May 2022 arXiv papers — page 78

Karl Bringmann, Alejandro Cassis

We present new exact and approximation algorithms for 0-1-Knapsack and Unbounded Knapsack: * Exact Algorithm for 0-1-Knapsack: 0-1-Knapsack has known algorithms running in time $\widetilde{O}(n + \min\{n OPT, n W, OPT^2, W^2\})$, where $n$ is the number of items, $W$ is the weight budget, and $OPT$ is the optimal profit. We present an algorithm running in ti

Shingo Sugiyama

Let $\Gamma$ be a Fuchsian group in ${\rm SL}_2(\mathbb{R})$. In this note, we discuss the existence of $\rho$-equivariant functions for a two-dimensional representation $\rho$ of $\Gamma$. This assertion was first stated by Saber and Sebbar in 2020, and this note partially fills a gap of their statement by proving the assertion for a certain class of Fuchsi

Andrew Thompson, Larisa Y. C. Loke, Brenna Argall

Users of assistive devices vary in their extent of motor impairment, and hence their physical interaction with control interfaces can differ. There is the potential for improved utility if control interface actuation is mapped to assistive device control signals in a manner customized to each user. In this paper, we present (1) a method for creating a custom

Julio Toledo, Renann Lipinski Jusinskas, Carlos A. Hernaski, Pedro R. S. Gomes

Over the years, many theoretical frameworks have been developed to understand the remarkable physics of the quantum Hall system. In this work we discuss the interplay among quantum wires, Chern-Simons theory, bosonization, and particle-vortex duality, which enable a unified approach for the Laughlin states of the fractional quantum Hall system. Starting from

C. Dumitresc, M. Wolf

Applying Littlewood's lemma in connection to Riemann's Hypothesis and exploiting the symmetry of Riemann's $xi$ function we show that almost all nontrivial Riemann's Zeta zeros are on the critical line.

Oscar Aguayo, Samuel Sepúlveda

Context: The Importance of Dynamic Variability Management in Dynamic Software Product Lines. Objective: Define a protocol for conducting a systematic mapping study to summarize and synthesize evidence on dynamic variability management for Dynamic Software Product Lines in self-adaptive systems. Method: Application the protocol to conduct a systematic mapping

S. Krishnia, Y. Sassi, F. Ajejas, N. Reyren

The ability of spin-orbit interactions to convert charge current into spin current, most often in the bulk of heavy metal thin films, has been the hallmark of spintronics in the last decade. In this study, we demonstrate how the insertion of light metal element interface profoundly affects both the nature of spin-orbit torque and its efficiency in terms of d

Richard Cushman

This paper details the geometry of the Kustaanheimo-Stiefel mapping, which regularizes the Hamiltonian of the Kepler problem. It leans heavily on the work of J.-C. van der Meer.

Moisés García Chamorro, Rubén Gómez González, Vicente Garzó

It is well-recognized that granular media under rapid flow conditions can be modeled as a gas of hard spheres with inelastic collisions. At moderate densities, a fundamental basis for the determination of the granular hydrodynamics is provided by the Enskog kinetic equation conveniently adapted to account for inelastic collisions. A surprising result (compar

Zhichao Chang, Hui Xia

We investigate numerically the effects of long-range temporal and spatial correlations based on the rescaled distributions of the squared interface width $W^2(L,t)$ and the interface height $h(x,t)$ in the (1+1)-dimensional Kardar-Parisi-Zhang (KPZ) growth system within the early growth regimes. Through extensive numerical simulations, we find that long-rang

Charles Cifarelli, Ronan J. Conlon, Alix Deruelle

Let $D$ be a toric K\"ahler-Einstein Fano manifold. We show that any toric shrinking gradient K\"ahler-Ricci soliton on certain toric blowups of $\mathbb{C}\times D$ satisfies a complex Monge-Amp\`ere equation. We then set up an Aubin continuity path to solve this equation and show that it has a solution at the initial value of the path parameter. This we do

Alexander Senichev, Samuel Peana, Zachariah O. Martin, Omer Yesilyurt

The recent discovery of room temperature intrinsic single-photon emitters in silicon nitride (SiN) provides the unique opportunity for seamless monolithic integration of quantum light sources with the well-established SiN photonic platform. In this work, we develop a novel approach to realize planar waveguides made of low-autofluorescing SiN with intrinsic q

Valentin N. Hartmann, Marlin P. Strub, Marc Toussaint, Jonathan D. Gammell

Multiquery planning algorithms find paths between various different starts and goals in a single search space. They are designed to do so efficiently by reusing information across planning queries. This information may be computed before or during the search and often includes knowledge of valid paths. Using known valid paths to solve an individual planning

Ali Farahbakhsh, Chen Feng

Unlike classical routing algorithms, quantum routing algorithms make use of entangled states - a type of resources that have a limited lifetime and need to be regenerated after consumption. In a nutshell, quantum routing algorithms have to use these resources efficiently, while optimizing some objectives such as the total waiting time. Current routing algori

Ankan Mullick, Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik

A law practitioner has to go through numerous lengthy legal case proceedings for their practices of various categories, such as land dispute, corruption, etc. Hence, it is important to summarize these documents, and ensure that summaries contain phrases with intent matching the category of the case. To the best of our knowledge, there is no evaluation metric

J. S. Dowker

An earlier contour expression for the Green function of a free complex scalar field in the presence of a conical singularity with localised magnetic flux is shown to yield expressions for the field correlator and defect block expansions that have been more recently found in connection with monodromy defects in conformal field theory. The Green function appea

M. Kamil, S. Triambak, G. C. Ball, V. Bildstein

We use a high resolution $^{32}{\rm S}(d,t)$ measurement to investigate the claimed existence of a 6401(3) keV state in $^{31}$S that may affect the $^{30}{\rm P}(p,\gamma)$ nuclear reaction rate in oxygen-neon (ONe) novae. Our data are shown to exclude the null hypothesis - that the state does not exist - with high significance. Additionally, the data also

Bhanuka Mahanama, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas Ashok

Reading plays a vital role in updating the researchers on recent developments in the field, including but not limited to solutions to various problems and collaborative studies between disciplines. Prior studies identify reading patterns to vary depending on the level of expertise of the researcher on the content of the document. We present a pilot study of

Lior Gishboliner, Benny Sudakov

A chordal graph is a graph with no induced cycles of length at least $4$. Let $f(n,m)$ be the maximal integer such that every graph with $n$ vertices and $m$ edges has a chordal subgraph with at least $f(n,m)$ edges. In 1985 Erd\H{o}s and Laskar posed the problem of estimating $f(n,m)$. In the late '80s, Erd\H{o}s, Gy\'arf\'as, Ordman and Zalcstein determine

Nguyen Thanh Duc, Nguyen Thi Oanh, Nguyen Thi Thuy, Tran Minh Triet

Identifying polyps is challenging for automatic analysis of endoscopic images in computer-aided clinical support systems. Models based on convolutional networks (CNN), transformers, and their combinations have been proposed to segment polyps with promising results. However, those approaches have limitations either in modeling the local appearance of the poly

Stefan Kuntz, Robert Dauth, Gerald Gerlach, Peter Ott

We present a rigorous analytical method for harmonic analysis of the angular error of rotary and linear encoders with sine/cosine output signals in quadrature that are distorted by superimposed Fourier series. To calculate the angle from measured sine and cosine encoder channels in quadrature, the arctangent function is commonly used. The hence non-linear re

Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini, Christophe Fatras

As the severity and occurrence of flood events tend to intensify with climate change, the need for flood forecasting capability increases. In this regard, the Flood Detection, Alert and rapid Mapping (FloodDAM) project, funded by Space for Climate Observatory initiatives, was set out to develop pre-operational tools dedicated to enabling quick responses in f

Tomona Kinugawa, Tetsuo Hyodo

The composite nature of a shallow bound state is studied by using the weak-binding relation, which connects the compositeness of the bound state with observables. We first show that the previous weak-binding relation cannot be applied to the system with a large effective range. To overcome this difficulty, we introduce the finite-range correction by redefini

Alejandro Perez, Daniel Sudarsky

We present two alternative perspectives for the resolution of Hawking's information puzzle in black hole evaporation. The two views are deeply contrasting, yet they share several common aspects. One of them is the central role played by the existence of the interior singularity (whose physical relevance is implied by the singularity theorems of Penrose) that

Daniela Leite, Diego Baptista, Abdullahi Ibrahim, Enrico Facca

Detecting communities in networks is important in various domains of applications. While a variety of methods exists to perform this task, recent efforts propose Optimal Transport (OT) principles combined with the geometric notion of Ollivier-Ricci curvature to classify nodes into groups by rigorously comparing the information encoded into nodes' neighborhoo

Haiqing Zhang, Chen Li, Shiliang Ai, Haoyuan Chen

The gold standard for gastric cancer detection is gastric histopathological image analysis, but there are certain drawbacks in the existing histopathological detection and diagnosis. In this paper, based on the study of computer aided diagnosis system, graph based features are applied to gastric cancer histopathology microscopic image analysis, and a classif

Arya Chandran, K Vishnu Namboothiri

Srinivasa Ramanujan provided series expansions of certain arithmetical functions in terms of the exponential sums defined by $c_r(n) = \sum\limits_{\substack{{m=1}\\ (m,r)=1}}^{r} e^{\frac{2 \pi imn}{r}}$ in [Trans. Cambridge Phillos. Soc, 22(13):259-276,1918]. Here we give similar type of expansions in terms of the Cohen-Ramanujan sum defined by E. Cohen in

Daniele Malpetti, Alfredo Bellisario, Chiara Macchiavello

We study entanglement properties of hypergraph states in arbitrary finite dimension. We compute multipartite entanglement of elementary qudit hypergraph states, namely those endowed with a single maximum-cardinality hyperedge. We show that, analogously to the qubit case, also for arbitrary dimension there exists a lower bound for multipartite entanglement of

Andrew Patterson, Victor Liao, Martha White

Most value function learning algorithms in reinforcement learning are based on the mean squared (projected) Bellman error. However, squared errors are known to be sensitive to outliers, both skewing the solution of the objective and resulting in high-magnitude and high-variance gradients. To control these high-magnitude updates, typical strategies in RL invo

F. Laloë

Penrose has suggested that large fluctuations of the gravitational energy of quantum systems, resulting from fluctuations of its density in space, may induce a quantum collapse mechanism \cite{Penrose-1996}, but he did not propose a precise dynamics for this process. We use the GBC (Gravitational Bohmian Collapse) model \cite{GBC}, which provides such a dyna

Abdul Rahman Sani, Muneeb Ul Hassan, Longxiang Gao, Jinjun Chen

In the recent years, the interest of individual users in modern electric vehicles (EVs) has grown exponentially. An EV has two major components, which make it different from traditional vehicles, first is its environment friendly nature because of being electric, and second is the interconnection ability of these vehicles because of modern information and co

Avner Shultzman, Yonina C. Eldar

Due to its non-invasive and non-radiating nature, along with its low cost, ultrasound (US) imaging is widely used in medical applications. Typical B-mode US images have limited resolution and contrast and weak physical interpretation. Inverse US methods were developed to reconstruct the media's speed-of-sound (SoS) based on a linear acoustic model. However,

Lukas Tarra, Andreas Deutschmann-Olek, Vinzenz Stummer, Tobias Flöry

In this paper, we present a novel stochastic and spatially lumped multi-mode model to describe the nonlinear dynamics of actively Q-switched lasers and random perturbations due to amplified spontaneous emission. This model will serve as a basis for the design of (nonlinear) control and estimation strategies and thus a high value is set on its computational e

Arash Shahmansoori, Utz Roedig

Voice assistants overhear conversations and a consent management mechanism is required. Consent management can be implemented using speaker recognition. Users that do not give consent enrol their voice and all their further recordings are discarded. Building speaker recognition-based consent management is challenging as dynamic registration, removal, and re-

Yizhou Zhao, Hua Sun

The secure summation problem is considered, where $K$ users, each holds an input, wish to compute the sum of their inputs at a server securely, i.e., without revealing any information beyond the sum even if the server may collude with any set of up to $T$ users. First, we prove a folklore result for secure summation - to compute $1$ bit of the sum securely,

Slawomir Klimek, Matt McBride, John Wilson Peoples

We discuss various aspects of noncommutative geometry of smooth subalgebras of Bunce-Deddens-Toeplitz Algebras.

Alena Ernst, Kai-Uwe Schmidt

A subset $Y$ of the general linear group $\operatorname{GL}(n,q)$ is called $t$-intersecting if $\operatorname{rk}(x-y)\le n-t$ for all $x,y\in Y$, or equivalently $x$ and $y$ agree pointwise on a $t$-dimensional subspace of $\mathbb{F}_q^n$ for all $x,y\in Y$. We show that, if $n$ is sufficiently large compared to $t$, the size of every such $t$-intersectin

William Ravenscroft, Stefan Goetze, Thomas Hain

Speech dereverberation is an important stage in many speech technology applications. Recent work in this area has been dominated by deep neural network models. Temporal convolutional networks (TCNs) are deep learning models that have been proposed for sequence modelling in the task of dereverberating speech. In this work a weighted multi-dilation depthwise-s

Max Spahn, Martijn Wisse, Javier Alonso-Mora

Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and non-holonomic robots and prove that fundamental properties can be conserved. We show that convergence

Michael Farber, Amit Kumar Paul

In this paper we develop theory of sequential parametrized motion planning which generalises the approach of parametrized motion planning, which was introduced recently in [3]. A sequential parametrized motion planning algorithm produced a motion of the system which is required to visit a prescribed sequence of states, in certain order, at specified moments

Scott Cheng-Hsin Yang, Tomas Folke, Patrick Shafto

The goal of explainable Artificial Intelligence (XAI) is to generate human-interpretable explanations, but there are no computationally precise theories of how humans interpret AI generated explanations. The lack of theory means that validation of XAI must be done empirically, on a case-by-case basis, which prevents systematic theory-building in XAI. We prop

Ngoc Hoang Anh Mai

We utilize the same technique as in [arXiv:2205.04254 (2022)] to provide some representations of polynomials non-negative on a basic semi-algebraic set, defined by polynomial inequalities, under more general conditions. Based on each representation, we obtain semidefinite programs which return a sequence of values that finitely converges to the optimal value

Fajar Haifani, Patrick Koopmann, Sophie Tourret, Christoph Weidenbach

Abduction in description logics finds extensions of a knowledge base to make it entail an observation. As such, it can be used to explain why the observation does not follow, to repair incomplete knowledge bases, and to provide possible explanations for unexpected observations. We consider TBox abduction in the lightweight description logic EL, where the obs

Qian Hu, John Veitch

With the improvement in sensitivity of gravitational wave (GW) detectors and the increasing diversity of GW sources, there is a strong need for accurate GW waveform models for data analysis. While the current model accuracy assessments require waveforms generated by numerical relativity (NR) simulations as the "true waveforms", in this paper we propose an as

Satoya Imai, Otfried Gühne, Stefan Nimmrichter

We consider quantum batteries given by composite interacting quantum systems in terms of the thermodynamic work cost of local random unitary processes. We characterize quantum correlations by monitoring the average energy change and its fluctuations in the high-dimensional bipartite systems. We derive a hierarchy of bounds on high-dimensional entanglement (t

Eduard Gorbunov, Adrien Taylor, Gauthier Gidel

The Past Extragradient (PEG) [Popov, 1980] method, also known as the Optimistic Gradient method, has known a recent gain in interest in the optimization community with the emergence of variational inequality formulations for machine learning. Recently, in the unconstrained case, Golowich et al. [2020] proved that a $O(1/N)$ last-iterate convergence rate in t

Olivia Jacome, Shobhit Gupta, Stephanie Stockar, Marcello Canova

Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or Advanced Driver Assistance Systems (ADAS), have the opportunity to improve energy savings. However, lower levels of automation involve a human-machine interaction stage, where the presence of a human driver affects the performance of the cont

Chuandi Zhang, Qianhui Xu, Xu-Tao Zeng, Chao Lyu

The effects of Sr doping on the structural properties of Na$_{2}$BaCo(PO$_{4}$)$_{2}$, a spin-1/2 triangular-lattice antiferromagnet as a quantum spin liquid candidate, are investigated by complementary x-ray and neutron powder diffraction measurements. It is found that in Na$_{2}$Ba$_{1-x}$Sr$_{x}$Co(PO$_{4}$)$_{2}$ (NBSCPO), the trigonal phase (space group

Dario Pasquini, Mathilde Raynal, Carmela Troncoso

In this work, we carry out the first, in-depth, privacy analysis of Decentralized Learning -- a collaborative machine learning framework aimed at addressing the main limitations of federated learning. We introduce a suite of novel attacks for both passive and active decentralized adversaries. We demonstrate that, contrary to what is claimed by decentralized

Tim Hoheisel, Elliot Paquette

In this paper we establish necessary and sufficient conditions for the existence of line segments (or flats) in the sphere of the nuclear norm via the notion of simultaneous polarization and a refined expression for the subdifferential of the nuclear norm. This is then leveraged to provide (point-based) necessary and sufficient conditions for uniqueness of s

Sergio Izquierdo, Max Argus, Thomas Brox

Visual Servoing has been effectively used to move a robot into specific target locations or to track a recorded demonstration. It does not require manual programming, but it is typically limited to settings where one demonstration maps to one environment state. We propose a modular approach to extend visual servoing to scenarios with multiple demonstration s

Simon Tschirner, Shashank Shekher Tripathi, Mathias Roeper, Markus M. Becker

Blockchains provide environments where parties can interact transparently and securely peer-to-peer without needing a trusted third party. Parties can trust the integrity and correctness of transactions and the verifiable execution of binary code on the blockchain (smart contracts) inside the system. Including information from outside of the blockchain remai

Renat Sergazinov, Andrew Leroux, Erjia Cui, Ciprian Crainiceanu

Continuous glucose monitors (CGMs) are increasingly used to measure blood glucose levels and provide information about the treatment and management of diabetes. Our motivating study contains CGM data during sleep for 174 study participants with type II diabetes mellitus measured at a 5-minute frequency for an average of 10 nights. We aim to quantify the effe

Alexander Brownlee, Martin Pelikan, John McCall, Andrei Petrovski

Chemotherapy treatment for cancer is a complex optimisation problem with a large number of interacting variables and constraints. A number of different probabilistic algorithms have been applied to it with varying success. In this paper we expand on this by applying two estimation of distribution algorithms to the problem. One is UMDA, which uses a univariat

Margherita Mele, Roberto Covino, Raffaello Potestio

A steadily growing computational power is employed to perform molecular dynamics simulations of biological macromolecules, which represents at the same time an immense opportunity and a formidable challenge. In fact, large amounts of data are produced, from which useful, synthetic, and intelligible information has to be extracted to make the crucial step fro

Daniela De Silva, Ovidiu Savin

We obtain density estimates for the free boundaries of minimizers $u \ge 0$ of the Alt-Phillips functional involving negative power potentials $$\int_\Omega \left(|\nabla u|^2 + u^{-\gamma} \chi_{\{u>0\}}\right) \, dx, \quad \quad \gamma \in (0,2).$$ These estimates remain uniform as the parameter $\gamma \to 2$. As a consequence we establish the uniform con

Wing Fung Chong, Runhuan Feng, Hins Hu, Linfeng Zhang

This paper introduces a two-pillar cyber risk management framework to address the pervasive challenges in managing cyber risk. The first pillar, cyber risk assessment, combines insurance frequency-severity models with cybersecurity cascade models to capture the unique nature of cyber risk. The second pillar, cyber capital management, facilitates informed all

Youssef Nader, Leon Sixt, Tim Landgraf

K-nearest neighbors (KNN) is one of the earliest and most established algorithms in machine learning. For regression tasks, KNN averages the targets within a neighborhood which poses a number of challenges: the neighborhood definition is crucial for the predictive performance as neighbors might be selected based on uninformative features, and averaging does

Adar Kahana, Qian Zhang, Leonard Gleyzer, George Em Karniadakis

The main computational task of Scientific Machine Learning (SciML) is function regression, required both for inputs as well as outputs of a simulation. Physics-Informed Neural Networks (PINNs) and neural operators (such as DeepONet) have been very effective in solving Partial Differential Equations (PDEs), but they tax computational resources heavily and can

Dan Barbasch, Kayue Daniel Wong

In this paper, we compute the character formula of the Brylinski model for all classical nilpotent varieties $\overline{\mathcal{O}}$. As a consequence, one can compute the multiplicities of all $K-$types of the ring of regular functions $R(\overline{\mathcal{O}})$ for all classical nilpotent varieties.

Juan Carlos Bilbao-Ludena, George Papadakis

We investigate the spatial distributions and production mechanisms of vorticity and turbulent kinetic energy around a finite NACA 0018 wing with square wingtip profile at $Re_c=10^4$ and $10^{\circ}$ angle of attack with the aid of Direct Numerical Simulation (DNS). The analysis focuses on the highly inhomogeneous region around the tip and the near wake; thi

Guo-yuan Huang, Manfred Lindner, Pablo Martínez-Miravé, Manibrata Sen

We investigate a consistent scenario of time-varying neutrino masses, and discuss its impact on cosmology, beta decay, and neutrino oscillation experiments. Such time-varying masses are assumed to be generated by the coupling between a sterile neutrino and an ultralight scalar field, which in turn affects the light neutrinos by mixing. Besides, the scalar co

Lin Shih-Chun, Lin Chia-Hung, Chu Liang C., Lien Shao-Yu

Low earth orbit (LEO) mega-constellations, integrating government space systems and commercial practices, have emerged as enabling technologies for the sixth generation (6G) networks due to their good merits of global coverage and ubiquitous services for military and civilian use cases. However, convergent LEO-based satellite networking infrastructures still

Xiao-Wu Chen, Zhengfang Wang

For a noetherian ring $\Lambda$, the stabilization functor in the sense of Krause yields an embedding of the singularity category of $\Lambda$ into the homotopy category of acyclic complexes of injective $\Lambda$-modules. When $\Lambda$ contains a semisimple artinian subring $E$, we give an explicit description of the stabilization functor using the Hom com

Yuhao Hu, Peng Liu, Yuguang Shi

By using Gromov's $\mu$-bubble technique, we show that the $3$-dimensional spherical caps are rigid under perturbations that do not reduce the metric, the scalar curvature, and the mean curvature along its boundary. Several generalizations of this result will be discussed.

Yun Wang, Tian-Ci Zheng, Zhi-Ping Jin

The physical composition of the ejecta of gamma-ray bursts (GRBs) remains an open question. The radiation mechanism of the prompt gamma rays is also in debate. This problem can be solved for the bursts hosting distinct thermal radiation. However, the events with dominant thermal spectral components are still rare. In this work, we focus on GRB 220426A, a rec

Kshiteej J. Deshmukh, Graeme W. Milton

Changing the microstructure properties of a space-time metamaterial while a wave is propagating through it, in general requires addition or removal of energy, which can be of exponential form depending on the type of modulation. This limits the realization and application of space-time metamaterials. We resolve this issue by introducing a novel mechanism of

Ryan Shah, Chuadhry Mujeeb Ahmed, Shishir Nagaraja

Connected robots play a key role in Industry 4.0, providing automation and higher efficiency for many industrial workflows. Unfortunately, these robots can leak sensitive information regarding these operational workflows to remote adversaries. While there exists mandates for the use of end-to-end encryption for data transmission in such settings, it is entir

Abdelhakim Hannousse, Salima Yahiouche, Mohamed Cherif Nait-Hamoud

Cross-site scripting (XSS) is one of the major threats menacing the privacy of data and the navigation of trusted web applications. Since its reveal in late 1999 by Microsoft security engineers, several techniques have been developed in the aim to secure web navigation and protect web applications against XSS attacks. The problem became worse with the emerge

Stijn N. B. Debackere, Henk Hoekstra, Joop Schaye

Systematic uncertainties in the mass measurement of galaxy clusters limit the cosmological constraining power of future surveys that will detect more than $10^5$ clusters. Previously, we argued that aperture masses can be inferred more accurately and precisely than 3D masses without loss of cosmological constraining power. Here, we use the Baryons and Haloes

Cong Jiang, Zong-Wen Yu, Xiao-Long Hu, Xiang-Bin Wang

Based on the idea that there is no side channel in the vacuum state, the side-channel-free quantum key distribution (SCFQKD) protocol was proposed, which is immune to all attacks in the source side-channel space and all attacks in the detectors. In the original SCFQKD protocol, an important assumption is that Alice and Bob can produce the perfect vacuum puls

Qingyu Li, Yilei Shi, Xiao Xiang Zhu

Accurate and reliable building footprint maps are vital to urban planning and monitoring, and most existing approaches fall back on convolutional neural networks (CNNs) for building footprint generation. However, one limitation of these methods is that they require strong supervisory information from massive annotated samples for network learning. State-of-t

Xiang Li, Jing Hao, Jiguang Bao

In this paper, we discuss the more general Hessian inequality $\sigma_{k}^{\frac{1}{k}}(\lambda (D_i (A\left(|Du|\right) D_j u)))\geq f(u)$ including the Laplacian, p-Laplacian, mean curvature, Hessian, k-mean curvature operators, and provide a necessary and sufficient condition on the global solvability, which can be regarded as generalized Keller-Osserman

Ruby J. Wright, Claudia del P. Lagos, Chris Power, Adam R. H. Stevens

Using the EAGLE suite of simulations, we demonstrate that both cold gas stripping {\it and} starvation of gas inflow play an important role in quenching satellite galaxies across a range of stellar and halo masses, $M_{\star}$ and $M_{200}$. By quantifying the balance between gas inflows, outflows, and star formation rates, we show that even at $z=2$, only $

Max Dabagia, Konrad P Kording, Eva L Dyer

Many questions in neuroscience involve understanding of the responses of large populations of neurons. However, when dealing with large-scale neural activity, interpretation becomes difficult, and comparisons between two animals, or across different time points becomes challenging. One major challenge that we face in modern neuroscience is that of correspond

Valentina Pansanella, Giulio Rossetti, Letizia Milli

Nowadays, we live in a society where people often form their opinion by accessing and discussing contents shared on social networking websites. While these platforms have fostered information access and diffusion, they represent optimal environments for the proliferation of polluted contents, which is argued to be one of the co-causes of polarization/radical

Quentin Da Cruz Lopes, Sophie Ramananarivo, Caroline Cohen, Michael Benzaquen

We designed and built a reduced-scale model experiment to study the paragliding inflation and launching phase at given traction force. We show that the launch trajectory of a single skin glider is universal, that is, independent of the exerted force. As a consequence, the length of the take-off run required for the glider to reach its "ready to launch" verti

Kurando Baba, Osamu Ikawa

In this paper, we first introduce the notion of double Satake diagrams for compact symmetric triads. In terms of this notion, we give an alternative proof for the classification theorem for compact symmetric triads, which was originally given by Toshihiko Matsuki. Secondly, we introduce the notion of canonical forms for compact symmetric triads, and prove th

Georgios Amanatidis, Georgios Birmpas, Philip Lazos, Francisco J. Marmolejo-Cossío

Motivated by governance models adopted in blockchain applications, we study the problem of selecting appropriate system updates in a decentralised way. Contrary to most existing voting approaches, we use the input of a set of motivated experts of varying levels of expertise. In particular, we develop an approval voting inspired selection mechanism through wh

Ravi Kothari, Ali Kariminezhad, Christian Mayr, Haoming Zhang

Radar is an inevitable part of the perception sensor set for autonomous driving functions. It plays a gap-filling role to complement the shortcomings of other sensors in diverse scenarios and weather conditions. In this paper, we propose a Deep Neural Network (DNN) based end-to-end object detection and heading estimation framework using raw radar data. To th

Florian Miserez, Saswati Ganguly, Rudolf Haussmann, Matthias Fuchs

We present a microscopic derivation of the laws of continuum mechanics of nonideal ordered solids including dissipation, defect diffusion, and heat transport. Starting point is the classical many-body Hamiltonian. The approach relies on the Zwanzig-Mori projection operator formalism to connect microscopic fluctuations to thermodynamic derivatives and transpo

Rafia Inam, Alberto Yukinobu Hata, Vlasjov Prifti, Sara Abbaspour Asadollah

The recent development of artificial intelligence (AI) has increased the interest of researchers and practitioners towards applying its techniques into multiple domains like automotive, health care and air space to achieve automation. Combined to these applications, the attempt to use AI techniques into carrying out safety issues is momentarily at a progress

Yoshimasa Hidaka, Satoshi Iso, Kengo Shimada

Entanglement generation by Newtonian gravitational potential between objects has been widely discussed to reveal the quantum nature of gravity. In this paper, we perform a quantum field theoretical analysis of a slightly modified version of the gedanken experiment by Mari and co-workers. We show that decoherence due to the presence of a detector propagates w

Md Atiqul Islam, George C. Alexandropoulos, Besma Smida

In this paper, we present an Integrated Sensing and Communications (ISAC) system enabled by in-band Full Duplex (FD) radios, where a massive Multiple-Input Multiple-Output (MIMO) base station equipped with hybrid Analog and Digital (A/D) beamformers is communicating with multiple DownLink (DL) users, and simultaneously estimates via the same signaling wavefo

Niles Johnson, Donald Yau

We show that each of the three $K$-theory multifunctors from small permutative categories to $\mathcal{G}_*$-categories, $\mathcal{G}_*$-simplicial sets, and connective spectra, is an equivalence of homotopy theories. For each of these $K$-theory multifunctors, we describe an explicit homotopy inverse functor. As a separate application of our general results

K. Badiane, G. Rodary, M. Amato, A. Gloter

p-d hybridization of transition metal impurities in a semiconductor host is the mechanism that couples valence-band electrons and localized spins. We use scanning tunneling microscopy and spectroscopy combined with density functional theory to probe at the atomic scale hybridization of Cr single impurities with GaAs host. Combining spatial density of states

Lisa Bonheme, Marek Grzes

The ability of Variational Autoencoders (VAEs) to learn disentangled representations has made them popular for practical applications. However, their behaviour is not yet fully understood. For example, the questions of when they can provide disentangled representations, or suffer from posterior collapse are still areas of active research. Despite this, there

François Smekens, Nicolas Freud, Bruno Sixou, Guillaume Beslon

Proton therapy is a modality in fast development. Characterized by a maximum dose deposition at the end of the proton trajectory followed by a sharp fall-off, proton beams can deliver a highly conformal dose to the tumor while sparing organs at risk and surrounding healthy tissues. New treatment planning systems based on spot scanning techniques can now prop

Rasmus Pagh, Mikkel Thorup

Sketching is an important tool for dealing with high-dimensional vectors that are sparse (or well-approximated by a sparse vector), especially useful in distributed, parallel, and streaming settings. It is known that sketches can be made differentially private by adding noise according to the sensitivity of the sketch, and this has been used in private analy

Andrzej Rozkosz, Leszek Slominski

We show, that under natural assumptions, solutions of Dirichlet problems for uniformly elliptic divergence form operator can be approximated pointwise by solutions of some versions of Robin problems. The proof is based on stochastic representation of solutions and properties of reflected diffusions corresponding to divergence form operators.

Gary Gordon

The relational interpretation of quantum mechanics (RQM), introduced in its present form by Carlo Rovelli in 1996, involves a number of significant departures from other QM interpretations widely discussed in the literature. We begin here by summarizing these unique RQM features, with a focus on those that suggest altered insights into the nature of the rand

Alain Thomas

To prove that a measure, linearly representable by means of a finite set of nonnegative matrices $\mathcal M$, has the weak-Gibbs property, one check the uniform convergence (on $\mathcal M^\mathbb N$) of the sequence of vectors $\frac{A_1\cdots A_nc}{\Vert A_1\cdots A_nc\Vert}$ ($c$ positive column-vector). The main theorem gives a sufficient condition for

Sara Lafia, Lizhou Fan, Andrea Thomer, Libby Hemphill

Data archives are an important source of high quality data in many fields, making them ideal sites to study data reuse. By studying data reuse through citation networks, we are able to learn how hidden research communities - those that use the same scientific datasets - are organized. This paper analyzes the community structure of an authoritative network of

Ida Häggström, Lukas M. Carter, Thomas J. Fuchs, Adam L. Kesner

AIMS: Clinical radiographic imaging is seated upon the principle of differential keV photon transmission through an object. At clinical x-ray energies the scattering of photons causes signal noise and is utilized solely for transmission measurements. However, scatter - particularly Compton scatter, is characterizable. In this work we hypothesized that modern

George C. Alexandropoulos, Md Atiqul Islam, Besma Smida

The increasingly demanding objectives for next generation wireless communications have spurred recent research activities on multi-antenna transceiver hardware architectures and relevant intelligent communication schemes. Among them belong the Full Duplex (FD) Multiple-Input Multiple-Output (MIMO) architectures, which offer the potential for simultaneous upl

Chiara Balestra, Florian Huber, Andreas Mayr, Emmanuel Müller

Not all real-world data are labeled, and when labels are not available, it is often costly to obtain them. Moreover, as many algorithms suffer from the curse of dimensionality, reducing the features in the data to a smaller set is often of great utility. Unsupervised feature selection aims to reduce the number of features, often using feature importance scor

Jiawei Shen, Andrea Mifsud, Lijie Xie, Abdulaziz Alshaya

Emerging memristor-based array architectures have been effectively employed in non-volatile memories and neuromorphic computing systems due to their density, scalability and capability of storing information. Nonetheless, to demonstrate a practical on-chip memristor-based system, it is essential to have the ability to apply large programming voltage ranges d

Yuhao Mo, Chu Han, Yu Liu, Min Liu

Ultrasonography is an important routine examination for breast cancer diagnosis, due to its non-invasive, radiation-free and low-cost properties. However, the diagnostic accuracy of breast cancer is still limited due to its inherent limitations. It would be a tremendous success if we can precisely diagnose breast cancer by breast ultrasound images (BUS). Man

Giuseppe Vecchio, Simone Palazzo, Dario C. Guastella, Ignacio Carlucho

We present MIDGARD, an open-source simulation platform for autonomous robot navigation in outdoor unstructured environments. MIDGARD is designed to enable the training of autonomous agents (e.g., unmanned ground vehicles) in photorealistic 3D environments, and to support the generalization skills of learning-based agents through the variability in training s

Raphael Wagner, Emil Wiedemann

We study statistical solutions of the incompressible Euler equations in two dimensions with vorticity in $L^p$, $1\leq p \leq \infty$, and in the class of vortex-sheets with a distinguished sign. Our notion of statistical solution is based on the framework due to Bronzi, Mondaini and Rosa. Existence in this setting is shown by approximation with discrete mea