May 2022 arXiv papers — page 46

Ruben Gamboa, Woodrow Gamboa

If p is a prime, then the numbers 1, 2, ..., p-1 form a group under multiplication modulo p. A number g that generates this group is called a primitive root of p; i.e., g is such that every number between 1 and p-1 can be written as a power of g modulo p. Building on prior work in the ACL2 community, this paper describes a constructive proof that every prime

Mohammad Esmaeilpour, Nourhene Chaalia, Adel Abusitta, Francois-Xavier Devailly

This paper introduces a novel generative adversarial network (GAN) for synthesizing large-scale tabular databases which contain various features such as continuous, discrete, and binary. Technically, our GAN belongs to the category of class-conditioned generative models with a predefined conditional vector. However, we propose a new formulation for deriving

Qianli Xu, Nicolas Gauthier, Wenyu Liang, Fen Fang

When deploying a robot to a new task, one often has to train it to detect novel objects, which is time-consuming and labor-intensive. We present TAILOR -- a method and system for object registration with active and incremental learning. When instructed by a human teacher to register an object, TAILOR is able to automatically select viewpoints to capture info

Chenqing Hua, Guillaume Rabusseau, Jian Tang

Graph Neural Networks (GNNs) are attracting growing attention due to their effectiveness and flexibility in modeling a variety of graph-structured data. Exiting GNN architectures usually adopt simple pooling operations (eg. sum, average, max) when aggregating messages from a local neighborhood for updating node representation or pooling node representations

Amine El Hattami, Stefania Raimondo, Issam Laradji, David Vazquez

Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can sometimes be codified into workflows and used to guide humans or artificial agents through the task of helping clients. We introduce a new problem formulation that we call Workflow Discovery (WD) in which we are interested in

Juho Lee, Muhammad Ejaz Khan, Yong-Hoon Kim

While low-dimensional organometal halide perovskites are expected to open up new opportunities for a diverse range of device applications, like in their bulk counterparts, the toxicity of Pb-based halide perovskite materials is a significant concern that hinders their practical use. We recently predicted that lead triiodide (PbI$_3$) columns de-rived from tr

Naoko Kamada

Jin and Lee proved the following: Suppose that $D_1, \dots, D_n$ are link diagrams. Given a link $L$ which is partitioned into sublinks $L_1, \dots, L_n$ admitting diagrams $D_1, \dots, D_n$ respectively, there is a diagram $D$ of $L$ whose restrictions to $L_1, \dots, L_n$ are isotopic to $D_1, \dots, D_n$, respectively. In this paper we show that a similar

Khanh Dang, Daniel N. Blaschke, Saryu Fensin, Darby J. Luscher

To accurately predict the mechanical response of materials, especially at high strain rates, it is important to account for dislocation velocities in these regimes. Under these extreme conditions, it has been hypothesized that dislocations can move faster than the speed of sound. However, the presence of such dislocations remains elusive due to challenges as

Shruti Palaskar, Akshita Bhagia, Yonatan Bisk, Florian Metze

Combining the visual modality with pretrained language models has been surprisingly effective for simple descriptive tasks such as image captioning. More general text generation however remains elusive. We take a step back and ask: How do these models work for more complex generative tasks, i.e. conditioning on both text and images? Are multimodal models sim

Itay Harel, Hagai Taitelbaum, Idan Szpektor, Oren Kurland

We address the task of sentence retrieval for open-ended dialogues. The goal is to retrieve sentences from a document corpus that contain information useful for generating the next turn in a given dialogue. Prior work on dialogue-based retrieval focused on specific types of dialogues: either conversational QA or conversational search. To address a broader sc

Gaurab Aryal, Thayer Morrill, Peter Troyan

We study the problem of aggregating individual preferences over alternatives into a collective ranking. A distinctive feature of our setting is that agents are matched to alternatives. Applications include rankings of colleges or academic journals. The foundation of our approach is that alternatives agents desire -- that is, those they rank above their match

Jean-Sylvain Camier, Veselin Dobrev, Patrick Knupp, Tzanio Kolev

In this paper we present a new GPU-oriented mesh optimization method based on high-order finite elements. Our approach relies on node movement with fixed topology, through the Target-Matrix Optimization Paradigm (TMOP) and uses a global nonlinear solve over the whole computational mesh, i.e., all mesh nodes are moved together. A key property of the method is

SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. W. P. Amaral

CDMSlite Run 2 was a search for weakly interacting massive particles (WIMPs) with a cryogenic 600 g Ge detector operated in a high-voltage mode to optimize sensitivity to WIMPs of relatively low mass from 2 - 20 GeV/$c^2$. In this article, we present an effective field theory (EFT) analysis of the CDMSlite Run 2 data using an extended energy range and a comp

Pingsheng Li

Brain-Computer Interface (BCI) is a rapidly developing technology that allows direct communications between the human brain and external devices, such as robotic arms and computers. Bayesian Networks is a powerful tool in machine learning for tackling with problems that requires understanding and modelling the uncertainty and complexity within complex system

Hongqiang Song, Leping Li, Yao Chen

Coronal mass ejections (CMEs) are associated with the eruption of magnetic flux ropes (MFRs), which usually appear as hot channels in active regions and coronal cavities in quiet-Sun regions. CMEs often exhibit the classical three-part structure in the lower corona when imaged with white-light coronagraphs, including the bright front, dark cavity, and bright

S. Nojiri, S. D. Odintsov, V. K. Oikonomou

In this work, we shall provide an $F(R)$ gravity theoretical framework for solving the $H_0$-tension. Specifically, by exploiting the $F(R)$ gravity correspondence with a scalar-tensor theory, we shall provide a condition in which when it is satisfied, the $H_0$-tension is alleviated. The condition that remedies the $H_0$-tension restricts the corresponding

Hanyang Liu, Sunny S. Lou, Benjamin C. Warner, Derek R. Harford

Burnout is a significant public health concern affecting nearly half of the healthcare workforce. This paper presents the first end-to-end deep learning framework for predicting physician burnout based on electronic health record (EHR) activity logs, digital traces of physician work activities that are available in any EHR system. In contrast to prior approa

Daniel V. Cotton, Derek L. Buzasi, Conny Aerts, Jeremy Bailey

Here we report the detection of polarization variations due to nonradial modes in the beta Cephei star beta Crucis. In so doing we confirm 40-year-old predictions of pulsation-induced polarization variability and its utility in asteroseismology for mode identification. In an approach suited to other beta Cep stars, we combine polarimetry with space-based pho

Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu

Deep graph neural networks (GNNs) have been shown to be expressive for modeling graph-structured data. Nevertheless, the over-stacked architecture of deep graph models makes it difficult to deploy and rapidly test on mobile or embedded systems. To compress over-stacked GNNs, knowledge distillation via a teacher-student architecture turns out to be an effecti

Junda Sheng, Thomas Strohmer

The stochastic block model is a canonical random graph model for clustering and community detection on network-structured data. Decades of extensive study on the problem have established many profound results, among which the phase transition at the Kesten-Stigum threshold is particularly interesting both from a mathematical and an applied standpoint. It sta

Willam Bodeau, Kaisei Otoge, Wenchang Yeh, Nobuhiko P. Kobayashi

The use of laser with a Gaussian-beam profile is frequently adopted in attempts of crystallizing non-single-crystal thin films; however, it merely results in the formation of poly-crystal thin films. In this paper, selective area crystallization of non-single-crystal copper(II) oxide (CuO) is described. The crystallization is induced by laser, laser-induced

Anastasia Razdaibiedina, Alexander Brechalov

Protein function is inherently linked to its localization within the cell, and fluorescent microscopy data is an indispensable resource for learning representations of proteins. Despite major developments in molecular representation learning, extracting functional information from biological images remains a non-trivial computational task. Current state-of-t

Jiangyue Zhang, Yan Wu, Heping Zhang

A graph is $1$-$planar$ if it can be drawn in the plane so that each edge is crossed by at most one other edge. Moreover, a 1-planar graph $G$ is $optimal$ if it satisfies $|E(G)|=4|V(G)|-8$. J. Fujisawa et al. [16] first considered matching extension of optimal 1-planar graphs, obtained that each optimal 1-planar graph of even order is 1-extendable and char

Farnaz Fazelpour, Karen E. Daniels

Boundary shape, particularly roughness, strongly controls the amount of wall slip in dense granular flows. In this paper, we aim to quantify and understand which aspects of a dense granular flow are controlled by the boundary condition, and to incorporate these observations into a cooperative nonlocal model characterizing slow granular flows. To examine the

Eman Almuhur, Muhammad Ahsan Khan

In this paper, some features of countably $\alpha$-compact topological spaces are presented and proven. The connection between countably $\alpha$% -compact, Tychonoff, and $\alpha$-Hausdorff spaces is explained. The space is countably $\alpha$-compact space iff every locally finite family of non-empty subsets of such space is finite is demonstrated. The coun

Muhammad Al-Digeil, Yuri Grinberg, Daniele Melati3, Mohsen Kamandar Dezfouli

Autoencoders (AE) provide a useful method for nonlinear dimensionality reduction but are ill-suited for low data regimes. Conversely, Principal Component Analysis (PCA) is data-efficient but is limited to linear dimensionality reduction, posing a problem when data exhibits inherent nonlinearity. This presents a challenge in various scientific and engineering

Kamalika Chaudhuri, Kartik Ahuja, Martin Arjovsky, David Lopez-Paz

When facing data with imbalanced classes or groups, practitioners follow an intriguing strategy to achieve best results. They throw away examples until the classes or groups are balanced in size, and then perform empirical risk minimization on the reduced training set. This opposes common wisdom in learning theory, where the expected error is supposed to dec

Benito A. Juárez-Aubry, Bernard S. Kay, Tonatiuh Miramontes, Daniel Sudarsky

We explore how the initial value problem may be formulated for globally hyperbolic, Hadamard, solutions of the semiclassical Einstein-Klein-Gordon equations. Given a set of data on an initial 3-surface, consisting of the values on the surface of a spacetime metric and its first 3 time derivatives off the surface, we introduce a notion of 'surface Hadamard' s

David Baraglia

We construct a new family of knot concordance invariants $\theta^{(q)}(K)$, where $q$ is a prime number. Our invariants are obtained from the equivariant Seiberg-Witten-Floer cohomology, constructed by the author and Hekmati, applied to the degree $q$ cyclic cover of $S^3$ branched over $K$. In the case $q=2$, our invariant $\theta^{(2)}(K)$ shares many simi

Zhendong Chi, Guanxiong Qu, Yong-Chang Lau, Masashi Kawaguchi

The spin Hall effect of a Dirac Hamiltonian system is studied using semiclassical analyses and the Kubo formula. In this system, the spin Hall conductivity is dependent on the definition of spin current. All components of the spin Hall conductivity vanish when spin current is defined as the flow of spin angular momentum. In contrast, the off-diagonal compone

Benjamin A. Huerfano Z., Andres F Ardila, Pedro L Cifuentes

The current approach is carried out in order to have an overview of the level of inclusion and the participation of ICTs in social support and support for vulnerable populations suffering from chronic diseases. The inclusion was made through a bibliographic review, this being the basis for the collection of data and pertinent information. The argumentative s

Olli Tapiola, Xavier Tolsa

Inspired by recent work of Mourgoglou and the second named author, and earlier work of Hofmann, Mitrea and Taylor, we consider connections between the local John condition, the Harnack chain condition and weak boundary Poincar\'e inequalities in open sets $\Omega \subset \mathbb{R}^{n+1}$, with codimension $1$ Ahlfors--David regular boundaries. First, we pro

Takeshi Inagaki

In natural language processing (NLP), labeling on regions of text, such as words, sentences and paragraphs, is a basic task. In this paper, label is defined as map between mention of entity in a region on text and context of entity in a broader region on text containing the mention. This definition naturally introduces linkage of entities induced from inclus

Benjamin Andres Huerfano Zapata, Humberto Numpaque Lopez, Cindy Lorena Diaz Murillo

The following work shows an algorithm that can process images digitally with the goal of control the movement of a mobile robotic platform in a certain environment. The platform is identified with a specific color, and displacement environment of the platform shift has identified obstacles with different colors, for both cases it worked with the RGB color sc

Guido De Philippis, Antonio De Rosa

We prove the existence of nontrivial closed surfaces with constant anisotropic mean curvature with respect to elliptic integrands in closed smooth $3$-dimensional Riemannian manifolds. The constructed min-max surfaces are smooth with at most one singular point. The constant anisotropic mean curvature can be fixed to be any real number. In particular, we part

Shoki Koyanagi, Yoshitaka Tanimura

Using the quasi-equilibrium Helmholtz energy (qHE), defined as the thermodynamic work in a quasi-static process, we investigate the thermal properties of both an isothermal process and a transition process between the adiabatic and isothermal states (adiabatic transition). Here, the work is defined by the change in energy from a steady-state to another state

Zhenyu Li, Zehui Chen, Ang Li, Liangji Fang

Monocular 3D object detection (Mono3D) has achieved tremendous improvements with emerging large-scale autonomous driving datasets and the rapid development of deep learning techniques. However, caused by severe domain gaps (e.g., the field of view (FOV), pixel size, and object size among datasets), Mono3D detectors have difficulty in generalization, leading

Joel M. Bowman, Chen Qu Riccardo Conte, Apurba Nandi, Paul L. Houston

There has been great progress in developing methods for machine-learned potential energy surfaces. There have also been important assessments of these methods by comparing so-called learning curves on datasets of electronic energies and forces, notably the MD17 database. The dataset for each molecule in this database generally consists of tens of thousands o

Agnieszka Bier, Oleg Bogopolski

Let $G$ be a group acting acylindrically on a hyperbolic space and let $E$ be an exponential equation over $G$. We show that $E$ is equivalent to a finite disjunction of finite systems of pairwise independent equations which are either loxodromic over virtually cyclic subgroups or elliptic. We also obtain a description of the solution set of $E$. We obtain s

Polina Perstneva

It has been recently understood that the harmonic measure on the boundary $E = \partial \Omega$ of a domain $\Omega$ in $\mathbb{R}^n$ is absolutely continuous with respect to the Hausdorff measure $\mathcal{H}^{n - 1}$ on $E$ if and only if the boundary $E$ is rectifiable. Then, by G. David, M. Engelstein, J. Feneuil, S. Mayboroda and other coauthors, a not

Alberto Hernández Chillón, Meike Klettke, Diego Sevilla Ruiz, Jesús García Molina

Schema evolution is a crucial aspect in database management. The proposed taxonomies of schema changes have neglected the set of operations that involves relationships between entity types: aggregation and references, as well as the possible existence of structural variations for schema types, as most of NoSQL systems are schemaless. The distinction between

Raph Levien

Computation of bounding boxes is a fundamental problem in high performance rendering, as it is an input to visibility culling and binning operations. In a scene description structured as a tree, clip nodes and blend nodes entail intersection and union of bounding boxes, respectively. These are straightforward to compute on the CPU using a sequential algorith

Emily Allaway, Jena D. Hwang, Chandra Bhagavatula, Kathleen McKeown

Generics express generalizations about the world (e.g., birds can fly) that are not universally true (e.g., newborn birds and penguins cannot fly). Commonsense knowledge bases, used extensively in NLP, encode some generic knowledge but rarely enumerate such exceptions and knowing when a generic statement holds or does not hold true is crucial for developing

Akhil Mathew

The mod $p$ Riemann-Hilbert correspondence (in covariant and contravariant forms) relates $\mathbb{F}_p$-\'etale sheaves on the spectrum of an $\mathbb{F}_p$-algebra $R$ and Frobenius modules over $R$. We give an exposition of these correspondences using Breen's vanishing results on the perfect site.

Shikhar Tuli, Bhishma Dedhia, Shreshth Tuli, Niraj K. Jha

The existence of a plethora of language models makes the problem of selecting the best one for a custom task challenging. Most state-of-the-art methods leverage transformer-based models (e.g., BERT) or their variants. Training such models and exploring their hyperparameter space, however, is computationally expensive. Prior work proposes several neural archi

Francisco Segado-Boj, Juan-Jose Prieto-Gutiérrez, Juan Martín-Quevedo

The rise of open access (OA) publishing has been followed by the expansion of the Article Publishing Charges (APC) that moves the financial burden of scholarly journal publishing from readers to authors. We introduce the results of an international randomly selected sampled survey (N=3,422) that explores attitudes towards this pay-to-publish or Gold OA model

Mitsuru Tohyama

The damping of isoscalar giant quadrupole resonance in $^{16}$O is studied using extended random-phase-approximation approaches derived from the time-dependent density-matrix theory. It is pointed out that the effects of ground-state correlations bring strong fragmentation of quadrupole strength even if the number of two particle--two hole configurations is

Borbala Gerhat

We propose a method for the spectral analysis of unbounded operator matrices in a general setting which fully abstains from standard perturbative arguments. Rather than requiring the matrix to act in a Hilbert space $\mathcal{H}$, we extend its action to a suitable distributional triple $\mathcal{D} \subset \mathcal{H} \subset \mathcal{D}_-$ and restrict it

Ittai Abraham, Natacha Crooks, Neil Giridharan, Heidi Howard

Modern chained Byzantine Fault Tolerant (BFT) systems leverage a combination of pipelining and leader rotation to obtain both efficiency and fairness. These protocols, however, require a sequence of three or four consecutive honest leaders to commit operations. Therefore, even simple leader failures such as crashes can weaken liveness both theoretically and

Sara Lafia, Lizhou Fan, Libby Hemphill

Discovering authoritative links between publications and the datasets that they use can be a labor-intensive process. We introduce a natural language processing pipeline that retrieves and reviews publications for informal references to research datasets, which complements the work of data librarians. We first describe the components of the pipeline and then

Ronald S. Gamble

Relativistic jets from active galactic nuclei (AGN) have been of peak interest in the high-energy astrophysics community for their uniquely dynamic nature and incredible radiative power; emanating from supermassive black holes and similarly accreting compact dense objects. An overall consensus on relativistic jet formation states that accelerated outflow at

Duy H. N. Nguyen, Italo Atzeni, Antti Tölli, A. Lee Swindlehurst

Optimal data detection in massive multiple-input multiple-output (MIMO) systems requires prohibitive computational complexity. A variety of detection algorithms have been proposed in the literature, offering different trade-offs between complexity and detection performance. In this paper, we build upon variational Bayes (VB) inference to design low-complexit

Sikun Lin, Shuyun Tang, Scott Grafton, Ambuj Singh

Finding an appropriate representation of dynamic activities in the brain is crucial for many downstream applications. Due to its highly dynamic nature, temporally averaged fMRI (functional magnetic resonance imaging) can only provide a narrow view of underlying brain activities. Previous works lack the ability to learn and interpret the latent dynamics in br

Zhongmin Zhang, Vincent Du, Zhiyue Lu

Under temperature oscillation, cyclic molecular machines such as catalysts and enzymes could harness energy from the oscillatory bath and use it to drive other processes. Using a novel geometrical approach, under fast temperature oscillation, we derive a general design principle for obtaining the optimal catalytic energy landscape that can harness energy fro

Po-Hao Chang, Zachary Buschmann, Rajendra R. Zope

We review two common numerical schemes for Coulomb potential evaluation that differ only in their radial part of the solutions in the spherical harmonic expansion (SHE). One is based on finite-difference method (FDM) while the other is based on the Green's function (GF) solution to the radial part of the Poisson equation. We analyze the methods and observe t

M. Symeonidis, N. Maddox, M. J. Jarvis, M. J. Michalowski

We examine the far-IR properties of a sample of 5391 optically selected QSOs in the 0.5<z<2.65 redshift range down to log[nuLnu,2500 (erg/s)]>44.7, using SPIRE data from Herschel-ATLAS. We split the sample in a grid of 74 luminosity-redshift bins and compute the average optical-infrared spectral energy distribution (SED) in each bin. By normalising an intrin

Sara Capecchi, Cristina Gena, Ilaria Lombardi

Our Computer science k-12 education research group and the educational toy company Quercetti have been collaborating together to design and manufacture toys that help stimulate and consolidate so-called computational thinking. This approach is inspired by methods already consolidated in the literature and widespread worldwide such as the Bebras tasks and CS-

Wallace Moreira Bessa

The dead-zone is one of the most common hard nonlinearities in industrial actuators and its presence may drastically compromise control systems stability and performance. In this work, an adaptive variable structure controller is proposed to deal with a class of uncertain nonlinear systems subject to a non-symmetric dead-zone input. The adopted approach is p

Xaver Kriechbaum

We consider a branching random walk in time-inhomogeneous random environment, in which all particles at generation $k$ branch into the same random number of particles $\mathcal{L}_{k+1}\ge 2$, where the $\mathcal{L}_k$, $k\in\mathbb{N}$, are i.i.d., and the increments are standard normal. Let $\mathbb{P}$ denote the law of $(\mathcal{L}_k)_{k\in\mathbb{N}}$,

Virginia Agostiniani, Carlo Mantegazza, Lorenzo Mazzieri, Francesca Oronzio

We provide a new proof of the Riemannian Penrose inequality for time-symmetric asymptotically flat initial data with a single black-hole horizon. The proof proceeds through a newly established monotonicity formula holding along the level sets of the $p$-capacitary potential of the horizon boundary, in any asymptotically flat $3$-manifold with nonnegative sca

Laurent Pagnier, Robert Ferrando, Yury Dvorkin, Michael Chertkov

This paper seeks to design a machine learning twin of the optimal power flow (OPF) optimization, which is used in market-clearing procedures by wholesale electricity markets. The motivation for the proposed approach stems from the need to obtain the digital twin, which is much faster than the original, while also being sufficiently accurate and producing con

Mingtian Zhang, Peter Hayes, David Barber

The ability of likelihood-based probabilistic models to generalize to unseen data is central to many machine learning applications such as lossless compression. In this work, we study the generalization of a popular class of probabilistic model - the Variational Auto-Encoder (VAE). We discuss the two generalization gaps that affect VAEs and show that overfit

James Wheeler

We investigate the occurrence of naked singularities, local and global, in the incoming Vaidya spacetimes with zero initial mass. While it is well-known that these spacetimes admit locally and globally naked singularities, we demonstrate that globally naked singularities are significantly more common than is stressed in the literature, being generic in a nat

Josiane Maria Macedo Fernandes, Marcelo Costa Tanaka, Raimundo Carlos Silvério Freire Júnior, Wallace Moreira Bessa

Due to the enormous technological improvements obtained in the last decades it is possible to use robotic vehicles for underwater exploration. This work describes the development of a dynamic positioning system for remotely operated underwater vehicles based. The adopted approach is developed using Lyapunov Stability Theory and enhanced by a neural network b

Ahmed Abbas, Paul Swoboda

We present a fast, scalable, data-driven approach for solving relaxations of 0-1 integer linear programs. We use a combination of graph neural networks (GNN) and the Lagrange decomposition based algorithm FastDOG (Abbas and Swoboda 2022b). We make the latter differentiable for end-to-end training and use GNNs to predict its algorithmic parameters. This allow

Aron Ambrus, Monika Csikos, Gergely Kiss, Janos Pach

Given a triangle $\Delta$, we study the problem of determining the smallest enclosing and largest embedded isosceles triangles of $\Delta$ with respect to area and perimeter. This problem was initially posed by Nandakumar and was first studied by Kiss, Pach, and Somlai, who showed that if $\Delta'$ is the smallest area isosceles triangle containing $\Delta$,

Jean-Christophe Pain

We propose a simple derivation of an upper bound for the perimeter of an ellipse. The procedure, which relies on the use of elliptic integrals, consists in introducing, via inequalities and convexity properties, specific integrals which can be calculated analytically.

Bohdan M. Pavlyshenko

The paper describes the deep learning approach for forecasting non-stationary time series with using time trend correction in a neural network model. Along with the layers for predicting sales values, the neural network model includes a subnetwork block for the prediction weight for a time trend term which is added to a predicted sales value. The time trend

Mike D. Schneider

Recent work on the status of astrophysical modeling in the wake of quantum gravity indicates that a 'fauxrizon' (portmanteau of 'faux horizon'), such as is relevant to understanding astrophysical black holes according to the fuzzball proposal within string theory, might ultimately solve the familiar black hole evaporation paradox. I clarify, with general ups

Seungwook Kim, Juhong Min, Minsu Cho

Establishing correspondences between images remains a challenging task, especially under large appearance changes due to different viewpoints or intra-class variations. In this work, we introduce a strong semantic image matching learner, dubbed TransforMatcher, which builds on the success of transformer networks in vision domains. Unlike existing convolution

Bojan Mohar

The game of Cops and Robber is traditionally played on a finite graph. The purpose of this paper is to introduce and analyse the game that is played on an arbitrary geodesic space (a compact, path-connected space endowed with intrinsic metric). It is shown that the game played on metric graphs is essentially the same as the discrete game played on abstract g

Alexander M. Petersen

We develop a systematic approach to measuring combinatorial innovation in the biomedical sciences based upon the comprehensive ontology of Medical Subject Headings (MeSH). This approach leverages an expert-defined knowledge ontology that features both breadth (27,875 MeSH analyzed across 25 million articles indexed by PubMed from 1902 onwards) and depth (we

Javier Ferrando, Gerard I. Gállego, Belen Alastruey, Carlos Escolano

In Neural Machine Translation (NMT), each token prediction is conditioned on the source sentence and the target prefix (what has been previously translated at a decoding step). However, previous work on interpretability in NMT has mainly focused solely on source sentence tokens' attributions. Therefore, we lack a full understanding of the influences of every

József Balogh, Robert A. Krueger

The Boolean lattice $\mathcal{P}(n)$ consists of all subsets of $[n] = \{1,\dots, n\}$ partially ordered under the containment relation. Sperner's Theorem states that the largest antichain of the Boolean lattice is given by a middle layer: the collection of all sets of size $\lfloor{n/2}\rfloor$, or also, if $n$ is odd, the collection of all sets of size $\l

A. Martínez-Merino, M. Sabido

Non-additive entropies have been proposed as alternatives to understanding the thermodynamics of Black Holes. Moreover, it has been suggested that the difficulties of quantization of gravity are an indication that gravity is an emergent phenomenon, and therefore an entropic formulation is warranted. In this work, we explore cosmologies that come from non-add

M. S. Soares, G. Menezes, N. F. Svaiter

We propose a new form for the quantum master equation in the theory of open quantum systems. This new formalism allows one to describe the dynamics of two-level systems moving along different hyperbolic trajectories with distinct proper times. In the Born-Markov approximation, we consider a quantum massless scalar field coupled with two-level systems. Starti

Eric V. Strobl, Thomas A. Lasko

Complex diseases are caused by a multitude of factors that may differ between patients. As a result, hypothesis tests comparing all patients to all healthy controls can detect many significant variables with inconsequential effect sizes. A few highly predictive root causes may nevertheless generate disease within each patient. In this paper, we define patien

Mike D. Schneider

I provide some philosophical groundwork for the recently proposed 'trans-Planckian censorship' conjecture in theoretical physics. In particular, I argue that structure formation in early universe cosmology is, at least as we typically understand it, autonomous with regards to quantum gravity, the high energy physics that governs the Planck regime in our univ

Tadeusz Kosztołowicz, Aldona Dutkiewicz

A $g$--subdiffusion equation with fractional Caputo time derivative with respect to another function $g$ is used to describe a process of a continuous transition from subdiffusion with parameters $\alpha$ and $D_\alpha$ to subdiffusion with parameters $\beta$ and $D_\beta$. The parameters are defined by the time evolution of the mean square displacement of d

Rishi Veerapaneni, Tushar Kusnur, Maxim Likhachev

Conflict-Based Search (CBS) is a popular multi-agent path finding (MAPF) solver that employs a low-level single agent planner and a high-level constraint tree to resolve conflicts. The vast majority of modern MAPF solvers focus on improving CBS by reducing the size of this tree through various strategies with few methods modifying the low level planner. Typi

Zoltan Sztranyovszky, Wolfgang Langbein, Egor A. Muljarov

We present an exact first-order perturbation theory for the eigenmodes in systems with interfaces causing material discontinuities. We show that when interfaces deform, higher-order terms of the perturbation series can contribute to the eigenmode frequencies in first order in the deformation depth. This means that the usual diagonal approximation is not nece

Zili Wang

It is known that the flip distance between two triangulations of a convex polygon is related to the minimum number of tetrahedra in the triangulation of some polyhedron. It is interesting to know whether these two numbers are the same. In this work, we find examples to show that the two numbers are different in nature, and their ratio can be arbitrarily clos

Adhitha Dias, Kirshanthan Sundararajah, Charitha Saumya, Milind Kulkarni

Sparse tensor algebra computations have become important in many real-world applications like machine learning, scientific simulations, and data mining. Hence, automated code generation and performance optimizations for tensor algebra kernels are paramount. Recent advancements such as the Tensor Algebra Compiler (TACO) greatly generalize and automate the cod

Josiane Maria de Macedo Fernandes, Marcelo Costa Tanaka, Wallace Moreira Bessa

Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due

Joe Miller, Nathan Warnberg

A $k$-term arithmetic progression ($k$-AP) in a graph $G$ is a list of vertices such that each consecutive pair of vertices is the same distance apart. If $c$ is a coloring function of the vertices of $G$ and a $k$-AP in $G$ has each vertex colored distinctly, then that $k$-AP is a rainbow $k$-AP. The anti-van der Waerden number of a graph $G$ with respect t

Mike D. Schneider

I critically discuss a controversial 'trans-Planckian censorship' conjecture, which has recently been introduced to researchers working at the intersection of fundamental physics and cosmology. My focus explicitly avoids any appeals to contingent research within string theory (the sociological origins of the conjecture) or regarding the more general (quantum

Fabio Berra, Gladis Pradolini, Wilfredo Ramos

Given an $m$-tuple of weights $\vec{v}=(v_1,\dots,v_m)$, we characterize the classes of pairs $(w,\vec{v})$ involved with the boundedness properties of the multilinear fractional integral operator from $\prod_{i=1}^mL^{p_i}\left(v_i^{p_i}\right)$ into suitable Lipschitz spaces associated to a parameter $\delta$, $\mathcal{L}_w(\delta)$. Our results generaliz

Alberto Caballero

This paper attempts to provide an estimation of the prevalence of hostile extraterrestrial civilizations through an extrapolation of the probability that we, as the human civilization, would attack or invade an inhabited exoplanet once we become a Type-1 civilization in the Kardashev Scale capable of nearby interstellar travel. The estimation is based on the

Asmita Roy, Jun Chen, Xianyang Zhang

Genomic data are subject to various sources of confounding, such as demographic variables, biological heterogeneity, and batch effects. To identify genomic features associated with a variable of interest in the presence of confounders, the traditional approach involves fitting a confounder-adjusted regression model to each genomic feature, followed by multip

Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski

Word translation without parallel corpora has become feasible, rivaling the performance of supervised methods. Recent findings have shown that the accuracy and robustness of unsupervised word translation (UWT) can be improved by making use of visual observations, which are universal representations across languages. In this work, we investigate the potential

A. R. Moura

We applied the Self-Consistent Harmonic Approximation (SCHA), combined with coherent states formalism, to study the ferromagnetic resonance (FMR) in a ferromagentic/normal metal junction. Due to the interface interaction, the FMR-generated spin current is injected from the magnetic insulator to the normal metal, the so-called spin pumping. Ordinarily, ferrom

Oluwashina K. Adegoke

Probing the physics of the accretion flow around active galactic nuclei (AGN) is crucial to understanding their emission mechanisms as well as being able to constrain the geometrical and variability properties of the different regions around them. The soft X-ray excess -- usually observed below $\sim2\,\mathrm{keV}$ in excess of the dominant X-ray powerlaw c

Harsh Shrivastava, Urszula Chajewska, Robin Abraham, Xinshi Chen

Probabilistic Graphical Models (PGMs) are generative models of complex systems. They rely on conditional independence assumptions between variables to learn sparse representations which can be visualized in a form of a graph. Such models are used for domain exploration and structure discovery in poorly understood domains. This work introduces a novel techniq

Roberta Varela de Albuquerque Herôncio, João Deodato Batista dos Santos, Wallace Moreira Bessa, Aline Souza de Paula

Smart structures are usually designed with a stimulus-response mechanism to mimic the autoregulatory process of living systems. In this work, in order to simulate this natural and self-adjustable behavior, a fuzzy feedback linearization scheme is applied to a shape memory two-bar truss. This structural system exhibits both constitutive and geometrical nonlin

Milica Lučić, Enrico Pasqualetto, Ivana Vojnović

In this paper we investigate some reflexivity-type properties of separable measurable Banach bundles over a $\sigma$-finite measure space. Our two main results are the following: - The fibers of a bundle are uniformly convex (with a common modulus of convexity) if and only if the space of its $L^p$-sections is uniformly convex for every $p\in(1,\infty)$. - T

Tianjie Wang, Jie Chen, Joel Vaughan, Vijayan N. Nair

Regression problems with time-series predictors are common in banking and many other areas of application. In this paper, we use multi-head attention networks to develop interpretable features and use them to achieve good predictive performance. The customized attention layer explicitly uses multiplicative interactions and builds feature-engineering heads th

Pengyu Gao, Zilong Liu, Pei Xiao, Chuan Heng Foh

Grant-free non-orthogonal multiple access (NOMA) scheme is considered as a promising candidate for the enabling of massive connectivity and reduced signalling overhead for Internet of Things (IoT) applications in massive machine-type communication (mMTC) networks. Exploiting the inherent nature of sporadic transmissions in the grant-free NOMA systems, compre

Tobias Schlagenhauf, Yiwen Lin, Benjamin Noack

Ensembles of Convolutional neural networks have shown remarkable results in learning discriminative semantic features for image classification tasks. Though, the models in the ensemble often concentrate on similar regions in images. This work proposes a novel method that forces a set of base models to learn different features for a classification task. These

Afra Feyza Akyürek, Sejin Paik, Muhammed Yusuf Kocyigit, Seda Akbiyik

Large language models trained on a mixture of NLP tasks that are converted into a text-to-text format using prompts, can generalize into novel forms of language and handle novel tasks. A large body of work within prompt engineering attempts to understand the effects of input forms and prompts in achieving superior performance. We consider an alternative meas

Kazuki Morita, Yu Kumagai, Fumiyasu Oba, Aron Walsh

Ferroelectricity in crystals is associated with the displacement of ions or rotations of polar units. Here we consider the dipole created by donor doping ($D^+$) and the corresponding bound polaron ($e^-$).A dipole of 6.15 Debye is predicted, from Berry phase analysis, in the Ruddlesden-Popper phase of ${\rm Sr_3Ti_2O_7}$. A characteristic double-well potent