June 2020 arXiv papers — page 42

P. Samantray, R. H. J. Peerlings, E. Bosco, M. G. D. Geers

Materials like paper, consisting of a network of natural fibres, exposed to variations in moisture, undergo changes in geometrical and mechanical properties. This behaviour is particularly important for understanding the hygro-mechanical response of sheets of paper in applications like digital printing. A two-dimensional microstructural model of a fibrous ne

U. A. Rozikov

We define a DNA as a sequence of $1, 2$'s and embed it on a path of Cayley tree in such a way that each vertex of the Cayley tree belongs only to one of DNA and each DNA has its own countably many set of neighboring DNAs. The Hamiltonian of this set of DNAs is a model with two spin values considered as DNA base pairs. We describe translation invariant Gi

A. D. Alhaidari, H. Bahlouli

We obtain a class of exact solutions of a Bessel-type differential equation, which is a six-parameter linear ordinary differential equation of the second order with irregular (essential) singularity at the origin. The solutions are obtained using the Tridiagonal Representation Approach (TRA) as bounded series of square integrable functions written in terms o

Tongxin Li, Steven H. Low, Adam Wierman

Aggregators have emerged as crucial tools for the coordination of distributed, controllable loads. However, to be used effectively, aggregators must be able to communicate the available flexibility of the loads they control to the system operator in a manner that is both (i) concise enough to be scalable to aggregators governing hundreds or even thousands of

Varun Mannam, Yide Zhang, Yinhao Zhu, Scott Howard

We present a new convolutional neural network (CNN) based ImageJ plugin for fluorescence microscopy image denoising with an average improvement of 7.5 dB in peak signal-to-noise ratio (PSNR) and denoising instantly within 80 msec.

Rainald Löhner, Harbir Antil, Sergio Idelsohn, Eugenio Oñate

A summary is given of the mechanical characteristics of virus contaminants and the transmission via droplets and aerosols. The ordinary and partial differential equations describing the physics of these processes with high fidelity are presented, as well as appropriate numerical schemes to solve them. Several examples taken from recent evaluations of the bui

David Hilditch, Juan A. Valiente Kroon, Peng Zhao

We adapt Luk's analysis of the characteristic initial value problem in General Relativity to the asymptotic characteristic problem for the conformal Einstein field equations to demonstrate the local existence of solutions in a neighbourhood of the set on which the data are given. In particular, we obtain existence of solutions along a narrow rectangle al

Zlatko Koinov

Recently, the attractive Kane-Mele-Habbard (KMH) model on a honeycomb lattice at half filling has been studied in two papers: PRB 99, 184514 (2019) and PRB 94, 104508 (2016). The authors of the first one presented the phase diagram which interpolates the trivial and non-trivial topological states. However, the next-nearest-neighbor (NNN) hopping term has bee

Mehrdad Ghadiri, Richard Santiago, Bruce Shepherd

Submodular function maximization has found a wealth of new applications in machine learning models during the past years. The related supermodular maximization models (submodular minimization) also offer an abundance of applications, but they appeared to be highly intractable even under simple cardinality constraints. Hence, while there are well-developed to

Paulo R. Zingano, Janaina P. Zingano, Alessandra M. Silva, Carolina P. Zingano

We discuss the generation of various reproduction ratios or numbers that are very useful to monitor an ongoing epidemic like Covid-19 and examine the effects of intervention measures. A detailed SEIR algorithm is described for their computation, with applications given to the current Covid-19 outbreaks in a number of countries (Argentina, Brazil, France, Ita

Yanli Chen, Peijun Li, Xiaokai Yuan

Consider the electromagnetic scattering of a time-harmonic plane wave by an open cavity which is embedded in a perfectly electrically conducting infinite ground plane. This paper is concerned with the numerical solutions of the transverse electric and magnetic polarizations of the open cavity scattering problems. In each polarization, the scattering problem

Mohamed Lamine Abdelali, Noureddine Mebarki

A Universe containing uniform magnetic fields, strings, or domain walls is shown to have an ellipsoidal expansion. This case has motivations from observational cosmology especially the anomaly concerning the low quadrupole amplitude compared to the best-fit $Λ$CDM prediction in Planck data. It is shown that a Universe with eccentricity at decoupling of order

Ryan Darragh, Colin A. Z. Towery, Alexei Y. Poludnenko, Peter E. Hamlington

Turbulent mixing is a physical process of fundamental importance in high-speed premixed flames. This mixing results in enhanced transport of temperature and chemical scalars, leading to potentially large changes in flame structure and dynamics. To understand turbulent mixing in non-reacting flows, a number of classical theories have been proposed to describe

Soumyadeep Ghosh, Haranath Ghosh

Electron energy loss near edge spectra (ELNES) has been calculated for two different Fe based superconducting material FeSe and FeTe using density functional theory (DFT). Fe K-edge absorption spectra consist of several features, origins of which are thoroughly described in light of partial density of states of constituent atoms. Here we have included "c

Xiao-Bo Yan

Slow and fast light is an important and fascinating phenomenon in quantum optics. Here, we theoretically study how to achieve the ultraslow and ultrafast light in a passive-active optomechanical system, based on the ideal optomechanically induced transparency (OMIT). Under the conditions of the ideal OMIT, an abnormal (inverted) transparency window will emer

F. Baroni

In some recent papers some theorems on sufficiency conditions for the occurrence of a $\mathbb{Z}_2$-symmetry breaking phase transition ($\mathbb{Z}_2$-SBPT) have been showed making use of geometric-topological concepts of potential energy landscapes. In particular, a $\mathbb{Z}_2$-SBPT can be triggered by double-well potentials, or in an equivalent way, by

Mila Runnwerth, Markus Stocker, Sören Auer

The Open Research Knowledge Graph (ORKG) provides machine-actionable access to scholarly literature that habitually is written in prose. Following the FAIR principles, the ORKG makes traditional, human-coded knowledge findable, accessible, interoperable, and reusable in a structured manner in accordance with the Linked Open Data paradigm. At the moment, in O

Sercan Kazımoğlu, Erhan Deniz

In this paper our aim is to find the radii of starlikeness and convexity for three different kind of normalization of the $N_ν(z)=az^{2}J_{ν}^{\prime \prime }(z)+bzJ_{ν}^{\prime}(z)+cJ_{ν}(z)$ function, where $J_ν(z)$ is called the Bessel function of the first kind of order $ν.$ The key tools in the proof of our main results are the Mittag-Leffler expansion

Musaj Pacarizi, Arber Zeqiraj, Ibrahim Hameli, Isuf Tredhaku

In this paper, we present a new method to determine the numerical value of the Boltzmann constant k and its uncertainty. We have used Nitrogen gas in different pressure values in the range 56 kPa - 100 kPa, for three different volumes.In this experiment, we have used a simple idea called static expansion method, simple equipment, and simple equation for calc

Yongjin Lee

In this paper, we propose embedding sparsity into the structure of deep neural networks, where model parameters can be exactly zero during training with the stochastic gradient descent. Thus, it can learn the sparsified structure and the weights of networks simultaneously. The proposed approach can learn structured as well as unstructured sparsity.

Miguel Zambrano, Sintya Serrano, Boyan S. Lazarov, Juan Galvis

The goal of this work is to present a fast and viable approach for the numerical solution of the high-contrast state problems arising in topology optimization. The optimization process is iterative, and the gradients are obtained by an adjoint analysis, which requires the numerical solution of large high-contrast linear elastic problems with features spannin

Maneesh Bilalpur, Seyed Mostafa Kia, Mohan Kankanhalli, Ramanathan Subramanian

This work explores the utility of implicit behavioral cues, namely, Electroencephalogram (EEG) signals and eye movements for gender recognition (GR) and emotion recognition (ER) from psychophysical behavior. Specifically, the examined cues are acquired via low-cost, off-the-shelf sensors. 28 users (14 male) recognized emotions from unoccluded (no mask) and p

Jonathan Kernes, Alex J. Levine

The mechanics of lower dimensional elastic structures depends strongly on the geometry of their stress-free state. Elastic deformations separate into in-plane stretching and lower energy out-of-plane bending deformations. For elastic structures with a curved stress-free state, these two elastic modes are coupled within linear elasticity. We investigate the e

L. Santelli, P. Orlandi, R. Verzicco

In this study we have developed a flexible and efficient numerical scheme for the simulation of three-dimensional incompressible flows in spherical coordinates. The main idea, inspired by a similar strategy as (Verzicco, R., Orlandi, P., 1996, A Finite-Difference Scheme for Three-Dimensional Incompressible Flows in Cylindrical Coordinates) for cylindrical co

Brian M. de Silva, Jared Callaham, Jonathan Jonker, Nicholas Goebel

We develop data-driven algorithms to fully automate sensor fault detection in systems governed by underlying physics. The proposed machine learning method uses a time series of typical behavior to approximate the evolution of measurements of interest by a linear time-invariant system. Given additional data from related sensors, a Kalman observer is used to m

Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo

In recent years, convolutional neural networks have demonstrated promising performance in a variety of medical image segmentation tasks. However, when a trained segmentation model is deployed into the real clinical world, the model may not perform optimally. A major challenge is the potential poor-quality segmentations generated due to degraded image quality

Thiago Rateke, Aldo von Wangenheim

A challenge still to be overcome in the field of visual perception for vehicle and robotic navigation on heavily damaged and unpaved roads is the task of reliable path and obstacle detection. The vast majority of the researches have as scenario roads in good condition, from developed countries. These works cope with few situations of variation on the road su

Jan Bouwe van den Berg, Jean-Philippe Lessard, Elena Queirolo

In this paper we present a general approach to rigorously validate Hopf bifurcations as well as saddle-node bifurcations of periodic orbits in systems of ODEs. By a combination of analytic estimates and computer-assisted calculations, we follow solution curves of cycles through folds, checking along the way that a single nondegenerate saddle-node bifurcation

Nikita Tafintsev, Dmitri Moltchanov, Sergey Andreev, Shu-ping Yeh

Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public and civil applications, such as goods delivery, medicine, surveillance, and telecommunications. For the latter, UAVs with onboard communication equipment may help temporarily offload traffic onto the neighboring cells in fifth-generation networks and beyond (5G+). In this paper, we

Hussein Cheikh Ali

We consider the second best constant in the Hardy-Sobolev inequality on a Riemannian manifold. More precisely, we are interested with the existence of extremal functions for this inequality. This problem was tackled by Djadli-Druet [5] for Sobolev inequalities. Here, we establish the corresponding result for the singular case. In addition, we perform a blow-

Motoki Osada, Bai Yang Wang, Berit H. Goodge, Kyuho Lee

A variety of nickel oxide compounds have long been studied for their manifestation of various correlated electron phenomena. Recently, superconductivity was observed in nanoscale infinite layer nickelate thin films of Nd$_{0.8}$Sr$_{0.2}$NiO$_2$, epitaxially stabilized on SrTiO$_3$ substrates via topotactic reduction from the perovskite precursor phase. Here

Sunghan Kim

This paper is concerned with the nodal set of weak solutions to a broken quasilinear partial differential equation, \begin{equation*} \mbox{div} (a_+ \nabla u^+ - a_- \nabla u^-) = \mbox{div} f, \end{equation*} where $a_+$ and $a_-$ are uniformly elliptic, Dini continuous coefficient matrices, subject to a strong correlation that $a_+$ and $a_-$ are a multip

Md Whaiduzzaman, Md. Razon Hossain, Ahmedur Rahman Shovon, Shanto Roy

To slow down the spread of COVID-19, governments around the world are trying to identify infected people and to contain the virus by enforcing isolation and quarantine. However, it is difficult to trace people who came into contact with an infected person, which causes widespread community transmission and mass infection. To address this problem, we develop

Yuxiang Luo, Cheng Zhang, Yunqi Zhang, Chaoshun Zuo

In this paper, we propose a new privacy-preserving, automated contact tracing system, ACOUSTIC-TURF, to fight COVID-19 using acoustic signals sent from ubiquitous mobile devices. At a high level, ACOUSTIC-TURF adaptively broadcasts inaudible ultrasonic signals with randomly generated IDs in the vicinity. Simultaneously, the system receives other ultrasonic s

Florence Merlevède, Magda Peligrad, Costel Peligrad

In this paper we investigate the local limit theorem for additive functionals of a nonstationary Markov chain with finite or infinite second moment. The moment conditions are imposed on the individual summands and the weak dependence structure is expressed in terms of some uniformly mixing coefficients.

Jun Han Bae, Wonse Jo, Jee Hwan Park, Richard M. Voyles

Analysis of sediments from rivers, lakes, reservoirs, wetlands and other constructed surface water impoundments is an important tool to characterize the function and health of these systems, but is generally carried out manually. This is costly and can be hazardous and difficult for humans due to inaccessibility, contamination, or availability of required eq

M. Zhao, Pedro H. A. Anjos, J. Lowengrub, S. Li

The three-layer Saffman-Taylor problem introduces two coupled moving interfaces separating the three fluids. A very recent weakly nonlinear analysis of this problem in a radial Hele-Shaw cell setup has shown that the morphologies of the emerging fingering patterns strongly depend on the initial thickness of the intermediate layer connecting the two interface

Sandro Bettin, Dimitris Koukoulopoulos, Carlo Sanna

Given two sets of natural numbers $\mathcal{A}$ and $\mathcal{B}$ of natural density $1$ we prove that their product set $\mathcal{A}\cdot \mathcal{B}:=\{ab:a\in\mathcal{A},\,b\in\mathcal{B}\}$ also has natural density $1$. On the other hand, for any $\varepsilon>0$, we show there are sets $\mathcal{A}$ of density $>1-\varepsilon$ for which the product set $

Jaeyoon Kim

We study arithmetic functions $Φ(x;d,a)$, called prime running functions, whose value at $x$ sums the gaps between primes $p_k \equiv a\ (\text{mod}\ d)$ below $x$ and the next following prime $p_{k+1}$, up to $x$. (The following prime $p_{k+1}$ may be in any residue class $(\text{mod}\ d)$.) We empirically observe systematic biases of order $x / \log x$ in

Stephan van Schaik, Marina Minkin, Andrew Kwong, Daniel Genkin

Recent transient-execution attacks, such as RIDL, Fallout, and ZombieLoad, demonstrated that attackers can leak information while it transits through microarchitectural buffers. Named Microarchitectural Data Sampling (MDS) by Intel, these attacks are likened to "drinking from the firehose", as the attacker has little control over what data is observe

Roger Waleffe, Theodoros Rekatsinas

Recent works show that overparameterized networks contain small subnetworks that exhibit comparable accuracy to the full model when trained in isolation. These results highlight the potential to reduce training costs of deep neural networks without sacrificing generalization performance. However, existing approaches for finding these small networks rely on e

Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen

In multi-label classification, where the evaluation of predictions is less straightforward than in single-label classification, various meaningful, though different, loss functions have been proposed. Ideally, the learning algorithm should be customizable towards a specific choice of the performance measure. Modern implementations of boosting, most prominent

Preeti Kumari, Amine Mezghani, Robert W. Heath,

A fully-digital wideband joint communication-radar (JCR) with a multiple-input-multiple-output (MIMO) architecture at the millimeter-wave (mmWave) band will enable high joint communication and radar performance with enhanced design flexibility. A quantized receiver with few-bit analog-to-digital converters (ADCs) will enable a practical JCR solution with red

Kaili Vesik, Muhammad Abdul-Mageed, Miikka Silfverberg

The task of grapheme-to-phoneme (G2P) conversion is important for both speech recognition and synthesis. Similar to other speech and language processing tasks, in a scenario where only small-sized training data are available, learning G2P models is challenging. We describe a simple approach of exploiting model ensembles, based on multilingual Transformers an

Liliane Rodrigues de Almeida, Gilson A. Giraldi, Marcelo Bernardes Vieira

In the last decades, some literature appeared using the Lie groups theory to solve problems in computer vision. On the other hand, Lie algebraic representations of the transformations therein were introduced to overcome the difficulties behind group structure by mapping the transformation groups to linear spaces. In this paper we focus on application of Lie

Le Qiao, Gary W. Slater

Both the translational diffusion coefficient $D$ and the electrophoretic mobility $μ$ of a short rod-like molecule (such as dsDNA) that is being pulled towards a nanopore by an electric field should depend on its orientation. Since a charged rod-like molecule tends to orient in the presence of an inhomogeneous electric field, $D$ and $μ$ will change as the m

Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang

Graphs are ubiquitous in modelling relational structures. Recent endeavours in machine learning for graph-structured data have led to many architectures and learning algorithms. However, the graph used by these algorithms is often constructed based on inaccurate modelling assumptions and/or noisy data. As a result, it fails to represent the true relationship

Ian Leifer, Flaviano Morone, Saulo D. S. Reis, Jose S. Andrade

We show that logic computational circuits in gene regulatory networks arise from a fibration symmetry breaking in the network structure. From this idea we implement a constructive procedure that reveals a hierarchy of genetic circuits, ubiquitous across species, that are surprising analogues to the emblematic circuits of solid-state electronics: starting fro

Laureline Logiaco, G. Sean Escola

We study learning of recurrent neural networks that produce temporal sequences consisting of the concatenation of re-usable "motifs". In the context of neuroscience or robotics, these motifs would be the motor primitives from which complex behavior is generated. Given a known set of motifs, can a new motif be learned without affecting the performance

Hadi Rezaie Heris, Movaffaq Kateb, Sigurdur I. Erlingsson, Andrei Manolescu

We calculate the charge and heat current associate with electrons, generated by a temperature gradient and chemical potential difference between two ends of a tubular nanowire of 30 nm radius in the presence of an external magnetic field perpendicular to its axis. We consider a nanowire based on a semiconductor material, and use the Landauer-Bttiker approach

Victoria Yaneva, Le An Ha, Richard Evans, Ruslan Mitkov

When processing a text, humans and machines must disambiguate between different uses of the pronoun it, including non-referential, nominal anaphoric or clause anaphoric ones. In this paper, we use eye-tracking data to learn how humans perform this disambiguation. We use this knowledge to improve the automatic classification of it. We show that by using gaze

Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi

In this paper, we consider non-convex optimization problems under \textit{unknown} yet safety-critical constraints. Such problems naturally arise in a variety of domains including robotics, manufacturing, and medical procedures, where it is infeasible to know or identify all the constraints. Therefore, the parameter space should be explored in a conservative

Sujay Nair, Jonathan Varghese, Kalée Tock

The ability for citizen scientists to analyze image data and search for exoplanets using images from small telescopes has the potential to greatly accelerate the search for exoplanets. Recent work on the Exoplanet Transit Interpretation Code (EXOTIC) enables the generation of high-quality light curves of exoplanet transits given such image data. However, on

Mümün Can

In this paper, we introduce vast generalizations of the Hardy-Berndt sums. They involve higher-order Euler and/or Bernoulli functions, in which the variables are affected by certain linear shifts. By employing the Fourier series technique we derive linear relations for these sums. In particular, these relations yield reciprocity formulas for Carlitz, Rademac

Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang

Neural network-based approaches can achieve high accuracy in various medical image segmentation tasks. However, they generally require large labelled datasets for supervised learning. Acquiring and manually labelling a large medical dataset is expensive and sometimes impractical due to data sharing and privacy issues. In this work, we propose an adversarial

Gyorgy Csomos

In Hungary, the highest and most prestigious scientific qualification is considered to be the Doctor of Science (DSc) title being awarded by the Hungarian Academy of Sciences. The academic performance indicators of the DSc title are of high importance in the evaluation of individuals' research performance not only when a researcher applies for obtaining

Andrea Montessori, Marco Lauricella, Nicola Tirelli, Sauro Succi

We present a mesoscale kinetic model for multicomponent flows, augmented with a short range forcing term, aimed at describing the combined effect of surface tension and near-contact interactions operating at the fluid interface level. Such mesoscale approach is shown to i) accurately capture the complex dynamics of bouncing colliding droplets for different v

Robert Burduk

In the classification of a class imbalance dataset, the performance measure used for the model selection and comparison to competing methods is a major issue. In order to overcome this problem several performance measures are defined and analyzed in several perspectives regarding in particular the imbalance ratio. There is still no clear indication which met

Chen Cai, Yusu Wang

Graph Neural Networks (GNNs) have achieved a lot of success on graph-structured data. However, it is observed that the performance of graph neural networks does not improve as the number of layers increases. This effect, known as over-smoothing, has been analyzed mostly in linear cases. In this paper, we build upon previous results \cite{oono2019graph} to fu

Bartomeu Monserrat, Jan Gerit Brandenburg, Edgar A. Engel, Bingqing Cheng

We investigate the structural similarities between liquid water and 53 ices, including 20 knowncrystalline phases. We base such similarity comparison on the local environments that consist of atoms within a certain cutoff radius of a central atom. We reveal that liquid water explores the localenvironments of the diverse ice phases, by directly comparing the

Victor Asavei, Andrei A. Muller, Esther Sanabria-Codesal, Alin Moldoveanu

The article proves first that the constant quality factor (Q) contours for passive circuits, while represented on a 2D Smith chart, form circle arcs on a coaxal circle family. Furthermore, these circle arcs represent semi-circles families in the north hemisphere while represented on a 3D Smith chart. On the contrary we show that the constant Q contours for a

J. M. Joel Ong, Sarbani Basu

In the oscillation spectra of giant stars, nonradial modes may be seen to undergo avoided crossings, which produce a characteristic "mode bumping" of the otherwise uniform asymptotic p- and g-mode patterns in their respective echelle diagrams. Avoided crossings evolve very quickly relative to typical observational errors, and are therefore extremely

Jerry Li, Guanghao Ye

Robust covariance estimation is the following, well-studied problem in high dimensional statistics: given $N$ samples from a $d$-dimensional Gaussian $\mathcal{N}(\boldsymbol{0}, Σ)$, but where an $\varepsilon$-fraction of the samples have been arbitrarily corrupted, output $\widehatΣ$ minimizing the total variation distance between $\mathcal{N}(\boldsymbol{

M. Yu. Kagan, E. A. Mazur

The properties of a two-dimensional low density (n<<1) electron system with strong onsite Hubbard attraction U>W (W is the bandwidth) in the presence of a strong random potential V uniformly distributed in the range from -V to +V are considered. Electronic hoppings only at neighboring sites on the square lattice are taken into account, thus W=8t. The calcula

Martina T. Bevacqua, Tommaso Isernia

In this paper, a new inversion model for 2D microwave imaging is introduced by means of a convenient rewriting of the usual Lippmann Schwinger integral scattering equation. Such model is derived by decomposing the Greens function and the corresponding internal radiation operator in two different contributions. In fact, one of them can be easily computed from

Halid Ziya Yerebakan, Parmeet Bhatia, Yoshihisa Shinagawa

Pre-trained word embeddings are widely used for transfer learning in natural language processing. The embeddings are continuous and distributed representations of the words that preserve their similarities in compact Euclidean spaces. However, the dimensions of these spaces do not provide any clear interpretation. In this study, we have obtained supervised p

Namrata Vaswani

Phase retrieval (PR), also sometimes referred to as quadratic sensing, is a problem that occurs in numerous signal and image acquisition domains ranging from optics, X-ray crystallography, Fourier ptychography, sub-diffraction imaging, and astronomy. In each of these domains, the physics of the acquisition system dictates that only the magnitude (intensity)

Matthijs Ruijgrok

The Mean Field Approximation (MFA), or continuum method, is often used in courses on Networks to derive the degree distribution of preferential attachment networks. This method is simple and the outcome is close to the correct answer. However, this paper shows that the method is flawed in several aspects, leading to unresolvable contradictions. More importan

Konstantinos Georgiou, Somnath Kundu, Pawel Pralat

Let $G$ be a graph in which each vertex initially has weight 1. In each step, the unit weight from a vertex $u$ to a neighbouring vertex $v$ can be moved, provided that the weight on $v$ is at least as large as the weight on $u$. The unit acquisition number of $G$, denoted by $a_u(G)$, is the minimum cardinality of the set of vertices with positive weight at

Yafei Ren, Qiang Gao, A. H. MacDonald, Qian Niu

Graphene bilayers exhibit zero-energy flat bands at a discrete series of magic twist angles. In the absence of intra-sublattice inter-layer hopping, zero-energy states satisfy a Dirac equation with a non-abelian SU(2) gauge potential that cannot be diagonalized globally. We develop a semiclassical WKB approximation scheme for this Dirac equation by introduci

Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain

Unsupervised image-to-image translation consists of learning a pair of mappings between two domains without known pairwise correspondences between points. The current convention is to approach this task with cycle-consistent GANs: using a discriminator to encourage the generator to change the image to match the target domain, while training the generator to

Manuel Hinojosa-Rodriguez, Jose Oliver De Leo-Jimenez, Maria Elena Juarez-Colin, Eduardo Gonzalez-Moreira

Aim: To determine the long-term efficacy of Katona therapy and early rehabilitation of infants with moderate-to-severe perinatal brain damage (PBD). Methods: Thirty-two participants were recruited (7-to-16 years) and divided into 3 groups: one Healthy group (n = 11), one group with PBD treated with Katona methodology from 2 months of corrected age, and with

A. Danehkar

Local conformal symmetry introduces the conformal curvature (Weyl tensor) that gets split into its (gravito-) electric and magnetic (tensor) parts. Newtonian tidal forces are expected from the gravitoelectric field, whereas general-relativistic frame-dragging effects emerge from the gravitomagnetic field. The symmetric, traceless gravitoelectric and gravitom

Chao Zhang, Yuanwei Liu, Zhijin Qin, Zhiguo Ding

Grant-free (GF) transmission holds promise in terms of low latency communication by directly transmitting messages without waiting for any permissions. However, collision situations may frequently happen when limited spectrum is occupied by numerous GF users. The non-orthogonal multiple access (NOMA) technique can be a promising solution to achieve massive c

Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska

Filtering data based on predicates is one of the most fundamental operations for any modern data warehouse. Techniques to accelerate the execution of filter expressions include clustered indexes, specialized sort orders (e.g., Z-order), multi-dimensional indexes, and, for high selectivity queries, secondary indexes. However, these schemes are hard to tune an

Chixiang Chen, Ming Wang, Rongling Wu, Runze Li

Conventional likelihood-based information criteria for model selection rely on the distribution assumption of data. However, for complex data that are increasingly available in many scientific fields, the specification of their underlying distribution turns out to be challenging, and the existing criteria may be limited and are not general enough to handle a

Lorenz Eberhardt

We give an introduction to conformal and superconformal algebras and their representations in various dimensions. Special emphasis is put on 4d $\mathcal{N}=2$ superconformal symmetry. This is the writeup of the lectures given at the Winter School &#34;YRISW 2020&#34; to appear in a special issue of JPhysA.

Richard A. Battye, Apostolos Pilaftsis, Dominic G. Viatic

The Two Higgs Doublet Model predicts the emergence of 3 distinct domain wall solutions arising from the breaking of 3 accidental global symmetries, $Z_2$, CP1 and CP2, at the electroweak scale for specific choices of the model parameters. We present numerical kink solutions to the field equations in all three cases along with dynamical simulations of the mod

Sámuel G. Balogh, Gergely Palla, Péter Pollner, Dániel Czégel

The concept of entropy connects the number of possible configurations with the number of variables in large stochastic systems. Independent or weakly interacting variables render the number of configurations scale exponentially with the number of variables, making the Boltzmann-Gibbs-Shannon entropy extensive. In systems with strongly interacting variables,

Erion Çano, Ondřej Bojar

Automatic methods and metrics that assess various quality criteria of automatically generated texts are important for developing NLG systems because they produce repeatable results and allow for a fast development cycle. We present here an attempt to automate the evaluation of text naturalness which is a very important characteristic of natural language gene

Alëna Rodionova, Yash Vardhan Pant, Kuk Jang, Houssam Abbas

With increasing urban population, there is global interest in Urban Air Mobility (UAM), where hundreds of autonomous Unmanned Aircraft Systems (UAS) execute missions in the airspace above cities. Unlike traditional human-in-the-loop air traffic management, UAM requires decentralized autonomous approaches that scale for an order of magnitude higher aircraft d

Vinícius da Silva, Claudio Esperança, Ricardo Marroquim

Rendering large point clouds ordinarily requires building a hierarchical data structure for accessing the points that best represent the object for a given viewing frustum and level-of-detail. The building of such data structures frequently represents a large portion of the cost of the rendering pipeline both in terms of time and space complexity, especially

Nicole L. Vike, Sumra Bari, Khrystyna Stetsiv, Linda Papa

Recent research has shown there can be detrimental neurological effects of short- and long-term exposure to contact sports. In the present study, metabolomic profiling was combined with inflammatory miRNA quantification, computational behavior with virtual reality (VR) testing of motor control, and head collision event monitoring to explore trans-omic and co

D. S. Smirnov, T. S. Shamirzaev, D. R. Yakovlev, M. Bayer

We suggest a new spin orientation mechanism for localized electrons: $dynamic~electron~spin~polarization~provided~by~nuclear~spin~fluctuations$. The angular momentum for the electrons is gained from the nuclear spin system via the hyperfine interaction in a weak magnetic field. For this the sample is illuminated by an unpolarized light, which directly polari

Imon Banerjee, Priyanshu Sinha, Saptarshi Purkayastha, Nazanin Mashhaditafreshi

Purpose: Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the disease. To test the performance of the two top models for CXR COVID-19 diagnosis on external datasets to assess model generalizability. Methods: In this paper, we present our argu

Chao Zhang, Wenqiang Yi, Yuanwei Liu, Zhijin Qin

By activating blocked users and altering successive interference cancellation (SIC) sequences, reconfigurable intelligent surfaces (RISs) become promising for enhancing non-orthogonal multiple access (NOMA) systems. This work investigates the downlink performance of RIS-aided NOMA networks via stochastic geometry. We first introduce the unique path loss mode

Lana Yarosh, Suzanne Bakken, Alan Borning, Munmun De Choudhury

Substance Use Disorders (SUDs) involve the misuse of any or several of a wide array of substances, such as alcohol, opioids, marijuana, and methamphetamine. SUDs are characterized by an inability to decrease use despite severe social, economic, and health-related consequences to the individual. A 2017 national survey identified that 1 in 12 US adults have or

Shen Wang, Jibing Gong, Jinlong Wang, Wenzheng Feng

Massive open online courses are becoming a modish way for education, which provides a large-scale and open-access learning opportunity for students to grasp the knowledge. To attract students&#39; interest, the recommendation system is applied by MOOCs providers to recommend courses to students. However, as a course usually consists of a number of video lect

Trisha Ashley, Andrew J. Fox, Edward B. Jenkins, Bart P. Wakker

Using new ultraviolet (UV) spectra of five background quasars from the Cosmic Origins Spectrograph on the Hubble Space Telescope, we analyze the low-latitude (|b|=20-30 degree) regions of the Fermi Bubbles, the giant gamma-ray emitting lobes at the Galactic Center. We combine these data with previous UV and atomic hydrogen (HI) datasets to build a comprehens

Thao Nguyen, Nakul Gopalan, Roma Patel, Matt Corsaro

Natural language object retrieval is a highly useful yet challenging task for robots in human-centric environments. Previous work has primarily focused on commands specifying the desired object&#39;s type such as &#34;scissors&#34; and/or visual attributes such as &#34;red,&#34; thus limiting the robot to only known object classes. We develop a model to retr

Bence Racskó, László Árpád Gergely

We discuss junction conditions across null hypersurfaces in a class of scalar-tensor gravity theories with i) second order dynamics, ii) obeying the recent constraints imposed by gravitational wave propagation, and iii) allowing for a cosmologically viable evolution. These requirements select kinetic gravity braiding models with linear kinetic term dependenc

Josh Kirklin

We describe an explicit mechanism for the emergence of a dynamical holographic bulk from the structure of entanglement in a quantum state. We start with a generic system in complete isolation, assuming it has a classical limit involving coherent states. Then we entangle it with another system of that kind, and subject the pair to a decohering process. We mak

William P. Bowman, Gregory R. Zeimann, Gautam Nagaraj, Robin Ciardullo

We present MCSED, a new spectral energy distribution (SED)-fitting code, which mates flexible stellar evolution calculations with the Markov Chain Monte Carlo algorithms of the software package emcee. MCSED takes broad, intermediate, and narrow-band photometry, emission-line fluxes, and/or absorption line spectral indices, and returns probability distributio

Jurek Czyzowicz, Konstantinos Georgiou, Ryan Killick, Evangelos Kranakis

Assume that $m \geq 1$ autonomous mobile agents and $0 \leq b \leq m$ single-agent transportation devices (called {\em bikes}) are initially placed at the left endpoint $0$ of the unit interval $[0,1]$. The agents are identical in capability and can move at speed one. The bikes cannot move on their own, but any agent riding bike $i$ can move at speed $v_i >

Sankhadeep Bhattacharyya, Puneet Kumar Patra

We show numerically that including soft-sphere type collisions in the celebrated Fermi-Pasta-Ulam ($FPU$) chain completely alters the thermal transport characteristics. The resulting $FPU^C$ chains, while being momentum preserving, satisfy the Fourier&#39;s law and do not show anomalous thermal transport behavior. Collisions play a significant role in reduci

S. Andreon

It is not well understood whether the growth of early-type cluster galaxies proceeds inside-out, outside-in, or at the same pace at all radii. In this work we measured the galaxy size, defined by the radius including 80\% of the galaxy light, non-parametrically. We also determined a non-parametric estimate of galaxy light concentration, which measures the cu

C. Tortora, N. R. Napolitano, M. Radovich, C. Spiniello

Relic galaxies are thought to be the progenitors of high-redshift red nuggets that for some reason missed the channels of size growth and evolved passively and undisturbed since the first star formation burst (at $z>2$). These local ultracompact old galaxies are unique laboratories for studying the star formation processes at high redshift and thus the early

Gianluca Grignani, Troels Harmark, Marta Orselli, Andrea Placidi

We obtain a first order post-Minkowskian two-body effective potential whose post-Newtonian expansion directly reproduces the Einstein-Infeld-Hoffmann potential. Post-Minkowskian potentials can be extracted from on-shell scattering amplitudes in a quantum field theory of scalar matter coupled to gravity. Previously, such potentials did not reproduce the Einst

Shingo Hirano, Yusuke Tsukamoto, Shantanu Basu, Masahiro N. Machida

The formation of circumstellar disks is investigated using three-dimensional resistive magnetohydrodynamic simulations, in which the initial prestellar cloud has a misaligned rotation axis with respect to the magnetic field. We examine the effects of (i) the initial angle difference between the global magnetic field and the cloud rotation axis ($θ_0$) and (i

J. Bodensteiner, T. Shenar, H. Sana

About 20% of all B-type stars are classical Be stars. The Be phenomenon is strongly correlated with rapid rotation, the origin of which remains unclear. It may be rooted in single- or binary-star evolution. In the framework of the binary channel, the initially more massive star transfers mass and angular momentum to the original secondary, which becomes a Be