar, Debasisha Mishra

Motivated by the very recent work of Gao, Y., Chen, J., Wang, J., Zou, H. [Comm. Algebra, 49(8) (2021) 3241-3254; MR4283143], we introduce two new generalized inverses named weak Drazin (WD) and weak Drazin Moore-Penrose (WDMP) inverses for elements in rings. A few of their properties are then provided, and the fact that the proposed generalized inverses coi

Bidisha Bandyopadhyay, Christian Fendt, Dominik R. G. Schleicher, Javier Lagunas

The Event Horizon Telescope Collaboration (EHTC) has presented first - dynamic-range limited - images of the black hole shadows in M87 and Sgr A*. The next generation Event Horizon Telescope (ngEHT) will provide higher sensitivity and higher dynamic range images (and movies) of these two sources plus image at least a dozen others at $\leq$100 gravitational r

Waqas Aman, Saif Al-Kuwari, Marwa Qaraqe

Research in underwater communication is rapidly becoming attractive due to its various modern applications. An efficient mechanism to secure such communication is via physical layer security. In this paper, we propose a novel physical layer authentication (PLA) mechanism in underwater acoustic communication networks where we exploit the position/location of

Liang Cheng

By using the Yamabe flow, we prove that if $(M^n,g)$, $n\geq3$, is an $n$-dimensional locally conformally flat complete Riemannian manifold $Rc\geq \epsilon Rg>0$, where $\epsilon>0$ is a uniformly constant, then $M^n$ must be compact. Our result shows that Hamilton's pinching conjecture also holds for higher dimensional case if we assume additionally the me

Jiaqi Liao, Zequn Lv, Mengyu Cao, Mei Lu

Let $ k, m, n $ be positive integers with $ k \geq 2 $. A $ k $-multiset of $ [n]_m $ is a collection of $ k $ integers from the set $ \{1, 2, \ldots, n\} $ in which the integers can appear more than once but at most $ m $ times. A family of such $ k $-multisets is called an intersecting family if every pair of $ k $-multisets from the family have non-empty

Jie Xu, Yuefei Zheng

We introduce the concept of a pseudo-cluster tilting subcategory from the viewpoint of the fact that the quotient of an exact category by a cluster tilting subcategory is an abelian category. We prove that the quotients in the case of pseudo-cluster tilting are always semi-abelian. In addition, it is abelian if and only if some self-orthogonal conditions are

Yu-Zhe Liu, Chao Zhang

The Cohen-Macaulay Auslander algebra of any string algebra is explicitly constructed in this paper. Furthermore, we show that a class of special string algebras, which are called to be string algebras with G-condition, are representation-finite if and only if their Cohen-Macaulay Auslander algebras are representation-finite. Finally, the self-injective dimen