December 2020 arXiv papers — page 18

Vladimir Vovk

This note continues study of exchangeability martingales, i.e., processes that are martingales under any exchangeable distribution for the observations. Such processes can be used for detecting violations of the IID assumption, which is commonly made in machine learning. Violations of the IID assumption are sometimes referred to as dataset shift, and dataset

Lorenzo Iorio

Putative natural massive satellites (exomoons) has gained increasing attention, where they orbit Jupiter-like planets within the habitable zone of their host main sequence star. An exomoon is expected to move within the equatorial plane of its host planet, with its spin ${\boldsymbol S}_\mathrm{s}$ aligned with its orbital angular momentum $\boldsymbol L$ wh

Siyang Li, Ke Ding, Aijun Ding, Lejun He

As an important symbol of civilization and culture, architectures originally were built for sheltering human beings from weather disasters and therefore should be affected by climate change, particularly the associated change in the occurrence of extreme weather events. However, although meteorology has been considered as a factor in modern architecture desi

R. Schupp, L. Behnke, J. Sheil, Z. Bouza

Experimental spectroscopic studies are presented, in a 5.5--25.5nm extreme-ultraviolet (EUV) wavelength range, of the light emitted from plasma produced by the irradiation of tin microdroplets by 5-ns-pulsed, 2-$\mu$m-wavelength laser light. Emission spectra are compared to those obtained from plasma driven by 1-$\mu$m-wavelength Nd:YAG laser light over a ra

Cong Zhang, Shicong Song, Muxin Han

Given the Loop-Quantum-Gravity (LQG) non-graph-changing Hamiltonian $\widehat{H[N]}$, the coherent state expectation value $\langle\widehat{H[N]}\rangle$ admits an semiclassical expansion in $\ell^2_{\rm p}$. In this paper, we compute explicitly the expansion of $\langle\widehat{H[N]}\rangle$ on the cubic graph to the linear order in $\ell^2_{\rm p}$, when t

Hamed Barzegar, David Fajman

It is shown that Milne models (a subclass of FLRW spacetimes with negative spatial curvature) are nonlinearly stable in the set of solutions to the Einstein-Vlasov-Maxwell system, describing universes with ensembles of collisionless self-gravitating, charged particles. The system contains various slowly decaying borderline terms in the mutually coupled equat

Marko Mihajlovic, Silvan Weder, Marc Pollefeys, Martin R. Oswald

We present DeepSurfels, a novel hybrid scene representation for geometry and appearance information. DeepSurfels combines explicit and neural building blocks to jointly encode geometry and appearance information. In contrast to established representations, DeepSurfels better represents high-frequency textures, is well-suited for online updates of appearance

Hartmut Pecher

The local well-posedness problem for the Maxwell-Klein-Gordon system in Coulomb gauge as well as Lorenz gauge is treated in two space dimensions for data with minimal regularity assumptions. In the classical case of data in $L^2$-based Sobolev spaces $H^s$ and $H^l$ for the electromagnetic field $\phi$ and the potential $A$, respectively. The minimal regular

Nirian Martín

Even though the Rao's score tests are classical tests, such as the likelihood ratio tests, their application has been avoided until now in a multivariate framework, in particular high-dimensional setting. We consider they could play an important role for testing high-dimensional data, but currently the classical Rao's score tests for an arbitrary but fixed d

Thomas Vogel, Chinh Tran, Lars Grunske

Context: In search-based software engineering we often use popular heuristics with default configurations, which typically lead to suboptimal results, or we perform experiments to identify configurations on a trial-and-error basis, which may lead to better results for a specific problem. We consider the problem of generating test suites for mobile applicatio

Argyrios Deligkas, John Fearnley, Themistoklis Melissourgos

We study the computational complexity of finding a solution for the straight-cut and square-cut pizza sharing problems. We show that computing an $\varepsilon$-approximate solution is PPA-complete for both problems, while finding an exact solution for the square-cut problem is FIXP-hard. Our PPA-hardness results apply for any $\varepsilon < 1/5$, even when a

Margarida Ferreira, Miguel Terra-Neves, Miguel Ventura, Inês Lynce

Form validators based on regular expressions are often used on digital forms to prevent users from inserting data in the wrong format. However, writing these validators can pose a challenge to some users. We present FOREST, a regular expression synthesizer for digital form validations. FOREST produces a regular expression that matches the desired pattern for

Bowen Hao, Jing Zhang, Cuiping Li, Hong Chen

The proliferation of massive open online courses (MOOCs) demands an effective way of course recommendation for jobs posted in recruitment websites, especially for the people who take MOOCs to find new jobs. Despite the advances of supervised ranking models, the lack of enough supervised signals prevents us from directly learning a supervised ranking model. T

Hyung-Chan An, Robert Kleinberg, David B. Shmoys

We present the first nontrivial approximation algorithm for the bottleneck asymmetric traveling salesman problem. Given an asymmetric metric cost between n vertices, the problem is to find a Hamiltonian cycle that minimizes its bottleneck (or maximum-length edge) cost. We achieve an O(log n / log log n) approximation performance guarantee by giving a novel a

Abdulaziz Abu El-Fadl, Azza M. Hassan, Mohamed A. Kassem

Nanoparticles of Cr3+-substituted Ni-Zn ferrites with a general formula Ni0.4Zn0.6-xCrxFe2O4 (x = 0.0 - 0.6) have been synthesized via a facile microwave combustion route. The crystalline phase has been characterized by XRD, TEM, FT-I and XPS revealing the spinel ferrite structure without extra phases. Crystallite sizes of 23 - 32 nm as estimated by XRD anal

Mark Beliaev, Erdem Bıyık, Daniel A. Lazar, Woodrow Z. Wang

The COVID-19 pandemic has severely affected many aspects of people's daily lives. While many countries are in a re-opening stage, some effects of the pandemic on people's behaviors are expected to last much longer, including how they choose between different transport options. Experts predict considerably delayed recovery of the public transport options, as

Fons van der Laan, René Reimann, Felix Tebbenjohanns, Jayadev Vijayan

According to quantum theory, measurement and backaction are inextricably linked. In optical position measurements, this backaction is known as radiation pressure shot noise. In analogy, a measurement of the orientation of a mechanical rotor must disturb its angular momentum by radiation torque shot noise. In this work, we observe the shot-noise torque fluctu

Bo Li, Wiro J. Niessen, Stefan Klein, Marius de Groot

This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear registration. Segmentation and registration are modeled using a convolutional neural network and optimized simulta

Philipp Ritzinger, Helena Reichlova, Dominik Kriegner, Anastasios Markou

Ferromagnetic Co$_2$MnGa has recently attracted significant attention due to effects related to non-trivial topology of its band structure, however a systematic study of canonical magneto-galvanic transport effects is missing. Focusing on high quality thin films, here we systematically measure anisotropic magnetoresistance (AMR) and its thermoelectric counte

Minne Li, Mengyue Yang, Furui Liu, Xu Chen

The capability of imagining internally with a mental model of the world is vitally important for human cognition. If a machine intelligent agent can learn a world model to create a "dream" environment, it can then internally ask what-if questions -- simulate the alternative futures that haven't been experienced in the past yet -- and make optimal decisions a

Yong Huang, Wei Wang, Tao Jiang, Qian Zhang

Due to the openness of wireless medium, robotic networks that consist of many miniaturized robots are susceptible to Sybil attackers, who can fabricate myriads of fictitious robots. Such detrimental attacks can overturn the fundamental trust assumption in robotic collaboration and thus impede widespread deployments of robotic networks in many collaborative t

Zonghai Li, Yujie Duan, Junji Jia

Based on the Jacobi metric method, this paper studies the deflection of a charged massive particle by a novel four-dimensional charged Einstein-Gauss-Bonnet black hole. We focus on the weak field approximation and consider the deflection angle with finite distance effects. To this end, we use a geometric and topological method, which is to apply the Gauss-Bo

Nicolas Behr, Stefan Fredenhagen

We investigate the fusion of B-type interfaces in two-dimensional supersymmetric Landau-Ginzburg models. In particular, we propose to describe the fusion of an interface in terms of a fusion functor that acts on the category of modules of the underlying polynomial rings of chiral superfields. This uplift of a functor on the category of matrix factorisations

Florian Loebbert, Jan Plefka, Canxin Shi, Tianheng Wang

We study the Post-Minkowskian (PM) and Post-Newtonian (PN) expansions of the gravitational three-body effective potential. At order 2PM a formal result is given in terms of a differential operator acting on the maximal generalized cut of the one-loop triangle integral. We compute the integral in all kinematic regions and show that the leading terms in the PN

E. En-naoui

Euler's totient function counts the positive integers up to a given integer n that are relatively prime to n. The aim of this article is to give a result about the sum of euler's totient function from k equal 1 to n whene p divides n and p a prime number.

G. Rebora, D. Ferraro, R. H. Rodriguez, F. D. Parmentier

We theoretically investigate the evolution of the peak height of an energy resolved electronic wave-packets ballistically propagating along integer quantum Hall edge channels at filling factor $\nu=2$. This is ultimately related to the elastic scattering amplitude for the fermionic excitations evaluated at different injection energy. We investigate this quan

Dmitry Novikov, Boris Shapiro, Guillaume Tahar

Meromorphic connections on Riemann surfaces originate and are closely related to the classical theory of linear ordinary differential equations with meromorphic coefficients. Limiting behaviour of geodesics of such connections has been studied by e.g. Abate, Bianchi and Tovena in relation with generalized Poincar\'{e}-Bendixson theorems. At present, it seems

Song Noh, Heejung Yu, Youngchul Sung

In this paper, the problem of training signal design for intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) communication under a sparse channel model is considered. The problem is approached based on the Cram$\acute{\text{e}}$r-Rao lower bound (CRB) on the mean-square error (MSE) of channel estimation. By exploiting the sparse structure

Igor Frenkel, Robert Penner

We review and reformulate old and prove new results about the triad $ {\rm PPSL}_2({\mathbb Z})\subseteq{\rm PPSL}_2({\mathbb R})\circlearrowright ppsl_2({\mathbb R}) $, which provides a universal generalization of the classical automorphic triad ${\rm PSL}_2({\mathbb Z})\subseteq{\rm PSL}_2({\mathbb R})\circlearrowright psl_2({\mathbb R})$. The leading P or

Michal Choras, Konstantinos Demestichas, Agata Gielczyk, Alvaro Herrero

Fake news has now grown into a big problem for societies and also a major challenge for people fighting disinformation. This phenomenon plagues democratic elections, reputations of individual persons or organizations, and has negatively impacted citizens, (e.g., during the COVID-19 pandemic in the US or Brazil). Hence, developing effective tools to fight thi

Hejing Li, Jialin Li, Antoine Kaufmann

Full system "end-to-end" measurements in physical testbeds are the gold standard for network systems evaluation but are often not feasible. When physical testbeds are not available we frequently turn to simulation for evaluation. Unfortunately, existing simulators are insufficient for end-to-end evaluation, as they either cannot simulate all components, or s

Ismet Karakan, Ceren Gürkan, Cem Avcı

Steady and unsteady Poisson and Stokes equations are solved using mesh dependent Finite Element Method and meshless Radial Basis Function Collocation Method to compare the performances of these two numerical techniques across several criteria. The accuracy of Radial Basis Function Collocation Method with multiquadrics is enhanced by implementing a shape para

Tokuro Fukui

How the nuclear force behaves in cluster states, in particular those consisting of the $\alpha$ clusters, has been investigated so far, but not yet elucidated. Today the chiral effective field theory is established and it would shed new light on the microscopic understanding of the cluster states. We aim to address a possible source of the attraction in the

Anderson L. R. Barbosa, Jorge Gabriel G. S. Ramos, Aires Ferreira

Van der Waals heterostructures based on two-dimensional materials have recently become a very active topic of research in spintronics, both aiming at a fundamental description of spin dephasing processes in nanostructures and as a potential element in spin-based information processing schemes. Here, we theoretically investigate the magnetoconductance of meso

A. Pahler, M. Ångermann, J. Barnstedt, S. Bougueroua

Stratospheric balloons offer accessible and affordable platforms for observations in atmosphere-constrained wavelength ranges. At the same time, they can serve as an effective step for technology demonstration towards future space applications of instruments and other hardware. The Stratospheric UV Demonstrator of an Imaging Observatory (STUDIO) is a balloon

Sen Yang, Zhibin Quan, Mu Nie, Wankou Yang

While CNN-based models have made remarkable progress on human pose estimation, what spatial dependencies they capture to localize keypoints remains unclear. In this work, we propose a model called \textbf{TransPose}, which introduces Transformer for human pose estimation. The attention layers built in Transformer enable our model to capture long-range relati

Gi-Chan Bae, Jin Woo Jang, Seok-Bae Yun

The relativistic quantum Boltzmann equation (or the relativistic Uehling-Uhlenbeck equation) describes the dynamics of single-species fast-moving quantum particles. With the recent development of the relativistic quantum mechanics, the relativistic quantum Boltzmann equation has been widely used in physics and engineering such as in the quantum collision exp

Rodolfo Gambini, Javier Olmedo, Jorge Pullin

We continue our investigation of an improved quantization scheme for spherically symmetric loop quantum gravity. We find that in the region where the black hole singularity appears in the classical theory, the quantum theory contains semi-classical states that approximate general relativity coupled to an effective anisotropic fluid. The singularity is elimin

Yanyan Li, Jingjing Zhang, Ting Zhang

In this paper, we show that Landau solutions to the Navier-Stokes system are asymptotically stable under $L^3$-perturbations. We give the local well-posedness of solutions to the perturbed system with initial data in $L_{\sigma}^3$ space and the global well-posedness with small initial data in $L_{\sigma}^3$ space, together with a study of the $L^q$ decay fo

Nils Reimers, Iryna Gurevych

Information Retrieval using dense low-dimensional representations recently became popular and showed out-performance to traditional sparse-representations like BM25. However, no previous work investigated how dense representations perform with large index sizes. We show theoretically and empirically that the performance for dense representations decreases qu

Rongjing Guo, Tai-Chang Chiang, Huan-hua Wang

Atomic-scale smooth thin films are keys to successful integration and proper function of many multilayer-structured devices. However, the intrinsic island-like growth mode prevents human being from realizing such ultrasmooth films of many important functional materials. To solve this problem, we propose a negative entropy-infusing method that employs evanesc

Tobias Becker, Ling-Na Wu, André Eckardt

Away from equilibrium, the properties of open quantum systems depend on the details of their environment. A microscopic derivation of a master equation (ME) is therefore crucial. Of particular interest are Lindblad-type equations, not only because they provide the most general class of Markovian MEs, but also since they are the starting point for efficient q

Jun Ma, Xiaoping Yang

Automatic segmentation of head and neck tumors plays an important role in radiomics analysis. In this short paper, we propose an automatic segmentation method for head and neck tumors from PET and CT images based on the combination of convolutional neural networks (CNNs) and hybrid active contours. Specifically, we first introduce a multi-channel 3D U-Net to

Hongmei Jing, Benrong Mu, Jun Tao, Peng Wang

Super-entropic black holes possess finite-area but noncompact event horizons and violate the reverse isoperimetric inequality. It has been conjectured that such black holes always have negative specific heat at constant volume $C_{V}$ or negative specific heat at constant pressure $C_{P}$ whenever $C_{V}>0$, making them unstable in extended thermodynamics. I

Marco Guarnieri, Marco Patrignani

Microarchitectural attacks exploit the abstraction gap between the Instruction Set Architecture (ISA) and how instructions are actually executed by processors to compromise the confidentiality and integrity of a system. To secure systems against microarchitectural attacks, programmers need to reason about and program against these microarchitectural side-eff

Maryam Dialameh, Ali Hamzeh, Hossein Rahmani, Amir Reza Radmard

The rapid outbreak of COVID-19 threatens humans life all around the world. Due to insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. As chest radiography, such as chest X-ray (CXR) and CT computed tomography (CT), is a possible way for screening COVID-19, developing an au

Zhangyang Gao, Haitao Lin, Stan. Z Li

Convolution and pooling are the key operations to learn hierarchical representation for graph classification, where more expressive $k$-order($k>1$) method requires more computation cost, limiting the further applications. In this paper, we investigate the strategy of selecting $k$ via neighborhood information gain and propose light $k$-order convolution and

Nuno J. Alves, Athanasios E. Tzavaras

This work establishes the relaxation limit from the bipolar Euler-Poisson system to the bipolar drift-diffusion system, for data so that the latter has a smooth solution. A relative energy identity is developed for the bipolar fluid system and is used to show that a dissipative weak solution of the bipolar Euler-Poisson system converges in the high-friction

Daniel C. Douglas, Zhe Sun

In a companion paper (arXiv 2011.01768), we constructed nonnegative integer coordinates $\Phi_\mathscr{T}(\mathscr{W}_{3, \hat{S}}) \subset \mathbb{Z}_{\geq 0}^N$ for the collection $\mathscr{W}_{3, \hat{S}}$ of reduced $\mathrm{SL}_3$-webs on a finite-type punctured surface $\hat{S}$, depending on an ideal triangulation $\mathscr{T}$ of $\hat{S}$. We show t

Stefan Konigorski, Sarah Wernicke, Tamara Slosarek, Alexander M. Zenner

N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully-functional platforms are not yet available. Here, we present the open source StudyU platform which includes the S

Max von Danwitz, Patrick Antony, Fabian Key, Norbert Hosters

Thinking of the flow through biological or technical valves, there is a variety of applications in which the topology of a fluid domain changes over time. This topology change is characteristic for the physical behaviour, but poses a particular challenge in computer simulations. A way to overcome this challenge is to consider the space-time extent of the app

Daniel Clavel, Cristian Mahulea, Manuel Silva

This paper considers the liveness enforcement problem in a class of Petri nets (PNs) modeling distributed systems called Synchronized Sequential Processes (SSP). This class of PNs is defined as a set of mono-marked state machines (sequential machines, called also agents) cooperating in a distributed way through buffers. These buffers could model intermediate

Yuri A. Kordyukov

In this paper, we construct a family of Berezin-Toeplitz type quantizations of a compact symplectic manifold. For this, we choose a Riemannian metric on the manifold such that the associated Bochner Laplacian has the same local model at each point (this is slightly more general than in almost-K\"ahler quantization). Then the spectrum of the Bochner Laplacian

Taro Kimura, Rui-Dong Zhu

In this article, we extend the work of arXiv:0901.4744 to a Bethe/Gauge correspondence between 2d (or resp. 3d) SO/Sp gauge theories and open XXX (resp. XXZ) spin chains with diagonal boundary conditions. The case of linear quiver gauge theories is also considered.

Yuri A. Kordyukov

We study the Bochner-Schr\"odinger operator $H_{p}=\frac 1p\Delta^{L^p\otimes E}+V$ on high tensor powers of a positive line bundle $L$ on a symplectic manifold of bounded geometry. First, we give a rough asymptotic description of its spectrum in terms of the spectra of the model operators. This allows us to prove the existence of gaps in the spectrum under

Sebastian Enqvist, Valentin Goranko

We introduce and study a natural extension of the Alternating time temporal logic ATL, called Temporal Logic of Coalitional Goal Assignments (TLCGA). It features just one, but quite expressive, coalitional strategic operator, viz. the coalitional goal assignment operator, which is based on a mapping assigning to each set of players in the game its coalitiona

Dhruvil Solanki, Prakash Adhikari, Ishmael Apachigawo, Fatemah Alharthi

The progression of cancer is associated with different genetic and epigenetic events which result in nano to microscale structural alterations in cells/tissue. However, these structural alterations in the early stage of the disease remain undetectable by conventional microscopy due to the diffraction-limited resolution of ~200nm. With cancer being an epidemi

Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo Kerg

The early phase of training a deep neural network has a dramatic effect on the local curvature of the loss function. For instance, using a small learning rate does not guarantee stable optimization because the optimization trajectory has a tendency to steer towards regions of the loss surface with increasing local curvature. We ask whether this tendency is c

Konstantinos Kaloudis, George A. Kevrekidis, Helena C. Maltezou, Cleo Anastassopoulou

Herein, we provide estimations for the effective reproduction number $R_e$ for the greater metropolitan area of Athens, Greece during the first wave of the pandemic (February 26-May 15, 2020). For our calculations, we implemented, in a comparative approach, the two most widely used methods for the estimation of $R_e$, that by Wallinga and Teunis and by Cori

Jinhong Jung, Jaemin Yoo, U Kang

Given a signed social graph, how can we learn appropriate node representations to infer the signs of missing edges? Signed social graphs have received considerable attention to model trust relationships. Learning node representations is crucial to effectively analyze graph data, and various techniques such as network embedding and graph convolutional network

Laurent Charles

We consider a magnetic Laplacian on a compact manifold, with a constant non-degenerate magnetic field. In the large field limit, it is known that the eigenvalues are grouped in clusters, the corresponding sums of eigenspaces being called the Landau levels. The first level has been studied in-depth as a natural generalization of the Kaehler quantization. The

Enno Diekema

This paper is an edited and shortened version of Chapter 6 from the thesis of the author. First the one dimensional orthogonal derivative will be extended to the two-dimensional case. In the two-dimensional case we have to define the region of integration. In this paper we treat the integration over the square region and over the triangle region where in the

Jun Gao, Vladyslav Shtabovenko, Tong-Zhi Yang

In this work we complete the investigation of the recently introduced energy-energy correlation (EEC) function in hadronic Higgs decays at next-to-leading order (NLO) in fixed-order perturbation theory in the limit of vanishing light quark masses. The full analytic NLO result for the previously unknown EEC in the $H \to q \bar{q} + X$ channel is given in ter

T. R. Tan, C. L. Edmunds, A. R. Milne, M. J. Biercuk

We report measurements of the branching fraction, hyperfine constant, and second-order Zeeman coefficient of the D$_{5/2}$ level in $^{171}$Yb$^+$ with up to two orders-of-magnitude improvement in precision compared to previously reported values. We estimate the electric quadrupole reduced matrix element of the S$_{1/2}$ $\leftrightarrow$ D$_{5/2}$ transitio

Hichem Sahbi

Learning graph convolutional networks (GCNs) is an emerging field which aims at generalizing deep learning to arbitrary non-regular domains. Most of the existing GCNs follow a neighborhood aggregation scheme, where the representation of a node is recursively obtained by aggregating its neighboring node representations using averaging or sorting operations. H

Alex Hernandez-Garcia

Interdisciplinary research is often at the core of scientific progress. This dissertation explores some advantageous synergies between machine learning, cognitive science and neuroscience. In particular, this thesis focuses on vision and images. The human visual system has been widely studied from both behavioural and neuroscientific points of view, as visio

Emre Baspinar, Luca Calatroni, Valentina Franceschi, Dario Prandi

We consider Wilson-Cowan-type models for the mathematical description of orientation-dependent Poggendorff-like illusions. Our modelling improves two previously proposed cortical-inspired approaches embedding the sub-Riemannian heat kernel into the neuronal interaction term, in agreement with the intrinsically anisotropic functional architecture of V1 based

Nageswara Rao Vemuri

In this article, a functional equation(IE) involving fuzzy implications has been considered. Two different perspectives of this equation have been provided to realize its significance. As it is very difficult to find the solutions of (IE) in general, the investigation of solutions of (IE) is restricted to main families of fuzzy implications.

Miguel A. Barja

We study and obtain Slope inequalities for fibred irregular varieties of non-maximal Albanese dimension. We give a comparison theorem between Clifford-Severi and Slope inequalities for this type of fibrations. We also obtain a set of Slope inequalities considering the geometry of the Albanese map and the associated eventual maps.

Sai Swetha Venkata Kolluru, Puneet Sharma, Rahul Pandit

We develop a Fourier-Chebyshev pseudospectral direct numerical simulation (DNS) to examine a potentially singular solution of the radially bounded, three-dimensional (3D), axisymmetric Euler equations [G. Luo and T.Y. Hou, Proc. Natl. Acad. Sci. USA, 111.36 (2014)]. We demonstrate that: (a) the time of singularity is preceded, in any spectrally truncated DNS

Sándor Jenei

We study amalgamation in odd and even involutive commutative residuated chains through their categorical representation by bunches of linearly ordered abelian groups. The representation separates three obstructions. A discrete $κ_J$-layer imports the failure of amalgamation for discrete abelian ordered groups with normal embeddings. Even when $κ_J$ is empty,

Filippo Brandolini, Guillem Domingo Ribas, Andrea Zerboni, Sam Turner

The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote an interdisciplinary dialogue to facilitate complementary landscape management strategies. With the socio-economic values of the natural and cultural landscape heritage increas

Anne-Ségolène Cottereau, Christophe Nioche, Anne-Sophie Dirand, Jérôme Clerc

We assessed the predictive value of new radiomic features characterizing the lesion dissemination in baseline 18F-FDG PET and tested whether combining them with baseline metabolic tumour volume (MTV) could improve prediction of progression free survival (PFS) and overall survival (OS) in diffuse large B cell lymphoma (DLBCL) patients.

Javier Gonzalez-Huerta, Jefferson Seide Molleri, Aivars Šablis, Ehsan Zabardast

Background: Software project management activities help to introduce software process models in Software Engineering courses. However, these activities should be adequately aligned with the learning outcomes and support student's progression. Objective: Present and evaluate an approach to help students acquire theoretical and practical knowledge and experien

Yong Siah Teo, Kimin Park, Seongwook Shin, Hyunseok Jeong

We propose a practical strategy for choosing sets of input coherent states that are near-optimal for reconstructing single-mode Gaussian quantum processes with output-state heterodyne measurements. We first derive analytical expressions for the mean squared-error that quantifies the reconstruction accuracy for general process tomography and large data. Using

Gabriela Csurka

Domain adaptation (DA) aims at improving the performance of a model on target domains by transferring the knowledge contained in different but related source domains. With recent advances in deep learning models which are extremely data hungry, the interest for visual DA has significantly increased in the last decade and the number of related work in the fie

AS Dirand, F Frouin, I Buvat

Many studies are devoted to the design of radiomic models for a prediction task. When no effective model is found, it is often difficult to know whether the radiomic features do not include information relevant to the task or because of insufficient data. We propose a downsampling method to answer that question when considering a classification task into two

Yong Li, David Sauzin, Shanzhong Sun

We discuss the analytic continuation of the Hadamard product of two holomorphic functions under assumptions pertaining to Ecalle's Resurgence Theory, proving that if both factors are endlessly continuable with prescribed sets of singular points $A$ and $B$, then so is their Hadamard product with respect to the set $\{0\}\cup A \cdot B$. In this generalizatio

Mingyu Xiao, Hiroshi Nagamochi

In the bounded-degree cut problem, we are given a multigraph $G=(V,E)$, two disjoint vertex subsets $A,B\subseteq V$, two functions $\mathrm{u}_A, \mathrm{u}_B:V\to \{0,1,\ldots,|E|\}$ on $V$, and an integer $k\geq 0$. The task is to determine whether there is a minimal $(A,B)$-cut $(V_A,V_B)$ of size at most $k$ such that the degree of each vertex $v\in V_A

David Morales, Estefania Talavera, Beatriz Remeseiro

The field of deep learning is evolving in different directions, with still the need for more efficient training strategies. In this work, we present a novel and robust training scheme that integrates visual explanation techniques in the learning process. Unlike the attention mechanisms that focus on the relevant parts of images, we aim to improve the robustn

Joe Kileel, Amit Moscovich, Nathan Zelesko, Amit Singer

Manifold learning methods play a prominent role in nonlinear dimensionality reduction and other tasks involving high-dimensional data sets with low intrinsic dimensionality. Many of these methods are graph-based: they associate a vertex with each data point and a weighted edge with each pair. Existing theory shows that the Laplacian matrix of the graph conve

Yue Li, Benedetta Tondi, Mauro Barni

DNN watermarking is receiving an increasing attention as a suitable mean to protect the Intellectual Property Rights associated to DNN models. Several methods proposed so far are inspired to the popular Spread Spectrum (SS) paradigm according to which the watermark bits are embedded into the projection of the weights of the DNN model onto a pseudorandom sequ

Andrzej Herdegen

We consider the Dirac equation for the classical spinor field placed in an external, time-dependent electromagnetic field of the form typical for scattering settings: $F=F^\mathrm{ret}+F^\mathrm{in}=F^\mathrm{adv}+F^\mathrm{out}$, where the current producing $F^{\mathrm{ret}/\mathrm{adv}}$ has past and future asymptotes homogeneous of degree $-3$, and the fr

Magnús M. Halldórsson, Fabian Kuhn, Yannic Maus, Tigran Tonoyan

Distributed vertex coloring is one of the classic problems and probably also the most widely studied problems in the area of distributed graph algorithms. We present a new randomized distributed vertex coloring algorithm for the standard CONGEST model, where the network is modeled as an $n$-node graph $G$, and where the nodes of $G$ operate in synchronous co

Hristo Manev, Mancho Manev

There are introduced and studied a pair of associated Schouten-van Kampen affine connections adapted to the paracontact distribution and an almost paracontact almost paracomplex Riemannian structure generated by the pair of associated metrics and their Levi-Civita connections. By means of the constructed non-symmetric connections, the basic classes of the ma

Andrea Visentin, Steven Prestwich, Roberto Rossi, S. Armagan Tarim

A well-know control policy in stochastic inventory control is the (R, s, S) policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls below reorder-level s. To date, little or no work has been devoted to developing approaches for computing (R, s, S) policy parameters. In this work, we introduce a hybrid approach t

E. A. O'Brien, I. Ponomarenko, A. V. Vasil'ev, E. Vdovin

Let $m$ be a positive integer and let $\Omega$ be a finite set. The $m$-closure of $G\leq\operatorname{Sym}(\Omega)$ is the largest permutation group on $\Omega$ having the same orbits as $G$ in its induced action on the Cartesian product $\Omega^m$. The $1$-closure and $2$-closure of a solvable permutation group need not be solvable. We prove that the $m$-c

Liang-qi Zhang, Shao-dong Wu, Hai-rong Huang, Hao-yang Lan

We investigate a novel scheme for brilliant attosecond {\gamma}-ray emission and high-yield positron production, which is accomplished with an ultra-intense laser pulse incident upon a Nano-Micro array (NMA) with substrate incorporated. This scheme is able to realize effectively electron acceleration and colliding geometry. Both the {\gamma}-ray flash and po

Yew Ken Chia, Sam Witteveen, Martin Andrews

Explainable question answering for science questions is a challenging task that requires multi-hop inference over a large set of fact sentences. To counter the limitations of methods that view each query-document pair in isolation, we propose the LSTM-Interleaved Transformer which incorporates cross-document interactions for improved multi-hop ranking. The L

Mélodie Boillet, Christopher Kermorvant, Thierry Paquet

In this paper, we introduce a fully convolutional network for the document layout analysis task. While state-of-the-art methods are using models pre-trained on natural scene images, our method Doc-UFCN relies on a U-shaped model trained from scratch for detecting objects from historical documents. We consider the line segmentation task and more generally the

Yiming Ding, Yun Sun

We consider the topological behaviors of continuous maps with one topological attractor on compact metric space $X$. This kind of map is a generalization of maps such as topologically expansive Lorenz map, unimodal map without homtervals and so on. We provide a leveled $A$-$R$ pair decomposition for such maps, and characterize $\alpha$-limit set of each poin

Emilien Chapon, David d'Enterria, Bertrand Ducloue, Miguel G. Echevarria

Prospects for quarkonium-production studies accessible during the upcoming high-luminosity phases of the CERN Large Hadron Collider operation after 2021 are reviewed. Current experimental and theoretical open issues in the field are assessed together with the potential for future studies in quarkonium-related physics. This will be possible through the exploi

Niko Jokela, K. Kajantie, Miika Sarkkinen

We study the empirical realization of the memory effect in Yang-Mills theory with an axion-like particle, especially in view of the classical vs. quantum nature of the theory. We solve for the coupled equations of motion iteratively in the axionic contributions and explicitly display the gauge invariant effects in terms of field strengths. We apply our resul

Guoxue Yao, Jiulin Du

We study the dust surface potential for the complex dusty plasma with negative ions and with a three-parameter non-Maxwell velocity distribution. The plasma contains electrons, positive ions, negative ions, and negatively charged dust particles. By using the current equilibrium condition, we derive the relationship between the normalized dust surface potenti

Matthieu Marbac, Mohammed Sedki, Christophe Biernacki, Vincent Vandewalle

We investigate the parameter estimation of regression models with fixed group effects, when the group variable is missing while group related variables are available. This problem involves clustering to infer the missing group variable based on the group related variables, and regression to build a model on the target variable given the group and eventually

Yujiro Kawamata

We calculate a semi-orthogonal decomposition of the bounded derived category of coherent sheaves on P(1,1,1,3) using a tilting bundle.

Davide Dobrilla, Stefano Francaviglia

A fake octagon is a genus two translation surface with only one singular point and the same periods as the octagon. Existence of infinitely many fakes was first established by McMullen in 2007, and more generally follows from dynamical properties of the so called isoperiodic foliation. The purpose of this note is to build an explicit infinite family of fake

Uğur Erkan, Abdurrahim Toktas, Serdar Enginoğlu, Enver Karabacak

A secure and reliable image encryption scheme is presented in this study. The encryption scheme hereby introduces a novel chaotic log-map, deep convolution neural network (CNN) model for key generation, and bit reversion operation for the manipulation process. Thanks to the sensitive key generation, initial values and control parameters are produced for the

Marko Kostić

In this paper, we analyze multi-dimensional Bohr $({\mathcal B},c)$-almost periodic type functions. The main structural characterizations for the introduced classes of Bohr $({\mathcal B},c)$-almost periodic type functions are established. Several applications of our abstract theoretical results to the abstract Volterra integro-differential equations in Bana

Tayeb Jamali

We describe a two-dimensional model for active particles whose self-propulsion speed is not fixed, but varies in time, and whose motion is subject to both translational and rotational diffusion. In the conventional treatment of active Brownian motion, the self-propulsion speed is taken to be constant - an assumption convenient for analysis but poorly matched