May 2022 arXiv papers — page 72

Satvik Garg, Dwaipayan Roy

In recent years, Knowledge Graph (KG) development has attracted significant researches considering the applications in web search, relation prediction, natural language processing, information retrieval, question answering to name a few. However, often KGs are incomplete due to which Knowledge Graph Completion (KGC) has emerged as a sub-domain of research to

J. L. Vergely, R. Lallement, N. L. J. Cox

3D maps of the extinction density in the Galaxy can be built through the inversion of catalogues of distance-extinction pairs for individual target stars. The spatial resolution of the maps that can be achieved increases with the spatial density of the targets, and subsequently with the combination of catalogues. However, this requires their careful inter-ca

Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li

Pluralistic image completion focuses on generating both visually realistic and diverse results for image completion. Prior methods enjoy the empirical successes of this task. However, their used constraints for pluralistic image completion are argued to be not well interpretable and unsatisfactory from two aspects. First, the constraints for visual reality c

Dmitry Beliaev, Michael McAuley, Stephen Muirhead

For a smooth stationary Gaussian field on $\mathbb{R}^d$ and level $\ell \in \mathbb{R}$, we consider the number of connected components of the excursion set $\{f \ge \ell\}$ (or level set $\{f = \ell\}$) contained in large domains. The mean of this quantity is known to scale like the volume of the domain under general assumptions on the field. We prove that

Shah Zeb, Aamir Mahmood, Sunder Ali Khowaja, Kapal Dev

Industry 5.0 vision, a step toward the next industrial revolution and enhancement to Industry 4.0, envisioned the new goals of resilient, sustainable, and human-centric approaches in diverse emerging applications, e.g., factories-of-the-future, digital society. The vision seeks to leverage human intelligence and creativity in nexus with intelligent, efficien

Carla Teixeira Lopes

This report provides an overview of the field of Information Retrieval (IR) in healthcare. It does not aim to introduce general concepts and theories of IR but to present and describe specific aspects of Health Information Retrieval (HIR). After a brief introduction to the more broader field of IR, the significance of HIR at current times is discussed. Speci

Daniel Larraz, Cesare Tinelli

We present a new feature of the open-source model checker Kind 2 which checks whether a component contract is realizable; i.e., it is possible to construct a component such that for any input allowed by the contract assumptions, there is some output value that the component can produce that satisfies the contract guarantees. When the contract is proven unrea

Victoria Knutson, Serge Aleshin-Guendel, Ariel Karlinsky, William Msemburi

Estimating the true mortality burden of COVID-19 for every country in the world is a difficult, but crucial, public health endeavor. Attributing deaths, direct or indirect, to COVID-19 is problematic. A more attainable target is the "excess deaths", the number of deaths in a particular period, relative to that expected during "normal times", and we estimate

Jeffrey Covington, Nan Chen, Monica M. Wilhelmus

Modeling and understanding sea ice dynamics in marginal ice zones relies on acquiring Lagrangian ice floe measurements. However, optical satellite images are susceptible to atmospheric noise, leading to gaps in the retrieved time series of floe positions. This paper presents an efficient and statistically accurate nonlinear dynamical interpolation framework

Alexander Lobashev, Mikhail V. Tamm

We introduce a new approach to reconstruction of the thermodynamic functions and phase boundaries in two-parametric statistical mechanics systems. Our method is based on expressing the Fisher metric in terms of the posterior distributions over a space of external parameters and approximating the metric field by a Hessian of a convex function. We use the prop

Rui Tang, Shuyu Jiang, Xingshu Chen, Wenxian Wang

Interlayer link prediction aims at matching the same entities across different layers of the multiplex network. Existing studies attempt to predict more accurately, efficiently, or generically from the aspects of network structure, attribute characteristics, and their combination. Few of them analyze the effects of intralayer links. Namely, few works study t

Chris Gorman, Davide Punzo, Igor Octaviano, Steve Pieper

The exchange of large and complex slide microscopy imaging data in biomedical research and pathology practice is impeded by a lack of data standardization and interoperability, which is detrimental to the reproducibility of scientific findings and clinical integration of technological innovations. Slim is an open-source, web-based slide microscopy viewer tha

Omar Besbes, Yash Kanoria, Akshit Kumar

Dynamic resource allocation problems are ubiquitous, arising in inventory management, order fulfillment, online advertising, and other applications. We initially focus on one of the simplest models of online resource allocation: the multisecretary problem. In the multisecretary problem, a decision maker sequentially hires up to $B$ out of $T$ candidates, and

Irena Rusu

Stick graphs are defined as follows. Let A (respectively B) be a set of vertical (respectively horizontal) segments in the plane such that the bottom endpoints of the segments in A and the left endpoints of the segments in B lie on the same ground straight line with slope -1. The Stick graph defined by A and B, which is necessarily bipartite, is the intersec

Nora Molkenthin, J. J. Güven, Steffen Mühle, Antonia S. J. S. Mey

The mechanisms by which a protein's 3D structure can be determined based on its amino acid sequence have long been one of the key mysteries of biophysics. Often simplistic models, such as those derived from geometric constraints, capture bulk real-world 3D protein-protein properties well. One approach is using protein contact maps to better understand protei

Zhuyun Dai, Arun Tejasvi Chaganty, Vincent Zhao, Aida Amini

Many important questions (e.g. "How to eat healthier?") require conversation to establish context and explore in depth. However, conversational question answering (ConvQA) systems have long been stymied by scarce training data that is expensive to collect. To address this problem, we propose a new technique for synthetically generating diverse and high-quali

Itay Safran, Gal Vardi, Jason D. Lee

We study the dynamics and implicit bias of gradient flow (GF) on univariate ReLU neural networks with a single hidden layer in a binary classification setting. We show that when the labels are determined by the sign of a target network with $r$ neurons, with high probability over the initialization of the network and the sampling of the dataset, GF converges

Eduard George Stan, Dan Andrei Ciubotaru, Michele Renda, Călin Alexa

We review the dimensional check problem of the high-level programming languages, discuss the existing solutions, and come up with a new solution suited for scientific and engineering computations. Then, we introduce Univec, our C++ library designed to make scalar, vector, and matrix operations using units of measurement. Moreover, Univec supports dimensional

Marcus M. Noack, Harinarayan Krishnan, Mark D. Risser, Kristofer G. Reyes

A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. This success is largely attributed to the GP's analytical tractability, robustness, non-parametric structure, and natural inclusion of uncertainty quantification. Unfortunately, the use of exact GPs is prohibitively exp

M. Khademi, S. Nasiri, F. S. Tabatabaei

Magnetic fields can play an important role in the energy balance and formation of gas structures in galaxies. However, their dynamical effect on the rotation curve of galaxies is immensely unexplored. We investigate the dynamical effect of the known magnetic arms of $NGC\;6946$ on its circular gas rotation traced in HI, considering two dark matter mass densi

Kennard Ng, Ser-Nam Lim, Gim Hee Lee

Content-based Video Retrieval (CBVR) is used on media-sharing platforms for applications such as video recommendation and filtering. To manage databases that scale to billions of videos, video-level approaches that use fixed-size embeddings are preferred due to their efficiency. In this paper, we introduce Video Region Attention Graph Networks (VRAG) that im

Reid Pryzant, Ziyi Yang, Yichong Xu, Chenguang Zhu

Semi-supervised learning has shown promise in allowing NLP models to generalize from small amounts of labeled data. Meanwhile, pretrained transformer models act as black-box correlation engines that are difficult to explain and sometimes behave unreliably. In this paper, we propose tackling both of these challenges via Automatic Rule Induction (ARI), a simpl

Mario Kendziorski, Leonard Göke, Christian von Hirschhausen, Claudia Kemfert

In this paper, we explore centralized and more decentral approaches to succeed the energiewende in Germany, in the European context. We use the AnyMOD framework to model a future renewable-based European energy system, based on a techno-economic optimization, i.e. cost minimization with given demand, including both investment and the subsequent dispatch of c

Neetik Mukherjee, Chandra Nath Patra, Amlan K. Roy

The behavior of H-like ions embedded in astrophysical plasmas in the form of \emph{dense, strongly and weakly coupled} plasmas are investigated. In these, the increase and decrease in temperature is impacted with a change in confinement radius $(r_{c})$. Two independent and generalized scaling ideas have been applied to modulate the effect of plasma screenin

Morteza Hasanvand

In 2006 Bar{\'a}t and Thomassen conjectured that every planar $4$-edge-connected $4$-regular simple graph of size divisible by three admits a claw-decomposition. Later, Lai (2007) disproved this conjecture by a family of planar graphs with edge-connectivity $4$ which the smallest one contains $24$ vertices. In this note, we first give a smaller counterexampl

Anna Puecher, Chinmay Kalaghatgi, Soumen Roy, Yoshinta Setyawati

Recently, strong evidence was found for the presence of higher-order modes in the gravitational wave signals GW190412 and GW190814, which originated from compact binary coalescences with significantly asymmetric component masses. This has opened up the possibility of new tests of general relativity by looking at the way in which the higher-order modes are re

Juho Timonen, Nikolas Siccha, Ben Bales, Harri Lähdesmäki

Statistical models can involve implicitly defined quantities, such as solutions to nonlinear ordinary differential equations (ODEs), that unavoidably need to be numerically approximated in order to evaluate the model. The approximation error inherently biases statistical inference results, but the amount of this bias is generally unknown and often ignored in

Guangzhi Sun, Chao Zhang, Philip C Woodland

Contextual knowledge is essential for reducing speech recognition errors on high-valued long-tail words. This paper proposes a novel tree-constrained pointer generator (TCPGen) component that enables end-to-end ASR models to bias towards a list of long-tail words obtained using external contextual information. With only a small overhead in memory use and com

Debojyoti Biswas, Parijat Banerjee, Pablo A. Iglesias

Cells rely on the ability to sense and respond to small spatial differences in chemoattractant concentrations for survival. There is growing evidence that this is accomplished by setting the signaling system near the threshold for activation in an excitable system and using the spatial heterogeneities to alter the threshold thereby biasing cell activity in t

Ian A. Kash, Lev Reyzin, Zishun Yu

Reinforcement learning generalizes multi-armed bandit problems with additional difficulties of a longer planning horizon and unknown transition kernel. We explore a black-box reduction from discounted infinite-horizon tabular reinforcement learning to multi-armed bandits, where, specifically, an independent bandit learner is placed in each state. We show tha

Bengisu Cagiltay, Joseph Michaelis, Sarah Sebo, Bilge Mutlu

Research in child-robot interactions suggests that engaging in "care-taking" of a social robot, such as tucking the robot in at night, can strengthen relationships formed between children and robots. In this work, we aim to better understand and explore the design space of caretaking activities with 10 children, aged 8--12 from eight families, involving an e

João Morais, Arash Behboodi, Hamed Pezeshki, Ahmed Alkhateeb

Millimeter-wave (mmWave) communication systems rely on narrow beams for achieving sufficient receive signal power. Adjusting these beams is typically associated with large training overhead, which becomes particularly critical for highly-mobile applications. Intuitively, since optimal beam selection can benefit from the knowledge of the positions of communic

Maxim Kharitonov

We present the {\em (symmetry-incorporating) formalism of general continuum models with boundary conditions} and apply it to the model with the minimal number of degrees of freedom necessary to have a well-defined boundary: a model with a two-component wave function and a linear-in-momentum Hamiltonian. We derive the most general forms (class A) of both the

Bengisu Cagiltay, Nathan White, Rabia Ibtasar, Bilge Mutlu

Social robots are emerging as learning companions for children, and research shows that they facilitate the development of interest and learning even through brief interactions. However, little is known about how such technologies might support these goals in authentic environments over long-term periods of use and interaction. We designed a learning compani

Zoltán M. Balogh, Sebastiano Don, Alexandru Kristály

We prove Gagliardo-Nirenberg inequalities with three weights -- verifying a joint concavity condition -- on open convex cones of $\mathbb R^n$. If the weights are equal to each other the inequalities become sharp and we compute explicitly the sharp constants. For a certain range of parameters we can characterize the class of extremal functions; in this case,

Denis Dobkowski-Ryłko, Jerzy Lewandowski

We study gravitational radiation produced by time changing matter source in de Sitter spacetime. We consider a cosmological Killing horizon instead of the conformal boundary used in the radiation theory in the Minkowski spacetime. The energy of the radiation passing through the horizon is derived. Our result takes the form of a generalized quadruple formula

Jason Cantarella, Tetsuo Deguchi, Clayton Shonkwiler, Erica Uehara

In this paper, we study random embeddings of polymer networks distributed according to any potential energy which can be expressed in terms of distances between pairs of monomers. This includes freely jointed chains, steric effects, Lennard-Jones potentials, bending energies, and other physically realistic models. A configuration of $n$ monomers in $\mathbb{

Hao Quan, Xingyu Li, Weixing Chen, Qun Bai

Based on digital pathology slice scanning technology, artificial intelligence algorithms represented by deep learning have achieved remarkable results in the field of computational pathology. Compared to other medical images, pathology images are more difficult to annotate, and thus, there is an extreme lack of available datasets for conducting supervised le

Nicoletta Gnan, Claudio Maggi

It is still a debated issue whether all critical active particles belong to the same universality class. Here we numerically study the critical behavior of quorum sensing active particles that represents the archetypal model for interpreting motility-induced phase separation. Mean-field theory predicts that this model should undergo a full phase separation i

Georgina Dransfield, Amaury H. M. J. Triaud, Tristan Guillot, Djamel Mekarnia

We report on the discovery and characterisation of three planets orbiting the F8 star HD~28109, which sits comfortably in \tess's continuous viewing zone. The two outer planets have periods of $\rm 56.0067 \pm 0.0003~days$ and $\rm 84.2597_{-0.0008}^{+0.0010}~days$, which implies a period ratio very close to that of the first-order 3:2 mean motion resonance,

Abhisek Ghosal, Amlan K. Roy

In this communication, we represent a self-consistent systematic optimization procedure for the development of optimally tuned (OT) range-separated hybrid (RSH) functionals from \emph{first principles}. This is an offshoot of our recent work, which employed a purely numerical approach for efficient computation of exact exchange contribution in the convention

Laurent W. Marcoux, Heydar Radjavi, Yuanhang Zhang

We describe the norm-closures of the set $\mathfrak{C}_{\mathfrak{E}}$ of commutators of idempotent operators and the set $\mathfrak{E} - \mathfrak{E}$ of differences of idempotent operators acting on a finite-dimensional complex Hilbert space, as well as characterising the intersection of the closures of these sets with the set $\mathcal{K}(\mathcal{H})$ of

Leon Liu, Walaa M. Moursi, Jon Vanderwerff

The correspondence between the class of nonexpansive mappings and the class of maximally monotone operators via the reflected resolvents of the latter has played an instrumental role in the convergence analysis of the splitting methods. Indeed, the performance of some of these methods, e.g., Douglas-Rachford and Peaceman-Rachford methods hinges on iterating

Unpil Baek, Diptarka Hait, James Shee, Oskar Leimkuhler

A balanced description of both static and dynamic correlations in electronic systems with nearly degenerate low-lying states presents a challenge for multi-configurational methods on classical computers. We present here a quantum algorithm utilizing the action of correlating cluster operators to provide high-quality wavefunction ans\"atze employing a non-ort

Morteza Hasanvand

In 1976 Frank and Gy{\'a}rf{\'a}s gave a necessary and sufficient condition for the existence of an orientation in an arbitrary graph $G$ such that for each vertex $v$, the out-degree $d^+_G(v)$ of it satisfies $p(v)\le d^+_G(v)\le q(v)$, where $p$ and $q$ are two integer-valued functions on $V(G)$ with $p\le q$. In this paper, we give a sufficient edge-conn

Harshitha Machiraju, Oh-Hyeon Choung, Michael H. Herzog, Pascal Frossard

Deep convolutional neural networks (DCNNs) have revolutionized computer vision and are often advocated as good models of the human visual system. However, there are currently many shortcomings of DCNNs, which preclude them as a model of human vision. There are continuous attempts to use features of the human visual system to improve the robustness of neural

Aso M. Aladdin, Jaza M. Abdullah, Kazhan Othman Mohammed Salih, Tarik A. Rashid

This discusses a case study on Fitness Dependent Optimizer or so-called FDO and adapting its parameters to the Internet of Things (IoT) healthcare. The reproductive way is sparked by the bee swarm and the collaborative decision-making of FDO. As opposed to the honey bee or artificial bee colony algorithms, this algorithm has no connection to them. In FDO, th

Shikun Zhang, Yan Shvartzshnaider, Yuanyuan Feng, Helen Nissenbaum

We present an empirical study exploring how privacy influences the acceptance of vaccination certificate (VC) deployments across different realistic usage scenarios. The study employed the privacy framework of Contextual Integrity, which has been shown to be particularly effective in capturing people's privacy expectations across different contexts. We use a

Matteo Cavaleri, Daniele D'Angeli, Alfredo Donno, Emanuele Rodaro

This paper deals with graph automaton groups associated with trees and some generalizations. We start by showing some algebraic properties of tree automaton groups. Then we characterize the associated semigroup, proving that it is isomorphic to the partially commutative monoid associated with the complement of the line graph of the defining tree. After that,

Bikash Chakraborty

Geometrically, $\int_{a}^{b}\frac{1}{x}dx$ means the area under the curve $\frac{1}{x}$ from $a$ to $b$, where $0<a<b$, and this area gives a positive number. Using this area argument, in this expository note, we present some visual representations of some classical results. For examples, we demonstrate an area argument on a generalization of Euler's limit $

Laura Stegner, Bilge Mutlu

Robots hold significant promise to assist with providing care to an aging population and to help overcome increasing caregiver demands. Although a large body of research has explored robotic assistance for individuals with disabilities and age-related challenges, this past work focuses primarily on building robotic capabilities for assistance and has not yet

Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt

Continual learning - learning new tasks in sequence while maintaining performance on old tasks - remains particularly challenging for artificial neural networks. Surprisingly, the amount of forgetting does not increase with the dissimilarity between the learned tasks, but appears to be worst in an intermediate similarity regime. In this paper we theoreticall

Laya Parkavousi, Hamed Kameli, Shant Baghram

Structures in the Universe are arranged into the cosmic web. Distributions, statistics, and evolutions of the structures can be used as probes for cosmological models. We investigate the number density of voids and dark matter halos-in-voids in the Excursion Set Theory (EST). We study the Markov and non-Markov frameworks of EST in both spherical and ellipsoi

James Hefford, Cole Comfort

We compare two possible ways of defining a category of 1-combs, the first intensionally as coend optics and the second extensionally as a quotient by the operational behaviour of 1-combs on lower-order maps. We show that there is a full and bijective on objects functor quotienting the intensional definition to the extensional one and give some sufficient con

Simone Soderi, Alessandro Brighente, Federico Turrin, Mauro Conti

Visible Light Communication (VLC) is one the most promising enabling technology for future 6G networks to overcome Radio-Frequency (RF)-based communication limitations thanks to a broader bandwidth, higher data rate, and greater efficiency. However, from the security perspective, VLCs suffer from all known wireless communication security threats (e.g., eaves

Christos Pylianidis, Ioannis N. Athanasiadis

Learning latent representations has aided operational decision-making in several disciplines. Its advantages include uncovering hidden interactions in data and automating procedures which were performed manually in the past. Representation learning is also being adopted by earth and environmental sciences. However, there are still subfields that depend on ma

Debraj Nath, Amlan K. Roy

Analytical solutions are presented for eigenvalues, eigenfunctions of {\color{red} D-dimensional Schrodinger equation having Eckart potential} within Nikiforov-Uvarov method. This uses a new, improved approximation for centrifugal term, from a combination of Greene-Aldrich and Pekeris approximations. Solutions are obtained in terms of hypergeometric function

Johannes H. Uhl, Stefan Leyk

The level of landscape heterogeneity may affect the performance of remote sensing based land use / land cover classification. However, the relationship between mapping accuracy of built-up surfaces and morphological characteristics of built-up areas has not been analyzed explicitly, and previous studies typically rely on aggregated landscape metrics to quant

Yunqi Sun, Jianfeng Zhou

Field distortion is widespread in imaging systems. If it cannot be measured and corrected well, it will affect the accuracy of photogrammetry. To this end, we proposed a general field distortion model based on Fredholm integration, which uses a reconstructed high-resolution reference point spread function (PSF) and two sets of 4-variable polynomials to descr

Claudio Pinhanez, Paulo Cavalin

This work explores the intrinsic limitations of the popular one-hot encoding method in classification of intents when detection of out-of-scope (OOS) inputs is required. Although recent work has shown that there can be significant improvements in OOS detection when the intent classes are represented as dense-vectors based on domain specific knowledge, we arg

Fanghao Yang, Xingqiu Yuan

Many existing timed-release encryption schemes uses time-lock puzzles to avoid relying on a trusted timeserver or a key holder which could be a weak spot in data security. However, it is unavoidable to consume massive computing power for solving time-lock puzzles and it is difficult for encryptors to predict the amount of time to solve a puzzle by decryptors

Akifumi Sako

We introduce a category composed of all quantizations of all Poisson algebras. By the category, we can treat in a unified way the various quantizations for all Poisson algebras and develop a new classical limit formulation. This formulation proposes a new method for the inverse problem, that is, the problem of finding the classical limit from a quantized spa

Neetik Mukherjee, Amlan K. Roy

Shell confined atom can serve as a generalized model to explain both \emph{free} and \emph{confined} condition. In this scenario, an atom is trapped inside two concentric spheres of inner $(R_{a})$ and outer $(R_{b})$ radius. The choice of $R_{a}, R_{b}$ renders four different quantum mechanical systems. In hydrogenic atom, they are termed as (a) free hydrog

Marvin Tammen, Xilin Li, Simon Doclo, Lalin Theverapperuma

In mobile speech communication applications, wind noise can lead to a severe reduction of speech quality and intelligibility. Since the performance of speech enhancement algorithms using acoustic microphones tends to substantially degrade in extremely challenging scenarios, auxiliary sensors such as contact microphones can be used. Although contact microphon

Dilli R. Paudel, Diego Marcos, Allard de Wit, Hendrik Boogaard

Predictor inputs and label data for crop yield forecasting are not always available at the same spatial resolution. We propose a deep learning framework that uses high resolution inputs and low resolution labels to produce crop yield forecasts for both spatial levels. The forecasting model is calibrated by weak supervision from low resolution crop area and y

Pascal Bergsträßer, Moses Ganardi, Anthony W. Lin, Georg Zetzsche

Automatic structures are infinite structures that are finitely represented by synchronized finite-state automata. This paper concerns specifically automatic structures over finite words and trees (ranked/unranked). We investigate the "directed version" of Ramsey quantifiers, which express the existence of an infinite directed clique. This subsumes the standa

Joseph Harry Silber, Parker Fagrelius, Kevin Fanning, Michael Schubnell

A system of 5,020 robotic fiber positioners was installed in 2019 on the Mayall Telescope, at Kitt Peak National Observatory. The robots automatically re-target their optical fibers every 10 - 20 minutes, each to a precision of several microns, with a reconfiguration time less than 2 minutes. Over the next five years, they will enable the newly-constructed D

Nick Huggett, Niels Linnemann, Mike Schneider

It has long been thought that observing distinctive traces of quantum gravity in a laboratory setting is effectively impossible, since gravity is so much weaker than all the other familiar forces in particle physics. But the quantum gravity phenomenology community today seeks to do the (effectively) impossible, using a challenging novel class of `tabletop' G

Morteza Hasanvand

Let $G$ be a bipartite graph with bipartition $(X,Y)$, let $k$ be a positive integer, and let $f:V(G)\rightarrow \{-1,\ldots, k-2\}$ be a mapping with $\sum_{v\in X}f(v) \stackrel{k}{\equiv}\sum_{v\in Y}f(v)$. In this paper, we show that if $G$ is essentially $(3k-3)$-edge-connected and for each vertex $v$, $d_G(v)\ge 2k-1+f(v)$, then it admits a factor $H$

Yuri A. Kordyukov

The Bochner-Schr\"odinger operator $H_{p}=\frac 1p\Delta^{L^p\otimes E}+V$ on tensor powers $L^p$ of a Hermitian line bundle $L$ twisted by a Hermitian vector bundle $E$ on a Riemannian manifold of bounded geometry is studied. For any function $\varphi\in \mathcal S(\mathbb R)$, we consider the bounded linear operator $\varphi(H_p)$ in $L^2(X,L^p\otimes E)$

Ugo Tricoli, Leon Schlemmer

Broken-supersymmetry is used to define a reflectionless active cavity capable of amplifying electromagnetic radiation in the visible. The approach is analytical through the use of the Darboux transform for the generation of the optical potential and the calculation of its solution, while the transmission/reflection spectra evaluation is done with the Transfe

The LHCb collaboration

The interpretation of cosmic antiproton flux measurements from space-borne experiments is currently limited by the knowledge of the antiproton production cross-section in collisions between primary cosmic rays and the interstellar medium. Using collisions of protons with an energy of 6.5 TeV incident on helium nuclei at rest in the proximity of the interacti

Nir Bachrach, Inbal Talgam-Cohen

Robust mechanism design is a rising alternative to Bayesian mechanism design, which yields designs that do not rely on assumptions like full distributional knowledge. We apply this approach to mechanisms for selling a single item, assuming that only the mean of the value distribution and an upper bound on the bidder values are known. We seek the mechanism th

Hitarth Choubisa, Jehad Abed, Douglas Mendoza, Zhenpeng Yao

To enable the accelerated discovery of materials with desirable properties, it is critical to develop accurate and efficient search algorithms. Quantum annealers and similar quantum-inspired optimizers have the potential to provide accelerated computation for certain combinatorial optimization challenges. However, they have not been exploited for materials d

Robert Beinert, Cosmas Heiss, Gabriele Steidl

Let $x_1 < \dots < x_n$ and $y_1 < \dots < y_n$, $n \in \mathbb N$, be real numbers. We show by an example that the assignment problem $$ \max_{\sigma \in S_n} F_\sigma(x,y) := \frac12 \sum_{i,k=1}^n |x_i - x_k|^\alpha \, |y_{\sigma(i)} - y_{\sigma(k)}|^\alpha, \quad \alpha >0, $$ is in general neither solved by the identical permutation (id) nor the anti-id

Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz

We present IPU Trusted Extensions (ITX), a set of experimental hardware extensions that enable trusted execution environments in Graphcore's AI accelerators. ITX enables the execution of AI workloads with strong confidentiality and integrity guarantees at low performance overheads. ITX isolates workloads from untrusted hosts, and ensures their data and model

Yeongseong Jo

Let $F$ be a non-archimedean local field of characteristic different from $2$ and $G$ be either an odd special orthogonal group ${\rm SO}_{2r+1}(F)$ or a symplectic group ${\rm Sp}_{2r}(F)$. In this paper, we establish the local converse theorem for $G$. Namely, for given two irreducible admissible generic representations of $G$ with the same central charact

Aleix Bassolas, Sergio Gómez, Alex Arenas

Urban systems are characterized by populations with heterogeneous characteristics, and whose spatial distribution is crucial to understand inequalities in life expectancy or education level. Traditional studies on spatial segregation indicators focus often on first-neighbour correlations but fail to capture complex multi-scale patterns. In this work, we aim

Sogo Murakami

We prove that oriented and standard shadowing properties are equivalent for topological flows with finite singularites that are Lyapunov stable or Lyapunov unstable. Moreover, we prove that the direct product $\phi_1 \times \phi_2$ of two topological flows has the oriented shdowing property if $\phi_1$ with finite singuralities has the oriented shadowing pro

Kevin Marc Seja, Tomas Lofwander

The Eilenberger-Larkin-Ovchinnikov-Eliashberg quasiclassical theory of superconductivity is a powerful method enabling studies of a wide range of equilibrium and non-equilibrium phenomena in conventional and unconventional superconductors. We introduce here a finite element method, based on a discontinuous Galerkin approach, to self-consistently solve the un

Antón Baleato Lizancos, Simone Ferraro

The search for primordial $B$-mode polarization of the CMB is limited by the sample variance of $B$-modes produced at later times by gravitational lensing. Constraints can be improved by `delensing': using some proxy of the matter distribution to partially remove the lensing-induced $B$-modes. Current and soon-upcoming experiments will infer a matter map --

Reza Karimzadeh, Javad Sheikh, Hamed Azarnoush, Hossein Arabi

Surgical simulators have been widely used in training and evaluation of physicians and surgeons. Virtual reality augmented with haptic technology has made it feasible to develop more realistic surgical simulators. In this context, we set out to design and develop a brain surgery bipolar electrocautery simulator using haptic technology. A 3D model of brain ti

Kento Asai, Coh Miyao, Shohei Okawa, Koji Tsumura

We study a renormalizable scalar singlet dark matter model based on $Z_4$ lepton flavor symmetry. A $\mu\tau$-philic scalar doublet is introduced to explain the discrepancy between the experimental value and the theoretical prediction of the muon anomalous magnetic moment. At the same time, these flavored scalars play the role of a mediator which connects da

Jose Moura, David Hutchison

It is becoming common practice to push interactive and location-based services from remote datacenters to resource-constrained edge domains. This trend creates new management challenges at the network edge, not least to ensure resilience. These challenges now need to be investigated and overcome. In this paper, we explore the use of open-source programmable

Quang Dang Nguyen, Mikhail Prokopenko

The COVID-19 pandemic created enormous public health and socioeconomic challenges. The health effects of vaccination and non-pharmaceutical interventions (NPIs) were often contrasted with significant social and economic costs. We describe a general framework aimed to derive adaptive cost-effective interventions, adequate for both recent and emerging pandemic

Michel Lavrauw, John Sheekey

We classify symplectic 4-dimensional semifields over $\mathbb{F}_q$, for $q\leq 9$, thereby extending (and confirming) the previously obtained classifications for $q\leq 7$. The classification is obtained by classifying all symplectic semifield subspaces in $\mathrm{PG}(9,q)$ for $q\leq 9$ up to $K$-equivalence, where $K\leq \mathrm{PGL}(10,q)$ is the lift o

Changjie Zhou, Huili Zhu, Weifeng Yang, Qiubao Lin

Two-dimensional (2D) WS2 films were deposited on SiO2 wafers, and the related interfacial properties were investigated by high-resolution x-ray photoelectron spectroscopy (XPS) and first-principles calculations. Using the direct (indirect) method, the valence band offset (VBO) at monolayer WS2/SiO2 interface was found to be 3.97 eV (3.86 eV), and the conduct

Qianqian Dong, Fengpeng Yue, Tom Ko, Mingxuan Wang

Direct Speech-to-speech translation (S2ST) has drawn more and more attention recently. The task is very challenging due to data scarcity and complex speech-to-speech mapping. In this paper, we report our recent achievements in S2ST. Firstly, we build a S2ST Transformer baseline which outperforms the original Translatotron. Secondly, we utilize the external d

Djamila Oudrar, Maurice Pouzet, Imed Zaguia

This paper is a contribution to the study of hereditary classes of finite graphs. We classify these classes according to the number of prime structures they contain. We consider such classes that are \emph{minimal prime}: classes that contain infinitely many primes but every proper hereditary subclass contains only finitely many primes. We give a complete ch

Frédéric Chyzak, Alexandre Goyer, Marc Mezzarobba

We present a symbolic-numeric Las Vegas algorithm for factoring Fuchsian ordinary differential operators with rational function coefficients. The new algorithm combines ideas of van Hoeij's "local-to-global" method and of the ''analytic'' approach proposed by van der Hoeven. It essentially reduces to the former in ''easy'' cases where the local-to-global met

H. Chau Nguyen, Jan Lennart Bönsel, Jonathan Steinberg, Otfried Gühne

Advances in quantum technology require scalable techniques to efficiently extract information from a quantum system, such as expectation values of observables or its entropy. Traditional tomography is limited to a handful of qubits and shadow tomography has been suggested as a scalable replacement for larger systems. Shadow tomography is conventionally analy

Ryan Feng, Neal Mangaokar, Jihye Choi, Somesh Jha

Patch attacks against object detectors have been of recent interest due to their being physically realizable and more closely aligned with practical systems. In response to this threat, many new defenses have been proposed that train a patch segmenter model to detect and remove the patch before the image is passed to the downstream model. We unify these appr

Erion Çano, Benjamin Roth

Collections of research article data harvested from the web have become common recently since they are important resources for experimenting on tasks such as named entity recognition, text summarization, or keyword generation. In fact, certain types of experiments require collections that are both large and topically structured, with records assigned to sepa

Sudipta Priyadarshini, Sukanta Nayak, Paresh Kumar Panigrahi

Convection-diffusion of heat transfer is one of the important phenomena in fluid flow and industrial problems. The involved parameters, boundary conditions, and material properties are greatly affecting the same. As such, the uncertainness of these parameters, conditions, and properties cannot be ignored. Therefore, the present research work focuses numerica

Sebastian Stock, Fabian Vu, David Geleßus, Atif Mashkoor

This document lays out the foundations for VO and requirement refinement, abstractions of models, and instantiations. Also, VOs on abstractions and instantiations are considered.

Jianqiao Zheng, Sameera Ramasinghe, Xueqian Li, Simon Lucey

It is well noted that coordinate-based MLPs benefit -- in terms of preserving high-frequency information -- through the encoding of coordinate positions as an array of Fourier features. Hitherto, the rationale for the effectiveness of these positional encodings has been mainly studied through a Fourier lens. In this paper, we strive to broaden this understan

Valery E. Lyubovitskij, Ivan Schmidt, Stanley J. Brodsky

A new approach to nonperturbative QCD, holographic light-front QCD, provides a comprehensive model for hadron dynamics and spectroscopy, incorporating color confinement, a universal hadron mass scale, the prediction of a massless pion in the chiral limit, and connections between the spectroscopy of mesons, baryons and tetraquarks across the full hadron spect

Daniel Fejgin, Simon Doclo

Recently, a method has been proposed to estimate the direction of arrival (DOA) of a single speaker by minimizing the frequency-averaged Hermitian angle between an estimated relative transfer function (RTF) vector and a database of prototype anechoic RTF vectors. In this paper, we extend this method to multi-speaker localization by introducing the frequency-

Manuel Nieto-Vesperinas, Xiaohao Xu

We uncover the existence of a universal phenomenon concerning the electromagnetic optical force exerted by light or other electromagnetic waves on a distribution of charges and currents in general, and of particles in particular. This conveys the appearence of underlying reactive quantities that hinder radiation pressure and currently observed time-averaged

Marvin Tammen, Simon Doclo

To improve speech intelligibility and speech quality in noisy environments, binaural noise reduction algorithms for head-mounted assistive listening devices are of crucial importance. Several binaural noise reduction algorithms such as the well-known binaural minimum variance distortionless response (MVDR) beamformer have been proposed, which exploit spatial