April 2023 arXiv papers — page 149

Boyang Lyu, Thuan Nguyen, Matthias Scheutz, Prakash Ishwar

Domain generalization aims to learn a model with good generalization ability, that is, the learned model should not only perform well on several seen domains but also on unseen domains with different data distributions. State-of-the-art domain generalization methods typically train a representation function followed by a classifier jointly to minimize both t

David Codony, Phanish Suryanarayana, Irene Arias

We review the authors' recent works on flexoelectricity at the nanoscale [arXiv:2010.01747, arXiv:2010.13899], while emphasizing the role of continuum mechanics in interpreting the electromechanical response of quantum mechanical systems under bending.

Felicitas Hörmann, Hannes Bartz, Anna-Lena Horlemann

We study the distinguishability of linearized Reed-Solomon (LRS) codes by defining and analyzing analogs of the square-code and the Overbeck distinguisher for classical Reed-Solomon and Gabidulin codes, respectively. Our main results show that the square-code distinguisher works for generalized linearized Reed-Solomon (GLRS) codes defined with the trivial au

Wayne Yuan Gao, Rui Wang

We study identification and estimation of endogenous linear and nonlinear regression models without excluded instrumental variables, based on the standard mean independence condition and a nonlinear relevance condition. Based on the identification results, we propose two semiparametric estimators as well as a discretization-based estimator that does not requ

Yuan Qi Ni, Dae-Sik Moon, Maria R. Drout, Christopher D. Matzner

SN~2021aefx is a normal Type Ia Supernova (SN) with red excess emission over the first $\sim$ 2 days. We present detailed analysis of this SN using our high-cadence KMTNet multi-band photometry, spectroscopy, and publicly available data. We provide the first measurements of its epochs of explosion (MJD 59529.32 $\pm$ 0.16) as well as ``first light'' (MJD 595

Sergio Luigi Cacciatori, Henri Epstein, Ugo Moschella

We reconsider the computation of banana integrals at different loops, by working in the configuration space, in any dimension. We show how the 2-loop banana integral can be computed directly from the configuration space representation, without the need to resort to differential equations, and we include the analytic extension of the diagram in the space of c

Ethan Weitkamp, Yusuke Satani, Adam Omundsen, Jingwen Wang

The machine learning approach is vital in Internet of Things (IoT) malware traffic detection due to its ability to keep pace with the ever-evolving nature of malware. Machine learning algorithms can quickly and accurately analyze the vast amount of data produced by IoT devices, allowing for the real-time identification of malicious network traffic. The syste

Tahmid Alavi Ishmam, Amin Ahsan Ali, Md Ahsraful Amin, A K M Mahbubur Rahman

This paper aims to detect rice field damage from natural disasters in Bangladesh using high-resolution satellite imagery. The authors developed ground truth data for rice field damage from the field level. At first, NDVI differences before and after the disaster are calculated to identify possible crop loss. The areas equal to and above the 0.33 threshold ar

Tuomas Oikari

For exponents $p,q\in (1,\infty),$ we study the $L^p$-to-$L^q$ boundedness and compactness of the commutator $[b,H_{\gamma}] = bH_{\gamma} - H_{\gamma}b,$ where $H_{\gamma}$ is the Hilbert transform along the monomial curve $\gamma$ and the function $b$ is complex valued. We obtain a sparse form domination of the commutator and show that $b\in \operatorname{

Carlos Maldonado, Fernando Mendez

We study the possibility to describe dark matter in a model of the universe with two scale factors and a non-standard Poisson bracket structure characterized by the deformation parameter \kappa. The dark matter evolution is analyzed in the early stages of the universe, and its relic density is obtained via the Freeze-In and Freeze-Out mechanism. We show that

Martin Kolář, Ilya Kossovskiy, David Sykes

We introduce a class of uniformly $2$-nondegenerate CR hypersurfaces in $\mathbb{C}^N$, for $N>3$, having a rank $1$ Levi kernel. The class is first of all remarkable by the fact that for every $N>3$ it forms an {\em explicit} infinite-dimensional family of everywhere $2$-nondegenerate hypersurfaces. To the best of our knowledge, this is the first such const

Joel Creutzberg, Erik Donovan Hedegård

We have recently developed a method based on relativistic time-dependent density functional theory (TD-DFT) that allows the calculation of electronic spectra in solution (Creutzberg, Hedeg{\aa}rd, J. Chem. Theory Comput.18, 2022, 3671). This method treats the solvent explicitly with a classical, polarizable embedding (PE) description. Furthermore, it employs

Takashi Arai

We propose a multivariate probability distribution for categorical and ordinal random variables. To this end, we use the Grassmann distribution in conjunction with dummy encoding of categorical and ordinal variables. To realize the co-occurrence probabilities of dummy variables required for categorical and ordinal variables, we propose a parsimonious paramet

Qing-Jie Li, Mahmut Nedim Cinbiz, Yin Zhang, Qi He

Modeling the full-range deformation behaviors of materials under complex loading and materials conditions is a significant challenge for constitutive relations (CRs) modeling. We propose a general encoder-decoder deep learning framework that can model high-dimensional stress-strain data and complex loading histories with robustness and universal capability.

Fernando Giner

Information retrieval (IR) evaluation measures are cornerstones for determining the suitability and task performance efficiency of retrieval systems. Their metric and scale properties enable to compare one system against another to establish differences or similarities. Based on the representational theory of measurement, this paper determines these properti

Sicong Liang, Junchao Tian, Shujun Yang, Yu Zhang

Federated Learning (FL) aims to learn a single global model that enables the central server to help the model training in local clients without accessing their local data. The key challenge of FL is the heterogeneity of local data in different clients, such as heterogeneous label distribution and feature shift, which could lead to significant performance deg

G. Arduini, L. Badurina, K. Balazs, C. Baynham

We present results from exploratory studies, supported by the Physics Beyond Colliders (PBC) Study Group, of the suitability of a CERN site and its infrastructure for hosting a vertical atom interferometer (AI) with a baseline of about 100 m. We first review the scientific motivations for such an experiment to search for ultralight dark matter and measure gr

Zifeng Ding, Jingpei Wu, Zongyue Li, Yunpu Ma

Temporal knowledge graph completion (TKGC) aims to predict the missing links among the entities in a temporal knwoledge graph (TKG). Most previous TKGC methods only consider predicting the missing links among the entities seen in the training set, while they are unable to achieve great performance in link prediction concerning newly-emerged unseen entities.

Samuel R. Bowman

The widespread public deployment of large language models (LLMs) in recent months has prompted a wave of new attention and engagement from advocates, policymakers, and scholars from many fields. This attention is a timely response to the many urgent questions that this technology raises, but it can sometimes miss important considerations. This paper surveys

Lydia Bieri

We derive new results on radiation, angular momentum at future null infinity and peeling for a general class of spacetimes. For asymptotically-flat solutions of the Einstein vacuum equations with a term homogeneous of degree $-1$ in the initial data metric, that is it may include a non-isotropic mass term, we prove new detailed behavior of the radiation fiel

Hunter Monroe

If no optimal propositional proof system exists, we (and independently Pudl\'ak) prove that ruling out length $t$ proofs of any unprovable sentence is hard. This mapping from unprovable to hard-to-prove sentences powerfully translates facts about noncomputability into complexity theory. For instance, because proving string $x$ is Kolmogorov random ($x{\in}R$

Wei Tang, Jutho Haegeman

In conformal field theories, when the conformal symmetry is enhanced by a global Lie group symmetry, the original Virasoro algebra can be extended to Kac-Moody algebra. In this paper, we extend the lattice construction of the Kac-Moody generators introduced in Wang et al., [Phys. Rev. B. 106, 115111 (2022)] to continuous systems and apply it to one-dimension

Philipp I. Vysikaylo

4D mathematical models of structurally related (conjugated, entangled, dual) phenomena of dissipation and cumulation of electrical energy (an external source in continuous media) are discussed, accompanied by the formation of cumulative-dissipative structures and their ordering into a regular system - a dynamic dissipative "crystal" with a long-range dynamic

Francisco Pipa

The received view in foundations and philosophy of physics holds that if we reject supplementing quantum theory (QT) with certain hidden variables and consider that unitary QT is correct and universal, we should adopt a relationalist interpretation of QT. Relationalist interpretations relativize measurement outcomes to, for example, worlds, systems, agents,

Carlos De la Cruz Mengual

We establish Monod's isomorphism conjecture in degree-three bounded cohomology for every complex simple Lie group of classical type. Our main ingredient is a bounded-cohomological stability theorem with an optimal range in degree three that we bootstrap from previous stability results by the author and Hartnick. The bootstrapping procedure relies on the occu

Langte Ma

We study the moduli space of $G_2$-instantons on (projectively) flat bundles over torsion-free $G_2$-orbifolds. We prove that the moduli space is compact and smooth at the irreducible locus after adding small and generic holonomy perturbations. Consequently, we define an integer-valued invariant that is invariant under $C^0$-deformation of torsion-free $G_2$

Pietro Benetti Genolini, Chiara Toldo

We study the thermodynamics in the BPS limit of AdS black holes realizing the topological twist. We use a limiting procedure that allows us to reach the extremal point along a trajectory in the space of supersymmetric Euclidean solutions. We show that on this space we can write a quantum statistical relation, which is well-defined in the BPS limit and relies

K. Azizi, Y. Sarac, H. Sundu

The recently observed strange pentaquark candidate, $P_{\psi s}^{\Lambda}(4338){}^0$, is investigated to provide information about its nature and substructure. To this end, its mass and width through the decay channels $P_{\psi s}^{\Lambda}(4338){}^0 \rightarrow J/\psi \Lambda$ and $P_{\psi s}^{\Lambda}(4338){}^0 \rightarrow \eta_c \Lambda$ are calculated by

Zhicheng Wu, Xiaoyan Huang, Nanfang Yu, Zongfu Yu

Modeling metasurfaces with high accuracy and efficiency is challenging because they have features smaller than the wavelength but sizes much larger than the wavelength. Full wave simulation is accurate but very slow. Popular design paradigms like locally periodic approximation (LPA) reduce the computational cost by neglecting, partially or fully, near-field

J. P. Linares Fernández, M. Płoszajczak, N. Michel

Spectrum of $^7$Li and elastic scattering reaction $^4$He($^3$H, $^3$H)$^4$He are studied using the unified description of the Gamow shell model in the coupled-channel formulation (GSMCC). The reaction channels are constructed using the cluster expansion with the two mass partitions [$^4$He + $^3$H], [$^6$Li + n].

Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh

Transformations based on domain expertise (expert transformations), such as random-resized-crop and color-jitter, have proven critical to the success of contrastive learning techniques such as SimCLR. Recently, several attempts have been made to replace such domain-specific, human-designed transformations with generated views that are learned. However for im

Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz

Cascaded computation, whereby predictions are recurrently refined over several stages, has been a persistent theme throughout the development of landmark detection models. In this work, we show that the recently proposed Deep Equilibrium Model (DEQ) can be naturally adapted to this form of computation. Our Landmark DEQ (LDEQ) achieves state-of-the-art perfor

Claudia Merger, Alexandre René, Kirsten Fischer, Peter Bouss

One challenge of physics is to explain how collective properties arise from microscopic interactions. Indeed, interactions form the building blocks of almost all physical theories and are described by polynomial terms in the action. The traditional approach is to derive these terms from elementary processes and then use the resulting model to make prediction

Karthik Sivaramakrishnan, Vignesh Sivaramakrishnan, Rosalyn Alex Devonport, Meeko M. K. Oishi

This paper poses a theoretical characterization of the stochastic reachability problem in terms of probability measures, capturing the probability measure of the state of the system that satisfies the reachability specification for all probabilities over a finite horizon. We achieve this by constructing the level sets of the probability measure for all proba

Jose Gaite

Various formulations of the exact renormalization group can be compared in the perturbative domain, in which we have reliable expressions for regularization-independent (universal) quantities. We consider the renormalization of the $\lambda\phi^4$ theory in three dimensions and make a comparison between the sharp-cutoff regularization method and other more r

Apostolos I. Rikos, Andreas Grammenos, Evangelia Kalyvianaki, Christoforos N. Hadjicostis

We propose two distributed iterative algorithms that can be used to solve, in finite time, the distributed optimization problem over quadratic local cost functions in large-scale networks. The first algorithm exhibits synchronous operation whereas the second one exhibits asynchronous operation. Both algorithms share salient features. Specifically, the algori

Charlie Yan, Iman Nodozi, Abhishek Halder

We consider the finite horizon optimal steering of the joint state probability distribution subject to the angular velocity dynamics governed by the Euler equation. The problem and its solution amounts to controlling the spin of a rigid body via feedback, and is of practical importance, for example, in angular stabilization of a spacecraft with stochastic in

Maria Lukacova -- Medvidova, Bangwei She, Yuhuan Yuan

In the present paper we consider the initial data, external force, viscosity coefficients, and heat conductivity coefficient as random data for the compressible Navier--Stokes--Fourier system. The Monte Carlo method, which is frequently used for the approximation of statistical moments, is combined with a suitable deterministic discretisation method in physi

Travis C. Cuvelier, Takashi Tanaka, Robert W. Heath

We propose an adaptive coding approach to achieve linear-quadratic-Gaussian (LQG) control with near-minimum bitrate prefix-free feedback. Our approach combines a recent analysis of a quantizer design for minimum rate LQG control with work on universal lossless source coding for sources on countable alphabets. In the aforementioned quantizer design, it was es

Cheng Deng, Bo Tong, Luoyi Fu, Jiaxin Ding

In the research of end-to-end dialogue systems, using real-world knowledge to generate natural, fluent, and human-like utterances with correct answers is crucial. However, domain-specific conversational dialogue systems may be incoherent and introduce erroneous external information to answer questions due to the out-of-vocabulary issue or the wrong knowledge

Marius Peper, Boudewijn F. Roukema, Krzysztof Bolejko

Curved-spacetime geometric-optics maps derived from a deep photometric survey should contain information about the three-dimensional matter distribution and thus about cosmic voids in the survey, despite projection effects. We explore to what degree sky-plane geometric-optics maps can reveal the presence of intrinsic three-dimensional voids. We carry out a c

Yuren Cong, Wentong Liao, Bodo Rosenhahn, Michael Ying Yang

Learning similarity between scene graphs and images aims to estimate a similarity score given a scene graph and an image. There is currently no research dedicated to this task, although it is critical for scene graph generation and downstream applications. Scene graph generation is conventionally evaluated by Recall$@K$ and mean Recall$@K$, which measure the

Isiaka Aremua, Messan Médard Akouetegan, Komi Sodoga, Mahouton Norbert Hounkonnou

In continuation of our previous works J. Phys. A: Math. Gen. 35, 9355-9365 (2002), J. Phys. A: Math. Gen. 38, 7851 (2005) and Eur. Phys. J. D 72, 172 (2018), we investigate a class of generalized coherent states for associated Jacobi polynomials and hypergeometric functions, satisfying the resolution of the identity with respect to a weight function expresse

Leonard Susskind

Semiclassical gravity and the holographic description of the static patch of de Sitter space appear to disagree about properties of correlation functions. Certain holographic correlation functions are necessarily real whereas their semiclassical counterparts have both real and imaginary parts. The resolution of this apparent contradiction involves the fact t

Urban Larsson, Richard J. Nowakowski, Carlos P. Santos

Combinatorial Game Theory typically studies sequential rulesets with perfect information where two players alternate moves. There are rulesets with {\em entailing moves} that break the alternating play axiom and/or restrict the other player's options within the disjunctive sum components. Although some examples have been analyzed in the classical work Winnin

Rinaldo M. Colombo, Graziano Guerra, Yannick Holle

Consider a balance law where the flux depends explicitly on the space variable. At jump discontinuities, modeling considerations may impose the defect in the conservation of some quantities, thus leading to non conservative products. Below, we deduce the evolution in the smooth case from the jump conditions at discontinuities. Moreover, the resulting framewo

Zsófia Juhász

An encoding of directed acyclic graphs (DAGs) on labeled vertices is proposed, which is a generalisation of the Pr\"ufer code for labeled trees, if a certain orienation on the edges of the tree is introduced. Hence it is shown that the number of sequences $S_1, S_2, \ldots, S_{n-1}$ of subsets of $\{1, 2, \ldots, n\}$ with the property that $|\bigcup_{i=1}^k

Farbod Faraji, Maryam Reza, Aaron Knoll

The dynamics of the neutral atoms in Hall thrusters affect several plasma processes, from the ionization to the electrons' mobility. In the context of Hall thruster's particle-in-cell (PIC) modeling, the neutrals are often treated kinetically, similar to the plasma species, and their interactions with themselves and the ions are resolved using the Direct-Sim

Afagh Mehri Shervedani, Siyu Li, Natawut Monaikul, Bahareh Abbasi

This paper proposes a neural network-based user simulator that can provide a multimodal interactive environment for training Reinforcement Learning (RL) agents in collaborative tasks involving multiple modes of communication. The simulator is trained on the existing ELDERLY-AT-HOME corpus and accommodates multiple modalities such as language, pointing gestur

Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins

Local feature extraction is a standard approach in computer vision for tackling important tasks such as image matching and retrieval. The core assumption of most methods is that images undergo affine transformations, disregarding more complicated effects such as non-rigid deformations. Furthermore, incipient works tailored for non-rigid correspondence still

Ethan Eddy, Erik Scheme, Scott Bateman

Electromyography (EMG) has been explored as an HCI input modality following a long history of success for prosthesis control. While EMG has the potential to address a range of hands-free interaction needs, it has yet to be widely accepted outside of prosthetics due to a perceived lack of robustness and intuitiveness. To understand how EMG input systems can b

Eugene Zhang

In this paper, a generalized version of the von Neumann universe known as the total universe is proposed to formally introduce non-well-founded sets that include infinitons, semi-infinitons and quasi-infinitons in Russell's paradox. All three infinitons are part of infinitely generated sets that are generators of non-well-founded sets. Combining the well-fou

Giorgio Parisi

This is an extended version of my Nobel Lecture, delivered on December $8^{th}$ 2021. I will recall the genesis of the concept of multiple equilibria in natural sciences. I will then describe my contribution to the development of this concept in the framework of statistical mechanics. Finally, I will briefly mention the cornucopia of applications of these id

Jiawei Hu, Ari Stern

We develop a new, coordinate-free formulation of Hamiltonian mechanics on the dual of a Lie algebroid. Our approach uses a connection, rather than coordinates in a local trivialization, to obtain global expressions for the horizontal and vertical dynamics. We show that these dynamics can be obtained in two equivalent ways: (1) using the canonical Lie-Poisson

Juan Pablo Equihua, Maged Ali, Henrik Nordmark, Berthold Lausen

Recommender systems are one of the most successful applications of machine learning and data science. They are successful in a wide variety of application domains, including e-commerce, media streaming content, email marketing, and virtually every industry where personalisation facilitates better user experience or boosts sales and customer engagement. The m

Kosar Asadi, Amin Nassiri-Rad, Hassan Firouzjahi

We study multiple fields inflation in diffusion dominated regime using stochastic $\delta N$ formalism. The fields are under pure Brownian motion in a dS background with boundaries in higher dimensional field space. This setup can be realized towards the final stages of the ultra slow-roll setup where the classical drifts fall off exponentially and the pertu

Katherine Jones-Smith, Harsh Mathur

A new class of Kuiper belt objects that lie beyond Neptune with semimajor axes greater than 250 astronomical units show orbital anomalies that have been interpreted as evidence for an undiscovered ninth planet. We show that a modified gravity theory known as MOND (Modified Newtonian Dynamics) provides an alternative explanation for the anomalies using the we

Juan Pablo Equihua, Henrik Nordmark, Maged Ali, Berthold Lausen

As retailers around the world increase efforts in developing targeted marketing campaigns for different audiences, predicting accurately which customers are most likely to churn ahead of time is crucial for marketing teams in order to increase business profits. This work presents a deep survival framework to predict which customers are at risk of stopping to

Y. S. Lo, R. I. Woodward, N. Walk, M. Lucamarini

Quantum key distribution (QKD) allows secret key exchange between two users with unconditional security. For QKD to be widely deployed, low cost and compactness are crucial requirements alongside high performance. Currently, the majority of QKD systems demonstrated rely on bulk intensity and phase modulators to generate optical pulses with precisely defined

Marc Rigter

Many sequential decision-making problems that are currently automated, such as those in manufacturing or recommender systems, operate in an environment where there is either little uncertainty, or zero risk of catastrophe. As companies and researchers attempt to deploy autonomous systems in less constrained environments, it is increasingly important that we

Seogjoo J. Jang, Young Min Rhee

Fermi's golden rule (FGR) serves as the basis for many expressions of spectroscopic observables and quantum transition rates. The utility of FGR has been demonstrated through decades of experimental confirmation. However, there still remain important cases where the evaluation of a FGR rate is ambiguous or ill-defined. Examples are cases where the rate has d

Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Wei Lin

This paper studies masked autoencoder (MAE) video pre-training for various temporal matching-based downstream tasks, i.e., object-level tracking tasks including video object tracking (VOT) and video object segmentation (VOS), self-supervised visual correspondence learning, dense tracking tasks including optical flow estimation and long-term point tracking, a

Bo Zhou, Huidong Xie, Qiong Liu, Xiongchao Chen

Low-count PET is an efficient way to reduce radiation exposure and acquisition time, but the reconstructed images often suffer from low signal-to-noise ratio (SNR), thus affecting diagnosis and other downstream tasks. Recent advances in deep learning have shown great potential in improving low-count PET image quality, but acquiring a large, centralized, and

Seth Siriya, Jingge Zhu, Dragan Nešić, Ye Pu

We consider the problem of adaptive stabilization for discrete-time, multi-dimensional linear systems with bounded control input constraints and unbounded stochastic disturbances, where the parameters of the true system are unknown. To address this challenge, we propose a certainty-equivalent control scheme which combines online parameter estimation with sat

Darryl Z. Seligman, Amaya Moro-Martín

Since 2017, two macroscopic interstellar objects have been discovered in the inner Solar System, both of which are distinct in nature. The first interstellar object, 1I/`Oumuamua, passed within $\sim63$ lunar distances of the Earth, appeared asteroidal lacking detectable levels of gas or dust loss, yet exhibited a nongravitational acceleration. 1I/`Oumuamua'

Varun Kumar, Somdatta Goswami, Daniel J. Smith, George Em Karniadakis

We develop a data-driven deep neural operator framework to approximate multiple output states for a diesel engine and generate real-time predictions with reasonable accuracy. As emission norms become more stringent, the need for fast and accurate models that enable analysis of system behavior have become an essential requirement for system development. The f

Agata Angelika Rzoska, Aleksandra Drozd-Rzoska

The report discusses the emergence of the Socio-Economic Soft Matter (SE-SM) as the result of interactions between physics and economy. First, demographic changes since the Industrial Revolution onset are tested using Soft Matter science tools. Notable in the support of innovative derivative-based and distortions-sensitive analytic tools. It revealed the Wei

Stoyan Kapralov, Valentin Bakoev, Kaloyan Kapralov

Two algorithms for construction of all closed knight's paths of lengths up to 16 are presented. An approach for classification (up to equivalence) of all such paths is considered. By applying the construction algorithms and classification approach, we enumerate both unrestricted and non-intersecting knight's paths and show the obtained results.

Yu-Ran Zhang, Franco Nori

Multipartite entanglement, characterized by the quantum Fisher information (QFI), plays a central role in quantum-enhanced metrology and understanding quantum many-body physics. With a dynamical generalization of the Mazur-Suzuki relations, we provide a rigorous lower bound on the QFI for the thermal Gibbs states in terms of dynamical symmetries, i.e., opera

Erhard Seiler, Dénes Sexty, Ion-Olimpiu Stamatescu

The Complex Langevin (CL) method to simulate `complex probabilities', ideally produces expectation values for the observables that converge to a limit equal to the expectation values obtained with the original complex `probability' measure. The situation may be spoiled in two ways: failure to converge and convergence to the wrong limit. It was found long ago

Francesco Silino, Fabio Dell'Acqua, Pietro Savazzi, Anna Vizziello

In space applications, hardware (HW) implementation is made more expensive not only by the levels of performance required, but also by complex and rigorous HW qualification tests. Reducing qualification cost and time is thus a key design requirement. In this paper, a new versatile transmitter is proposed for space telemetry, capable of soft-switching across

Athanasia Toliou, Mikael Granvik

All near-Earth asteroids (NEAs) that reach sufficiently small perihelion distances will undergo a so-called super-catastrophic disruption. The mechanisms causing such disruptions are currently unknown or, at least, undetermined. To help guide theoretical and experimental work to understand the disruption mechanism, we use numerical simulations of a synthetic

E. Canessa, L. Tenze

We introduce altiro3D, a free extended library developed to represent reality starting from a given original RGB image or flat video. It allows to generate a light-field (or Native) image or video and get a realistic 3D experience. To synthesize N-number of virtual images and add them sequentially into a Quilt collage, we apply MiDaS models for the monocular

Yuhang Li, Tamar Geller, Youngeun Kim, Priyadarshini Panda

Spiking Neural Networks (SNNs) have recently become more popular as a biologically plausible substitute for traditional Artificial Neural Networks (ANNs). SNNs are cost-efficient and deployment-friendly because they process input in both spatial and temporal manner using binary spikes. However, we observe that the information capacity in SNNs is affected by

Joaquim Brugués, Sonja Hohloch, Pau Mir, Eva Miranda

In this article, we introduce $b$-semitoric systems as a generalization of semitoric systems, specifically tailored for $b$-symplectic manifolds. The objective of this article is to furnish a collection of examples and investigate the distinctive characteristics of these systems. A $b$-semitoric system is a 4-dimensional $b$-integrable system that satisfies

Dominik Baumann, Thomas B. Schön

Event-based methods carefully select when to transmit information to enable high-performance control and estimation over resource-constrained communication networks. However, they come at a cost. For instance, event-based communication induces a higher computational load and increases the complexity of the scheduling problem. Thus, in some cases, allocating

Ningning Wang, Jun Hou, Ziyi Liu, Pengfei Shan

The stoichiometric bulk LuH2 is a paramagnetic metal with high electrical conductivity comparable to simple metals. Here we show that the resistivity of cold-pressed (CP) LuH2 samples varies sensitively upon modifying the grain size or surface conditions via the grinding process, i.e., the CP pellets made of commercially purchased LuH2 powder remain metallic

Viet H. Pham, Thang M. Pham, Giang Nguyen, Long Nguyen

The advent of deep learning has led to a significant gain in machine translation. However, most of the studies required a large parallel dataset which is scarce and expensive to construct and even unavailable for some languages. This paper presents a simple yet effective method to tackle this problem for low-resource languages by augmenting high-quality sent

Olivier Lafitte, Olof Runborg

In this work we show an error estimate for a first order Gaussian beam at a fold caustic, approximating time-harmonic waves governed by the Helmholtz equation. For the caustic that we study the exact solution can be constructed using Airy functions and there are explicit formulae for the Gaussian beam parameters. Via precise comparisons we show that the poin

Shun-Yao Yu, Han Li, Qi-Rong Zhao, Yuan Gao

The possible existence of a quantum spin liquid (QSL) phase, an exotic state of matter with long-range quantum entanglement and fractionalized excitations, in $\alpha$-RuCl$_3$ has sparked widespread interests in exploring QSLs in various Kitaev models under magnetic fields. Recently, a $K$-$J$-$\Gamma$-$\Gamma'$ model has been proposed to accurately describ

Henning Wunderlich

While planar graphs are flat from a topological viewpoint, we observe that they are not from a geometric one. We prove that every planar graph can be embedded into a surface consisting of spheres, glued together in a tree-like fashion. As a technical ingredient we prove a statement implying an inverse of the Jordan curve theorem. This statement helps to iden

Nijara Konch, A. Bharali, S. Pirzada

For a graph $G$, the generalized adjacency matrix $A_\alpha(G)$ is the convex combination of the diagonal matrix $D(G)$ and the adjacency matrix $A(G)$ and is defined as $A_\alpha(G)=\alpha D(G)+(1-\alpha) A(G)$ for $0\leq \alpha \leq 1$. This matrix has been found to be useful in merging the spectral theories of $A(G)$ and the signless Laplacian matrix $Q(G

Yong-Lu Li, Xiaoqian Wu, Xinpeng Liu, Zehao Wang

Action understanding has attracted long-term attention. It can be formed as the mapping from the physical space to the semantic space. Typically, researchers built datasets according to idiosyncratic choices to define classes and push the envelope of benchmarks respectively. Datasets are incompatible with each other like "Isolated Islands" due to semantic ga

Anna K. Yanchenko, Graham Tierney, Joseph Lawson, Christoph Hellmayr

We are most grateful to all discussants for their positive comments and many thought-provoking questions. In addition, the discussants provide a number of useful leads into various areas of the literatures on time series, forecasting and commercial application within which the work in our paper is, of course, just one contribution linked to multiple threads.

Matthew Cavorsi, Frederik Mallmann-Trenn, David Saldaña, Stephanie Gil

Coordination in a large number of networked robots is a challenging task, especially when robots are constantly moving around the environment and there are malicious attacks within the network. Various approaches in the literature exist for detecting malicious robots, such as message sampling or suspicious behavior analysis. However, these approaches require

Daniil A. Ilyukhin

The article studies a generalization of the classical Fermat-Torricelli problem to normed spaces of arbitrary finite dimension. Necessary and sufficient conditions for the uniqueness of the solution of the Fermat-Torricelli problem for any n points in a fixed space are obtained, and more precise conditions for normed planes and three-dimensional spaces are p

Quoc Hoan Tran, Shinji Kikuchi, Hirotaka Oshima

The variational quantum eigensolver (VQE) is a hybrid algorithm that has the potential to provide a quantum advantage in practical chemistry problems that are currently intractable on classical computers. VQE trains parameterized quantum circuits using a classical optimizer to approximate the eigenvalues and eigenstates of a given Hamiltonian. However, VQE f

Deniz Akyazi, Koray Kavakli, Ugur Aygun, Afsun Sahin

Cataract is a common ophthalmic disease in which a cloudy area is formed in the lens of the eye and requires surgical removal and replacement of eye lens. Careful selection of the intraocular lens (IOL) is critical for the post-surgery satisfaction of the patient. Although there are various types of IOLs in the market with different properties, it is challen

Victor Olkhov

We describe how the market-based average and volatility of the "actual" return, which the investors gain within their market sales, depend on the statistical moments, volatilities, and correlations of the current and past market trade values. We describe three successive approximations. First, we derive the dependence of the market-based average and volatili

Miguel Riopedre, Denys Biriukov, Martin Dračínský, Hector Martinez-Seara

Hyaluronan, a sugar polymer found outside the plasma membrane, is a critical component of the extracellular matrix (ECM) scaffold. Hyaluronan's length and moderate negative charge aid in ECM entanglement and solubility. This allows it to effectively foster gel-like conditions, which are critical for supporting and protecting cells in various tissues. As a re

Alexander Ke, Shih-Cheng Huang, Chloe P O'Connell, Michal Klimont

Pretraining on large natural image classification datasets such as ImageNet has aided model development on data-scarce 2D medical tasks. 3D medical tasks often have much less data than 2D medical tasks, prompting practitioners to rely on pretrained 2D models to featurize slices. However, these 2D models have been surpassed by 3D models on 3D computer vision

Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu

User-curated item lists, such as video-based playlists on Youtube and book-based lists on Goodreads, have become prevalent for content sharing on online platforms. Item list continuation is proposed to model the overall trend of a list and predict subsequent items. Recently, Transformer-based models have shown promise in comprehending contextual information

Carlos Carrillo-Tudela, Ludo Visschers

This paper studies the extent to which the cyclicality of occupational mobility shapes that of aggregate unemployment and its duration distribution. We document the relation between workers' occupational mobility and unemployment duration over the long run and business cycle. To interpret this evidence, we develop a multi-sector business cycle model with het

Shrihari D. Pande, Xiaojia Wang, Ivan C. Christov

We develop a theory of fluid--structure interaction (FSI) between an oscillatory Newtonian fluid flow and a compliant conduit. We consider the canonical geometries of a 2D channel with a deformable top wall and an axisymmetric deformable tube. Focusing on the hydrodynamics, we employ a linear relationship between wall displacement and hydrodynamic pressure,

Navid Shervani-Tabar

Bayesian approaches are one of the primary methodologies to tackle an inverse problem in high dimensions. Such an inverse problem arises in hydrology to infer the permeability field given flow data in a porous media. It is common practice to decompose the unknown field into some basis and infer the decomposition parameters instead of directly inferring the u

Binzhou Xia

For groups $G$ that can be generated by an involution and an element of odd prime order, this paper gives a sufficient condition for a certain Cayley graph of $G$ to be a graphical regular representation (GRR), that is, for the Cayley graph to have full automorphism group isomorphic to $G$. This condition enables one to show the existence of GRRs of prescrib

Jundai Nanasawa

Symmetries of knots have been studied extensively, and strongly invertible knots are one of them. Lamm defined the equivariant crossing number $c_t(K)$, the minimum crossing number among all symmetric diagrams for a strongly invertible knot $K$. In this paper, we define $c_2(K)$ for two-bridge knots by restricting diagrams to two types. This gives an upper b

Zuleika Ferre, Patricia Triunfo, José-Ignacio Antón

This paper examines the determinants of fertility among women at different stages of their reproductive lives in Uruguay. To this end, we employ time series analysis methods based on data from 1968 to 2021 and panel data techniques based on department-level statistical information from 1984 to 2019. The results of our first econometric exercise indicate a co

Chao Song, Kai Wang, Yuanyuan Zhang

In this paper, we firstly construct an $L_\infty[1]$-algebra via the method of higher derived brackets, whose Maurer-Cartan elements correspond to relative $\Omega$-family Rota-Baxter algebras structures of weight $\lambda$. For a relative $\Omega$-family Rota-Baxter algebra of weight $\lambda$, the corresponding twisted $ L_{\infty}[1] $-algebra controls it

Keita Hamamoto

Zero-inflated continuous data ubiquitously appear in many fields, in which lots of exactly zero-valued data are observed while others distribute continuously. Due to the mixed structure of discreteness and continuity in its distribution, statistical analysis is challenging especially for multivariate case. In this paper, we propose two copula-based density e