November 2019 arXiv papers — page 31

Jiaqi Yin

Various mixing conditions have been imposed on high dimensional time series, including the strong mixing ($\alpha$-mixing), maximal correlation coefficient ($\rho$-mixing), absolute regularity ($\beta$-mixing), and $\phi$-mixing. $\alpha$-mixing condition is a routine assumption when studying autoregression models. $\rho$-mixing can lead to $\alpha$-mixing.

Sara Pollock

In this paper, the Newton-Anderson method, which results from applying an extrapolation technique known as Anderson acceleration to Newton's method, is shown both analytically and numerically to provide superlinear convergence to non-simple roots of scalar equations. The method requires neither a priori knowledge of the multiplicities of the roots, nor compu

Mengyuan Zhang

We prove the existence theorem for basic elements in the quasi-projective case, extending results of Eisenbud-Evans and Bruns from the affine case. We give several geometric applications. For example, we show that every local complete intersection of pure codimension two in a smooth projective variety of dimension d over an infinite field is the degeneracy l

O. Njoya, T. Tsang, M. Tarka, W. Fairbank

Measurements of electron drift properties in liquid and gaseous xenon are reported. The electrons are generated by the photoelectric effect in a semi-transparent gold photocathode driven in transmission mode with a pulsed ultraviolet laser. The charges drift and diffuse in a small chamber at various electric fields and a fixed drift distance of 2.0 cm. At an

Sungbin Choi

This paper describes our UNet based deep convolutional neural network approach on the Traffic4cast challenge 2019. Challenges task is to predict future traffic flow volume, heading and speed on high resolution whole city map. We used UNet based deep convolutional neural network to train predictive model for the short term traffic forecast. On each convolutio

Aleksandr Beznosikov, Eduard Gorbunov, Alexander Gasnikov

In this paper, we propose a new method based on the Sliding Algorithm from Lan(2016, 2019) for the convex composite optimization problem that includes two terms: smooth one and non-smooth one. Our method uses the stochastic noised zeroth-order oracle for the non-smooth part and the first-order oracle for the smooth part. To the best of our knowledge, this is

María Victoria Cifuentes-Amado, Edilberto Cepeda-Cuervo

This paper proposes new linear regression models to deal with overdispersed binomial datasets. These new models, called tilted beta binomial regression models, are defined from the tilted beta binomial distribution, proposed assuming that the parameter of the binomial distribution follows a tilted beta distribution. As a particular case of this regression mo

Antonio Lei, Meng Fai Lim

Let $E$ be an elliptic curve defined over a number field $K$ where $p$ splits completely. Suppose that $E$ has good reduction at all primes above $p$. Generalizing previous works of Kobayashi and Sprung, we define multiply signed Selmer groups over the cyclotomic $\mathbb{Z}_p$-extension of a finite extension $F$ of $K$ where $p$ is unramified. Under the hyp

Linbin Huang, Huanhai Xin, Wei Dong, Florian Dörfler

Small-signal instability of grid-connected power converters may arise when the converters use a phase-locked loop (PLL) to synchronize with a weak grid. Commonly, this stability problem (referred as PLL-synchronization stability in this paper) was studied by employing a single-converter system connected to an infinite bus, which however, omits the impacts of

Shinji Kakinaka, Ken Umeno

The recent emergence of cryptocurrencies such as Bitcoin and Ethereum has posed possible alternatives to global payments as well as financial assets around the globe, making investors and financial regulators aware of the importance of modeling them correctly. The Levy's stable distribution is one of the attractive distributions that well describes the f

Bertrand Iooss, Clémentine Prieur

The global sensitivity analysis of a numerical model aims to quantify, by means of sensitivity indices estimate, the contributions of each uncertain input variable to the model output uncertainty. The so-called Sobol' indices, which are based on the functional variance analysis, present a difficult interpretation in the presence of statistical dependence

Matthew Alexander, Matthieu Fradelizi, Luis C. García-Lirola, Artem Zvavitch

The goal of this paper is to study geometric and extremal properties of the convex body $B_{\mathcal F(M)}$, which is the unit ball of the Lipschitz-free Banach space associated with a finite metric space $M$. We investigate $\ell_1$ and $\ell_\infty$-sums, in particular we characterize the metric spaces such that $B_{\mathcal F(M)}$ is a Hanner polytope. We

Bharathan Balaji, Jordan Bell-Masterson, Enes Bilgin, Andreas Damianou

Reinforcement Learning (RL) has achieved state-of-the-art results in domains such as robotics and games. We build on this previous work by applying RL algorithms to a selection of canonical online stochastic optimization problems with a range of practical applications: Bin Packing, Newsvendor, and Vehicle Routing. While there is a nascent literature that app

Aria Khademi, Vasant Honavar

ProPublica's analysis of recidivism predictions produced by Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) software tool for the task, has shown that the predictions were racially biased against African American defendants. We analyze the COMPAS data using a causal reformulation of the underlying algorithmic fairness problem. S

Alan Adolphson, Steven Sperber

We return to some past studies of hyperkloosterman sums ([9,10]) via $p$-adic cohomology with an aim to improve earlier results. In particular, we work here with Dwork's $\theta_\infty$-splitting function and a better choice of basis for cohomology. To a large extent, we are guided to this choice of basis by our recent work on the $p$-integrality of coeffici

Kathryn F. Neugent, Philip Massey, Cyril Georgy, Maria R. Drout

The mass-loss rates of red supergiant stars (RSGs) are poorly constrained by direct measurements, and yet the subsequent evolution of these stars depends critically on how much mass is lost during the RSG phase. In 2012 the Geneva evolutionary group updated their mass-loss prescription for RSGs with the result that a 20 solar mass star now loses 10x more mas

Patrick Leu, Ivan Puddu, Aanjhan Ranganathan, Srdjan Capkun

Low-power wide area networks (LPWANs), such as LoRa, are fast emerging as the preferred networking technology for large-scale Internet of Things deployments (e.g., smart cities). Due to long communication range and ultra low power consumption, LPWAN-enabled sensors are today being deployed in a variety of application scenarios where sensitive information is

Vincenzo Liguori

This paper discusses three basic blocks for the inference of convolutional neural networks (CNNs). Pyramid Vector Quantization (PVQ) is discussed as an effective quantizer for CNNs weights resulting in highly sparse and compressible networks. Properties of PVQ are exploited for the elimination of multipliers during inference while maintaining high performanc

Touria Karite, Ali Boutoulout, Delfim F. M. Torres

We investigate the exact enlarged controllability and optimal control of a fractional diffusion equation in Caputo sense. This is done through a new definition of enlarged controllability that allows us to extend available contributions. Moreover, the problem is studied using two approaches: a reverse Hilbert uniqueness method, generalizing the approach intr

Kaiqing Zhang, Zhuoran Yang, Tamer Başar

Recent years have witnessed significant advances in reinforcement learning (RL), which has registered great success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, involve the participation of more than one single agent, whic

Alexander Kalmynin

For $0\leq \alpha<1$ and prime number $p$ let $L(\alpha,p)$ be the sum of the first $[\alpha p]$ values of Legendre symbol modulo $p$. We study positivity of $L(\alpha,p)$ and prove that for $|\alpha-\frac13|<2\cdot 10^{-6}$ and for rational $\alpha\leq \frac12$ with denominators in the set $\{1,2,3,4,5,6,8,12\}$ the inequality $L(\alpha,p)\geq 0$ holds for

Guoping Long, Jun Yang, Wei Lin

Performance optimization is the art of continuous seeking a harmonious mapping between the application domain and hardware. Recent years have witnessed a surge of deep learning (DL) applications in industry. Conventional wisdom for optimizing such workloads mainly focus on compute intensive ops (GEMM, Convolution, etc). Yet we show in this work, that the per

Leonhard Held

Statistical methodology plays a crucial role in drug regulation. Decisions by the FDA or EMA are typically made based on multiple primary studies testing the same medical product, where the two-trials rule is the standard requirement, despite a number of shortcomings. A new approach is proposed for this task based on the (weighted) harmonic mean of the squar

A. G. Kozlov, A. G. Kolesnikov, M. E. Stebliy, A. V. Davydenko

Determination of the energy of Dzyaloshinskii-Moriya interaction along with a definition of the basic magnetic characteristics in ferromagnetic/nonmagnetic multilayered systems are both required for the construction of a magnetic skyrmion recording medium. A method for estimating the energy of the effective Dzyaloshinskii-Moriya interaction which compared th

Matthieu Jaquier, Raoul Röntsch

We study the production of a mixed scalar-pseudoscalar Higgs boson in gluon fusion at the LHC, through next-to-next-to-leading order (NNLO) in QCD. We obtain fully differential results, including the decay of the Higgs boson to two charged lepton pairs. We discuss the impact of the interference between the scalar and pseudoscalar states. We also show differe

Hsin-Yu Ko, Junteng Jia, Biswajit Santra, Xifan Wu

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semi-local density functional theory (DFT), and thereby furnish a more accurate and reliable description of the electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated

Ashish Verma, Ankush Goyal, Davinderjit Kaur

Nowadays, there are many fatigue detection methods and the majority of them are tracking eye in real-time using one or two cameras to detect the physical responses in eyes. It is indicated that the responses in eyes have high relativity with driver fatigue. As part of this project, We will propose a fatigue detection system based on pose estimation. Using po

Alfredo Roque Freire

We consider the foundational relation between arithmetic and set theory. Our goal is to criticize the construction of standard arithmetic models as providing grounds for arithmetic truth (even in a relative sense). Our method is to emphasize the incomplete picture of both theories and treat models as their syntactical counterparts. Insisting on the incomplet

Mihir Kulkarni, Huan Nguyen, Kostas Alexis

This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that simultaneously presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potential of dis

Oswaldo Lezama, Helbert Venegas

Let $A$ be a right Ore domain, $Z(A)$ be the center of $A$ and $Q_r(A)$ be the right total ring of fractions of $A$. If $K$ is a field and $A$ is a $K$-algebra, in this short paper we prove that if $A$ is finitely generated and ${\rm GKdim}(A)<{\rm GKdim}(Z(A))+1$, then $Z(Q_r(A))\cong Q(Z(A))$. Many examples that illustrate the theorem are included, most of

Gregory Lupton, Samuel Bruce Smith

Let $X$ be a simply connected space with finite-dimensional rational homotopy groups. Let $p_\infty \colon UE \to \mathrm{Baut}_1(X)$ be the universal fibration of simply connected spaces with fibre $X$. We give a DG Lie model for the evaluation map $ \omega \colon \mathrm{aut}_1(\mathrm{Baut}_1(X_{\mathbb Q})) \to \mathrm{Baut}_1(X_{\mathbb Q})$ expressed i

Zakhar Kabluchko, Matthias Löwe, Kristina Schubert

We continue our analysis of Ising models on the (directed) Erd\H{o}s-R\'enyi random graph. This graph is constructed on $N$ vertices and every edge has probability $p$ to be present. These models were introduced by Bovier and Gayrard [J. Stat. Phys., 1993] and analyzed by the authors in a previous note, in which we consider the case of $p=p(N)$ satisfying $p

İlker Gençtürk

In this paper, we introduce a new type of $ pq $-calculus. The $ pq $-derivative and $ pq $-integration are investigated and various properties of these concepts are given. The fundamental theorem of $ pq $-calculus and formulas of $ pq $-integration by part are also presented.

Catarina Cosme

We introduce an oscillating scalar field coupled to the Higgs that can account for all dark matter in the Universe. Due to an underlying scale invariance of this model, the dark scalar only acquires mass after the electroweak phase transition. We discuss the dynamics of this dark matter candidate, showing that it behaves like dark radiation until the Electro

Samet Demir, Hasan Ferit Eniser, Alper Sen

Testing Deep Neural Network (DNN) models has become more important than ever with the increasing usage of DNN models in safety-critical domains such as autonomous cars. The traditional approach of testing DNNs is to create a test set, which is a random subset of the dataset about the problem of interest. This kind of approach is not enough for testing most o

Raghunathan Ramakrishnan

Many-electron wavepacket dynamics based on time-dependent configuration interaction (TDCI) is a numerically rigorous approach to quantitatively model electron-transfer across molecular junctions. TDCI simulations of cyanobenzene thiolates---para- and meta-linked to an acceptor gold atom---show donor states \emph{conjugating} with the benzene $\pi$-network to

Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li

The computing wall and data movement challenges of deep neural networks (DNNs) have exposed the limitations of conventional CMOS-based DNN accelerators. Furthermore, the deep structure and large model size will make DNNs prohibitive to embedded systems and IoT devices, where low power consumption are required. To address these challenges, spin orbit torque m

A. V. Bibikov, G. Ya. Korenman, S. N. Yudin

Collisions of metastable antiprotonic helium atoms with atoms of the medium induce, among other processes, transitions between hyperfine structure (HFS) states, as well as shifts and broadening of microwave M1 spectral lines. In order to obtain matrix potential of interaction between $(\mathrm{\bar{p} He} ^+)$ and $\mathrm{He}$, we have calculated the potent

Mohamed Tahar Kadaoui Abbassi, Noura Amri

Considering pseudo-Riemannian $g$-natural metrics on tangent bundles, we prove that the condition of being Ricci soliton is hereditary in the sense that a Ricci soliton structure on the tangent bundle gives rise to a Ricci soliton structure on the base manifold. Restricting ourselves to some class of pseudo-Riemannian $g$-natural metrics, we show that the ta

Claas Flint, Katharina Förster, Sophie A. Koser, Carsten Konrad

Transgender individuals (TIs) show brain structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of $N

Noujan Pashanasangi, C. Seshadhri

Subgraph counting is a fundamental task in network analysis. Typically, algorithmic work is on total counting, where we wish to count the total frequency of a (small) pattern subgraph in a large input data set. But many applications require local counts (also called vertex orbit counts) wherein, for every vertex $v$ of the input graph, one needs the count of

Géraud Delport, Stuart Macpherson, Samuel D. Stranks

Halide perovskites have remarkable properties for relatively crudely processed semiconductors, including large optical absorption coefficients and long charge carrier lifetimes. Thanks to such properties, these materials are now competing with established technologies for use in cost-effective and efficient light harvesting and light emitting devices. Nevert

Yihui He, Jianren Wang

Mistakes/uncertainties in object detection could lead to catastrophes when deploying robots in the real world. In this paper, we measure the uncertainties of object localization to minimize this kind of risk. Uncertainties emerge upon challenging cases like occlusion. The bounding box borders of an occluded object can have multiple plausible configurations.

Jeonghun J. Lee

In this paper we present new stability and optimal error analyses of hybridized discontinuous Galerkin (HDG) methods which do not require elliptic regularity assumptions. To obtain error estimates without elliptic regularity assumptions, we use new inf-sup conditions based on stabilized saddle point structures of HDG methods. We show that this approach can b

Parvej Reja Saleh, Debasish Hazarika, Ajaz Ahmad Dar, Padmakar Singh Parihar

A rarely studied open cluster, King 1 is observed using the 1.3m telescope equipped with 2k x 4k CCD at the Vainu Bappu Observatory, India. We analyse the photometric data obtained from the CCD observations in both B and V bands. Out of 132 detected stars in the open cluster King 1 field, we have identified 4 stellar variables and 2 among them are reported a

T. Guillet, C. Zucchetti, A. Marchionni, A. Hallal

Topological insulators (TIs) hold great promises for new spin-related phenomena and applications thanks to the spin texture of their surface states. However, a versatile platform allowing for the exploitation of these assets is still lacking due to the difficult integration of these materials with the mainstream Si-based technology. Here, we exploit germaniu

Sergey Bereg, Oscar Chacón-Rivera, David Flores-Peñaloza, Clemens Huemer

Huemer et al. (Discrete Mathematics, 2019) proved that for any two point sets $R$ and $B$ with $|R|=|B|$, the perfect matching that matches points of $R$ with points of $B$, and maximizes the total \emph{squared} Euclidean distance of the matched pairs, verifies that all the disks induced by the matching have a common point. Each pair of matched points $p\in

F. Skara, L. Perivolaropoulos

The $E_G$ statistic is a powerful probe for detecting deviations from GR by combining weak lensing (WL), real-space clustering and redshift space distortion (RSD) measurements thus probing both the lensing and the growth effective Newton constants ($G_L$ and $G_{eff}$). We construct an up to date compilation of $E_G$ statistic data including both redshift an

Manpreet Singh Minhas, John Zelek

Humans can easily detect a defect (anomaly) because it is different or salient when compared to the surface it resides on. Today, manual human visual inspection is still the norm because it is difficult to automate anomaly detection. Neural networks are a useful tool that can teach a machine to find defects. However, they require a lot of training examples t

Patrik Christen, Olivier Del Fabbro

As a discipline cybernetics has a long and rich history. In its first generation it not only had a worldwide span, in the area of computer modelling, for example, its proponents such as John von Neumann, Stanislaw Ulam, Warren McCulloch and Walter Pitts, also came up with models and methods such as cellular automata and artificial neural networks, which are

Stephen L. Adler

In earlier work we analyzed an abelianized model in which a gauged Rarita-Schwinger spin-$\frac{3}{2}$ field is directly coupled to a spin-$\frac{1}{2}$ field. Here we extend this analysis to the gauged $SU(8)$ model for which the abelianized model was a simplified substitute. We calculate the gauge anomaly, show that anomaly cancellation requires adding an

Kan Li, Jose C. Principe

We present a general nonlinear Bayesian filter for high-dimensional state estimation using the theory of reproducing kernel Hilbert space (RKHS). Applying kernel method and the representer theorem to perform linear quadratic estimation in a functional space, we derive a Bayesian recursive state estimator for a general nonlinear dynamical system in the origin

Christopher Rentsch

Spectroscopic measurements at top of atmosphere are uniquely capable of attributing changes in Earth's outgoing infrared radiation field to specific greenhouse gasses. The Atmospheric Infrared Sounder (AIRS) placed in orbit in 2002 has spectroscopically resolved a portion of Earth's outgoing longwave radiation for over 17 years. Concurrently, atmospheric CO$

Rong Ma, T. Tony Cai, Hongzhe Li

Motivated by recent research on quantifying bacterial growth dynamics based on genome assemblies, we consider a permuted monotone matrix model $Y=\Theta\Pi+Z$, where the rows represent different samples, the columns represent contigs in genome assemblies and the elements represent log-read counts after preprocessing steps and Guanine-Cytosine (GC) adjustment

Yuehan Yao, Christian Machado, Youhua Jiang, Emma Feldman

Hydrophobic (HPo) surfaces for atmospheric water harvesting applications require sophisticated wettability and microstructure patterns, which suffer from high cost and low durability against severe mechanical and environmental degradations. Inspired by the leaves of Welwitschia mirabilis, a long lifespan desert-living plant, we present a robust superhydrophi

Yue Bai, Lichen Wang, Zhiqiang Tao, Sheng Li

Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on fusing multi-view information at an early stage, e.g., by learning a common feature subspace among multiple views. However, these early fusion methods may not fully exploit the uniq

David Gomez-Ullate, Yves Grandati, Robert Milson

Exceptional orthogonal polynomials are complete families of orthogonal polynomials that arise as eigenfunctions of a Sturm-Liouville problem. Antonio Dur\'an discovered a gap in the original proof of completeness for exceptional Hermite polynomials, that has propagated to analogous results for other exceptional families. In this paper we provide an alternati

Alexander Tschantz, Manuel Baltieri, Anil. K. Seth, Christopher L. Buckley

In reinforcement learning (RL), agents often operate in partially observed and uncertain environments. Model-based RL suggests that this is best achieved by learning and exploiting a probabilistic model of the world. 'Active inference' is an emerging normative framework in cognitive and computational neuroscience that offers a unifying account of how biologi

Sameeksha Katoch, Kowshik Thopalli, Jayaraman J. Thiagarajan, Pavan Turaga

Exploiting known semantic relationships between fine-grained tasks is critical to the success of recent model agnostic approaches. These approaches often rely on meta-optimization to make a model robust to systematic task or domain shifts. However, in practice, the performance of these methods can suffer, when there are no coherent semantic relationships bet

Erik Norlander, Alexandros Sopasakis

We propose a new type of variational autoencoder to perform improved pre-processing for clustering and anomaly detection on data with a given label. Anomalies however are not known or labeled. We call our method conditional latent space variational autonencoder since it separates the latent space by conditioning on information within the data. The method fit

Nicola Dalla Pozza, Stefano Gherardini, Matthias M. Müller, Filippo Caruso

The success of quantum noise sensing methods depends on the optimal interplay between properly designed control pulses and statistically informative measurement data on a specific quantum-probe observable. To enhance the information content of the data and reduce as much as possible the number of measurements on the probe, the filter orthogonalization method

Katherine D. Rainey, Bethany R. Wilcox

Thermal physics is a core course requirement for most physics degrees and encompasses both thermodynamics and statistical mechanics content. However, the primary content foci of thermal physics courses vary across universities. This variation can make creation of materials or assessment tools for thermal physics difficult. To determine the scope and content

M. A. Andreichikov, M. I. Eides, V. A. Novikov, M. I. Vysotsky

An approach to the properties of the $\eta$--$\eta'$ system developed to solve the famous $U(1)$ problem is used to calculate the partial widths ratios to $\eta$ and $\eta'$ in the $B^0 \rightarrow J/\Psi \ \eta(\eta',\ \pi^0)$ and $B_s \rightarrow J/\Psi \ \eta(\eta')$ decays. We obtain the results in agreement with the experimental data.

Gil Alon, Elad Paran

We prove a Nullstellensatz for the ring of polynomial functions in n non-commuting variables over Hamilton's ring of real quaternions. We also characterize the generalized polynomial identities in n variables which hold over the quaternions, and more generally, over any division algebra.

Dipan K. Pal, Sreena Nallamothu, Marios Savvides

We propose the first qualitative hypothesis characterizing the behavior of visual transformation based self-supervision, called the VTSS hypothesis. Given a dataset upon which a self-supervised task is performed while predicting instantiations of a transformation, the hypothesis states that if the predicted instantiations of the transformations are already p

Panayotis Smyrnelis

The extended Painlev\'e P.D.E. system $\Delta y -x_1 y - 2 |y|^2y=0$, $(x_1,\ldots,x_n)\in \mathbb{R}^n$, $y:\mathbb{R}^n\to\mathbb{R}^m$, is obtained by multiplying by $-x_1$ the linear term of the Ginzburg-Landau equation $\Delta \eta=|\eta|^2\eta-\eta$, $\eta:\mathbb{R}^{n}\to\mathbb{R}^{m}$. The two dimensional model $n=m=2$ describes in the theory of li

Hongming Yi, Adam J. Fleisher

Reported here are portions of the infrared absorption cross-section for methanol (CH$_3$OH) as measured by frequency-stabilized cavity ring-down spectroscopy (FS-CRDS) at wavelengths near $\lambda$ = 2.0 $\mu$m. High-resolution spectra of two gravimetric mixtures of CH$_3$OH-in-air with nominal mole fractions of 202.2 $\mu$mol/mol and 45.89 $\mu$mol/mol, res

Fanny Augeri, Alice Guionnet, Jonathan Husson

We establish large deviations estimates for the largest eigenvalue of Wigner matrices with sub-Gaussian entries. Under technical assumptions, we show that the large deviation behavior of the largest eigenvalue is universal for small deviations, in the sense that the speed and the rate function are the same as in the case of the GOE. In contrast, in the regim

Jean-Louis Verger-Gaugry

The Conjecture of Lehmer is proved to be true. The proof mainly relies upon: (i) the properties of the Parry Upper functions $f_{\house{\alpha}}(z)$ associated with the dynamical zeta functions $\zeta_{\house{\alpha}}(z)$ of the R\'enyi--Parry arithmetical dynamical systems ($\beta$-shift), for $\alpha$ a reciprocal algebraic integer of house $\house{\alpha}

W. Krzemien, E. Perez del Rio, Krzysztof Kacprzak

We discuss the possibility to perform the experimental searches of invisible decays in the ortho-positronium system with the J-PET detector

B. Rezaei, G. R. Boroun

We present a set of formulas to extract the ratio $F_{L}(x,Q^{2})/F_{2}(x,Q^{2})$ and $R(x,Q^{2})$ from the proton structure function parameterized in the next-to-next-to-leading order of the perturbative theory at low $x$ values. The behavior of these ratios are considered with respect to the power-law behavior of the proton structure function. The results

Manizheh Botshekananfard, Ehsan Bavarsad

We compute the expectation value of the energy-momentum tensor in the in-vacuum state of the quantized Dirac field coupled to a uniform electric field background on the Poincar$\rm\acute{e}$ path of the two dimensional de~Sitter spacetime ($\mathrm{dS}_{2}$). The adiabatic regularization scheme is applied to remove the ultraviolet divergencies from the expre

B. Rezaei, G. R. Boroun

The behavior of the gluon distribution function and the reduced cross section considered from the proton structure function and its derivatives at low values of $x$. These behaviors studied and compared with the experimental data. These results are augmented by including an additional higher-twist term in the description of the nonlinear correction. This add

Lorenzo Traldi

Joyce observed that the Alexander invariant and the medial quandle of a classical knot are equivalent to each other, as invariants. In the present paper, we discuss the rather complicated extension of Joyce's observation to several different medial quandles and reduced (one-variable) Alexander modules associated with classical links. The theme is that for li

E. V. Krishnan, M. Al Ghabshi, M. Alquran

This paper deals with the exact solutions of a nonlinear coupled coupled wave equation. The (G'/G)-expansion method has been applied to derive kink solutions and singular wave solutions. The restrictions on the coefficients of the governing equations have also been investigated. Solitary wave solutions have also been derived for this system of equations usin

Brianna Lacy, Adam Burrows

In this work, we investigate the properties of young giant planet spectra in the optical and suggest that future space-based direct imaging missions should be considering young planets as a valuable and informative science case. While young planets are dimmer in the optical than in the infrared, they can still be brighter in the optical than a mature planet

Aayush Jha, Ashim B. Karki

In this paper, we overlay a continuum of analytical relations which essentially serve to compute the arc-length described by a celestial body in an elliptic orbit within a stipulated time interval. The formalism is based upon a two-dimensional heliocentric coordinate frame, where both the coordinates are parameterized as two infinitely differentiable functio

N. V. Ustinov

The solutions of the two-dimensional multicomponent Yajima-Oikawa system that have the functional arbitrariness are constructed by using the Darboux transformation technique. For the zero and constant backgrounds, different types of solutions of this system, including the lumps, line rogue waves, semi-rational solutions and their higher-order counterparts, a

Piotr T. Grochowski, Tomasz Karpiuk, Mirosław Brewczyk, Kazimierz Rzążewski

By analyzing breathing mode of a Bose-Einstein condensate repulsively interacting with a polarized fermionic cloud, we further the understanding of a Bose-Fermi mixture recently realized by Lous et al. [\textit{Phys. Rev. Lett.} \textbf{120}, 243403]. We show that a hydrodynamic description of a domain wall between bosonic and fermionic atoms reproduces expe

Filippos Kokkinos, Ioannis Marras, Matteo Maggioni, Gregory Slabaugh

State-of-the-art methods for computer vision rely heavily on the translation equivariance and spatial sharing properties of convolutional layers without explicitly taking into consideration the input content. Modern techniques employ deep sophisticated architectures in order to circumvent this issue. In this work, we propose a Pixel Adaptive Filtering Unit (

Valentin Vengerovsky

We study asymptotic behaviour of the correlation functions of bipartite sparse random $N\times N$ matrices. We assume that the graphs have $N$ vertices, the ratio of parts is $\displaystyle\frac{\alpha}{1-\alpha}$ and the average number of edges attached to one vertex is $\alpha\cdot p$ or $(1-\alpha)\cdot p$. To each edge of the graph $e_{ij}$ we assign a w

Esty Kelman, Guy Kindler, Noam Lifshitz, Dor Minzer

The total influence of a function is a central notion in analysis of Boolean functions, and characterizing functions that have small total influence is one of the most fundamental questions associated with it. The KKL theorem and the Friedgut junta theorem give a strong characterization of such functions whenever the bound on the total influence is $o(\log n

Konstantin Yakovlev, Anton Andreychuk, Vitaly Vorobyev

Methods for centralized planning of the collision-free trajectories for a fleet of mobile robots typically solve the discretized version of the problem and rely on numerous simplifying assumptions, e.g. moves of uniform duration, cardinal only translations, equal speed and size of the robots etc., thus the resultant plans can not always be directly executed

Gabriel Picavet, Martine Picavet-L'Hermitte

If $R\subseteq S$ is a ring extension of commutative unital rings, the poset $[R,S]$ of $R$-subalgebras of $S$ is called catenarian if it verifies the Jordan-H\"older property. This property has already been studied by Dobbs and Shapiro for finite extensions of fields. We investigate this property for arbitrary ring extensions, showing that many type of exte

Yongzhe Yan, Stefan Duffner, Priyanka Phutane, Anthony Berthelier

We present a facial landmark position correlation analysis as well as its applications. Although numerous facial landmark detection methods have been presented in the literature, few of them explicitly take into account the inherent relationship among landmarks. To reveal and interpret this relationship, we propose to analyze landmark correlation by using Ca

Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Mohamed Shawky

Data scarcity is a bottleneck to machine learning-based perception modules, usually tackled by augmenting real data with synthetic data from simulators. Realistic models of the vehicle perception sensors are hard to formulate in closed form, and at the same time, they require the existence of paired data to be learned. In this work, we propose two unsupervis

N. Amburg, H. Itoyama, A. Mironov, A. Morozov

A novel functorial relationship in perturbative quantum field theory is pointed out that associates Feynman diagrams (FD) having no external line in one theory ${\bf Th}_1$ with singlet operators in another one ${\bf Th}_2$ having an additional $U({\cal N})$ symmetry and is illustrated by the case where ${\bf Th}_1$ and ${\bf Th}_2$ are respectively the rank

Hanyuan Hang

We investigate an algorithm named histogram transform ensembles (HTE) density estimator whose effectiveness is supported by both solid theoretical analysis and significant experimental performance. On the theoretical side, by decomposing the error term into approximation error and estimation error, we are able to conduct the following analysis: First of all,

M. O. Katanaev

The global conformal gauge is playing the crucial role in string theory providing the basis for quantization. Its existence for two-dimensional Lorentzian metric is known locally for a long time. We prove that if a Lorentzian metric is given on a plain then the conformal gauge exists globally on the whole ${\mathbb R}^2$. Moreover, we prove the existence of

Jean-Christophe Bourin, Eun-Young Lee

We revisit a classical result, the Russo-Dye Theorem, stating that every positive linear map attains its norm at the identity.

Yongzhe Yan, Stefan Duffner, Priyanka Phutane, Anthony Berthelier

The recent performance of facial landmark detection has been significantly improved by using deep Convolutional Neural Networks (CNNs), especially the Heatmap Regression Models (HRMs). Although their performance on common benchmark datasets has reached a high level, the robustness of these models still remains a challenging problem in the practical use under

Felix Biessmann, Dionysius Irza Refiano

The field of transparent Machine Learning (ML) has contributed many novel methods aiming at better interpretability for computer vision and ML models in general. But how useful the explanations provided by transparent ML methods are for humans remains difficult to assess. Most studies evaluate interpretability in qualitative comparisons, they use experimenta

Christopher A. Bowers, Cass T. Miller

Single fluid porous medium systems are typically modeled at an averaged length scale termed the macroscale using Darcy's law. Standard approaches for modeling macroscale single fluid phase flow of non-Newtonian fluids extend Darcy's law, using an effective viscosity and assuming that the permeability is invariant. This approach results in a need to determine

Brendan P. Bowler, Sarah C. Blunt, Eric L. Nielsen

The orbital eccentricities of directly imaged exoplanets and brown dwarf companions provide clues about their formation and dynamical histories. We combine new high-contrast imaging observations of substellar companions obtained primarily with Keck/NIRC2 together with astrometry from the literature to test for differences in the population-level eccentricity

F. Judee, J. Vaquero, L. Fouassier, T. Dufour

Atmospheric pressure plasma jets (APPJ) are investigated as an efficient approach to induce antitumor effects of cancerous tissues without inducing any damage (e.g. dessication, burnings). For this, a two-steps methodology has been developed where first APPJ are calibrated and characterized on targets mimicking electrical properties of living organisms (mice

F. Judée, J. Vaquero, S. Guégan, L. Fouassier

Two atmospheric pressure plasma jet devices - a plasma gun and a plasma Tesla jet - are compared in terms of safety and therapeutic efficiency to reduce the tumor volume progression of cholangiocarcinoma, i.e. a rare and very aggressive cancer emerging in biliary tree. For this, a three steps methodology is carried out. First, the two APPJ have been benchmar

Fu-Zhao Ou, Yuan-Gen Wang, Jin Li, Guopu Zhu

No-reference image quality assessment (NR-IQA) has received increasing attention in the IQA community since reference image is not always available. Real-world images generally suffer from various types of distortion. Unfortunately, existing NR-IQA methods do not work with all types of distortion. It is a challenging task to develop universal NR-IQA that has

Florian Judée, Thierry Dufour

Simulations and experimental works have been carried out in a complementary way to engineer a basic material target mimicking the same dielectric properties of the human body. It includes a resistor in parallel with a capacitor, whose values (Rh=1500 {\Omega} and Ch=100 pF) are estimated in regard of parameters commonly utilized upon in vivo campaigns (frequ

Shiqiang Zhang, Thierry Dufour

A pin liquid anode DC discharge is generated in open air without any additional gas feeding to form self-organized patterns (SOPs) on various liquid interfaces. Axially resolved emission spectra of the whole discharge reveal that the self-organized patterns are formed below a dark region and are visible mainly due to the N2 transitions. The high energy N2 (C

Mrinank Sharma, Michael Hutchinson, Siddharth Swaroop, Antti Honkela

In many real-world applications of machine learning, data are distributed across many clients and cannot leave the devices they are stored on. Furthermore, each client's data, computational resources and communication constraints may be very different. This setting is known as federated learning, in which privacy is a key concern. Differential privacy is com