November 2018 arXiv papers — page 89

Xiaobin Sun, Jianliang Zhai

In this paper, we study a system of stochastic partial differential equations with slow and fast time-scales, where the slow component is a stochastic real Ginzburg-Landau equation and the fast component is a stochastic reaction-diffusion equation, the system is driven by $α$-stable process with $α\in (1,2)$. Using the classical Khasminskii approach based on

Petar Bakic

We determine the occurrence and explicitly describe the theta lifts on all levels of all the irreducible generic representations for the dual pair of groups $(\mathrm{Sp}_{2n}, \mathrm{O}(V))$ defined over a local nonarchimedean field $\mathbb{F}$ of characteristic $0$. As a direct application of our results, we are able to produce a series of non-generic un

Arindam Das, Sudip Jana, Sanjoy Mandal, S. Nandi

The inclusion of heavy neutral leptons (right-handed neutrinos) to the Standard Model (SM) particle content is one of the best motivated ways to account for the observed neutrino masses and flavor mixing. The modification of the charged and neutral currents from active-sterile mixing of the neutral leptons can provide novel signatures which can be tested at

Michael Fauss, Abdelhak M. Zoubir, H. Vincent Poor

Under mild Markov assumptions, sufficient conditions for strict minimax optimality of sequential tests for multiple hypotheses under distributional uncertainty are derived. First, the design of optimal sequential tests for simple hypotheses is revisited and it is shown that the partial derivatives of the corresponding cost function are closely related to the

Hainan Xu, Shuoyang Ding, Shinji Watanabe

Most end-to-end speech recognition systems model text directly as a sequence of characters or sub-words. Current approaches to sub-word extraction only consider character sequence frequencies, which at times produce inferior sub-word segmentation that might lead to erroneous speech recognition output. We propose pronunciation-assisted sub-word modeling (PASM

Archana Rajakaruna, Ahsan Manzoor, Pawani Porambage, Madhusanka Liyanage

The proliferation of the Internet of Things (IoT) technologies have strengthen the self-monitoring and autonomous characteristics of the sensor networks deployed in numerous application areas. The recent developments of the edge computing paradigms have also enabled on-site processing and managing capabilities of sensor networks. In this paper, we introduce

Andrew Daw, Jamol Pender

Across a wide variety of applications, the self-exciting Hawkes process has been used to model phenomena in which the history of events influences future occurrences. However, there may be many situations in which the past events only influence the future as long as they remain active. For example, a person spreads a contagious disease only as long as they a

Yongpei Zhu, Zicong Zhou, Guojun Liao, Qianxi Yang

Accurate segmentation of brain tissue in magnetic resonance images (MRI) is a diffcult task due to different types of brain abnormalities. Using information and features from multimodal MRI including T1, T1-weighted inversion recovery (T1-IR) and T2-FLAIR and differential geometric features including the Jacobian determinant(JD) and the curl vector(CV) deriv

Michael O. Atambo, Daniele Varsano, Andrea Ferretti, S. Samaneh Ataei

Doping is one of the most common strategies for improving the photocatalytic and solar energy conversion properties of TiO$_2$, hence an accurate theoretical description of the electronic and optical properties of doped TiO$_2$ is of both scientific and practical interest. In this work we use many-body perturbation theory techniques to investigate two typica

Emmanuel Chauvet

Functions or 'functionings' enable to give a structure to any activity and their combinations constitute the capabilities which characterize economic assets such as work utility. The basic law of supply and demand naturally emerges from that structure while integrating this utility within frames of reference in which conditions of growth and associat

Nathan Kallus, Brenton Pennicooke, Michele Santacatterina

Inverse probability of treatment weighting (IPTW), which has been used to estimate sample average treatment effects (SATE) using observational data, tenuously relies on the positivity assumption and the correct specification of the treatment assignment model, both of which are problematic assumptions in many observational studies. Various methods have been p

Kaïs Ammari, Alessandro Duca

In this work, we consider the bilinear Schrödinger equation $i\partial_tψ=-Δψ+u(t)Bψ$ in the Hilbert space $L^2(\mathcal{G},\mathbb{C})$ with $\mathcal{G}$ an infinite graph. The Laplacian $-Δ$ is equipped with self-adjoint boundary conditions, $B$ is a bounded symmetric operator and $u\in L^2((0,T),\mathbb{R})$ with $T>0$. We study the well-posedness in sui

Vianney Bruned, André Mas, Sylvain Wlodarczyk

Particle swarm optimization algorithm is a stochastic meta-heuristic solving global optimization problems appreciated for its efficacity and simplicity. It consists in a swarm of particles interacting among themselves and searching the global optimum. The trajectory of the particles has been well-studied in a deterministic case and more recently in a stochas

Juste Raimbault

Several approaches and corresponding definitions of complexity have been developed in different fields. Urban systems are the archetype of complex socio-technical systems concerned with these different viewpoints. We suggest in this chapter some links between three types of complexity, namely emergence, computational complexity and informational complexity.

Patricia Alonso-Ruiz, Fabrice Baudoin, Li Chen, Luke Rogers

We introduce heat semigroup-based Besov classes in the general framework of Dirichlet spaces. General properties of those classes are studied and quantitative regularization estimates for the heat semigroup in this scale of spaces are obtained. As a highlight of the paper, we obtain a far reaching $L^p$-analogue, $p \ge 1$, of the Sobolev inequality that was

Gregor T. Leuthner, Stefan Hummel, Clemens Mangler, Timothy J. Pennycook

Transmission electron microscopy (TEM) is carried out in vacuum to minimize the interaction of the imaging electrons with gas molecules while passing through the microscope column. Nevertheless, in typical devices, the pressure remains at 10^-7 mbar or above, providing a large number of gas molecules for the electron beam to crack, which can lead to structur

Satoshi Yokoyama

We study the motion of the hypersurface $(γ_t)_{t\geq 0}$ evolving according to the mean curvature perturbed by $\dot{w}^Q$, the formal time derivative of the $Q$-Wiener process ${w}^Q$, in a two dimensional bounded domain. Namely, we consider the equation describing the evolution of $γ_t$ as a stochastic partial differential equation (SPDE) with a multiplic

Yanki Lekili, Alexander Polishchuk

Using Auroux's description of Fukaya categories of symmetric products of punctured surfaces, we compute the partially wrapped Fukaya category of the complement of $k+1$ generic hyperplanes in $\mathbb{CP}^n$, for $k \geq n$, with respect to certain stops in terms of the endomorphism algebra of a generating set of objects. The stops are chosen so that the

Alejandro Ginory

The space spanned by the characters of twisted affine Lie algebras admit the action of certain congruence subgroups of $SL(2,\mathbb{Z})$. By embedding the characters in the space spanned by theta functions, we study an $SL(2,\mathbb{Z})$-closure of the space of characters. Analogous to the untwisted affine Lie algebra case, we construct a commutative associ

Naoki Kitazawa

The theory of Morse functions and their higher dimensional versions or fold maps on manifolds and its application to geometric theory of manifolds is one of important branches of geometry and mathematics. Studies related to this was started in 1950s by differential topologists such as Thom and Whitney and they have been studied actively. In this paper, we st

Kouji Hashimoto, Takehiko Kinoshita, Mitsuhiro T. Nakao

In this paper, we present a numerical verification method of solutions for nonlinear parabolic initial boundary value problems. Decomposing the problem into a nonlinear part and an initial value part, we apply Nakao's projection method, which is based on the full-discrete finite element method with constructive error estimates, to the nonlinear part and

Mohamad Kazem Shirani Faradonbeh, Ambuj Tewari, George Michailidis

This paper studies adaptive algorithms for simultaneous regulation (i.e., control) and estimation (i.e., learning) of Multiple Input Multiple Output (MIMO) linear dynamical systems. It proposes practical, easy to implement control policies based on perturbations of input signals. Such policies are shown to achieve a worst-case regret that scales as the squar

Shangbang Long, Xin He, Cong Yao

With the rise and development of deep learning, computer vision has been tremendously transformed and reshaped. As an important research area in computer vision, scene text detection and recognition has been inescapably influenced by this wave of revolution, consequentially entering the era of deep learning. In recent years, the community has witnessed subst

Weijing Li

We give an alternative proof of skew information via operator algebra approach and show its strong monotonicity under particular quantum TPCP maps. We then formulate a family of new resource measure if the resource can be characterized by a resource destroying map and the free operation should be also modified. Our measure is easy-calculating and applicable

Muhammad Ahsan Khan, Dan Timotin

The maximal algebras of scalar Toeplitz matrices are known to be formed by generalized circulants. The identification of algebras consisting of block Toeplitz matrices is a harder problem, that has received little attention up to now. We consider the case when the block entries of the matrices belong to a commutative algebra $ \mathcal{A} $. After obtaining

David McAllester, Karl Stratos

Measuring mutual information from finite data is difficult. Recent work has considered variational methods maximizing a lower bound. In this paper, we prove that serious statistical limitations are inherent to any method of measuring mutual information. More specifically, we show that any distribution-free high-confidence lower bound on mutual information es

Linda S. L. Tan, Nial Friel

Deriving Bayesian inference for exponential random graph models (ERGMs) is a challenging "doubly intractable" problem as the normalizing constants of the likelihood and posterior density are both intractable. Markov chain Monte Carlo (MCMC) methods which yield Bayesian inference for ERGMs, such as the exchange algorithm, are asymptotically exact but

Bo Peng, Haodong Mei, Hao Zhang, Hezhu Shao

By using a first-principles approach, monolayer PbI$_2$ is found to have great potential in thermoelectric applications. The linear Boltzmann transport equation is applied to obtain the perturbation to the electron distribution by different scattering mechanisms. The mobility is mainly limited by the deformation-potential interaction with long-wavelength aco

Guyue Hu, Bo Cui, Shan Yu

Benefiting from its succinctness and robustness, skeleton-based action recognition has recently attracted much attention. Most existing methods utilize local networks (e.g., recurrent, convolutional, and graph convolutional networks) to extract spatio-temporal dynamics hierarchically. As a consequence, the local and non-local dependencies, which contain more

N. Teshima

In the DeeMe experiment, approximately $70\ \mathrm{GHz/mm^{2}}$ prompt-charged particles will hit the multi-wire proportional chambers (MWPCs) before signal electrons come. To avoid the space charge effect, we developed fast HV-switching MWPCs in order to control the gas gain dynamically. All four of the MWPCs were manufactured. Last year, the circuit of re

Ming Zhang, Nenggan Zheng, De Ma, Gang Pan

A Spiking Neural Network (SNN) can be trained indirectly by first training an Artificial Neural Network (ANN) with the conventional backpropagation algorithm, then converting it into an SNN. The conventional rate-coding method for SNNs uses the number of spikes to encode magnitude of an activation value, and may be computationally inefficient due to the larg

Won Ik Cho, Hyeon Seung Lee, Ji Won Yoon, Seok Min Kim

For a large portion of real-life utterances, the intention cannot be solely decided by either their semantic or syntactic characteristics. Although not all the sociolinguistic and pragmatic information can be digitized, at least phonetic features are indispensable in understanding the spoken language. Especially in head-final languages such as Korean, senten

Cecile Monthus

While the Macroscopic Fluctuation Theory (MFT) is a renormalized theory in the hydrodynamic limit based on a space-time local Lagrangian that is Gaussian with respect to the empirical current, C. Maes, K. Netocny and B. Wynants [Markov Proc. Rel. Fields. 14, 445 (2008)] have derived a microscopic Fluctuation Theory (mFT) for independent Markov jump processes

Mizuki Shirogane, Shinji Ejiri, Ryo Iwami, Kazuyuki Kanaya

We study energy gap (latent heat) between the hot and cold phases at the first order phase transition point of the SU(3) gauge theory. Performing simulations on lattices with various spatial volumes and lattice spacings, we calculate the energy gap by a method using the Yang-Mills gradient flow and compare it with that by the conventional derivative method.

Hao-Chung Cheng, Li Gao, Min-Hsiu Hsieh

R\'enyi and Augustin information are generalizations of mutual information defined via the R\'enyi divergence, playing a significant role in evaluating the performance of information processing tasks by virtue of its connection to the error exponent analysis. In quantum information theory, there are three generalizations of the classical R\'enyi divergence -

Sajad Abbar, Maria Cristina Volpe

A dense neutrino medium could experience self-induced flavor conversions on relatively small scales in the presence of the so-called fast flavor conversion modes. Owing to the fact that fast conversion scales could be much smaller than the ones of the traditional collective neutrino oscillations, it has been speculated that fast modes could lead to some sort

Duojie Jia, Wen-Chao Dong

In this work, we study the Regge-like spectra of excited singly heavy mesons by proposing a general Regge-like mass relations in which the slope ratio $α^{\prime }/β^{\prime }$ between the radial and angular-momentum Regge trajectories is $π/2$ and the hadron mass undergoes a shift including the heavy quark mass and an extra binding energy between heavy quar

Arvind Khuntia, Sushanta Tripathy, Ashish Bisht, Raghunath Sahoo

Small system collectivity observed at the LHC energies along with enhancement of strangeness makes high-multiplicity proton+proton (pp) collisions very interesting in order to look for QGP-like features, usually found in heavy-ion collisions. It may be interesting to perform a double differential study of different observables in pp collisions in terms of ch

Hsuan-Hao Chang, Wei-Yu Chiu, Hongjian Sun, Chia-Ming Chen

This paper investigates smart home energy management in consideration of tradeoffs between residential privacy and energy costs. A multiobjective approach that minimizes energy costs and maximizes privacy protection is proposed. The approach leads to a multiobjective optimization problem in which the two objectives are addressed in separate dimensions. A hyb

Jifeng Xuan, Matias Martinez, Favio Demarco, Maxime Clément

We propose NOPOL, an approach to automatic repair of buggy conditional statements (i.e., if-then-else statements). This approach takes a buggy program as well as a test suite as input and generates a patch with a conditional expression as output. The test suite is required to contain passing test cases to model the expected behavior of the program and at lea

Yi Tay, Luu Anh Tuan, Siu Cheung Hui, Jian Su

We propose DecaProp (Densely Connected Attention Propagation), a new densely connected neural architecture for reading comprehension (RC). There are two distinct characteristics of our model. Firstly, our model densely connects all pairwise layers of the network, modeling relationships between passage and query across all hierarchical levels. Secondly, the d

Mateusz Wilinski, Piero Mazzarisi, Daniele Tantari, Fabrizio Lillo

We study the problem of identifying macroscopic structures in networks, characterizing the impact of introducing link directions on the detectability phase transition. To this end, building on the stochastic block model, we construct a class of hardly detectable directed networks. We find closed form solutions by using belief propagation method showing how t

Bernold Fiedler, Carlos Rocha

We embark on a detailed analysis of the close relations between combinatorial and geometric aspects of the scalar parabolic PDE \begin{equation}\label{eq:*} u_t = u_{xx} + f(x,u,u_x) \tag{$*$} \end{equation} on the unit interval $0 < x<1$ with Neumann boundary conditions. We assume $f$ to be dissipative with $N$ hyperbolic equilibria $v\in\mathcal{E}$. The g

Pisheng Ding

For a harmonic function u on Euclidean space, this note shows that its gradient is essentially determined by the geometry of its level hypersurfaces. Specifically, the factor by which |grad(u)| changes along a gradient flow is completely determined by the mean curvature of the level hypersurfaces intersecting the flow.

Amir H. Ashouri, Tarek S. Abdelrahman, Alwyn Dos Remedios

Modern Convolutional Neural Networks (CNNs) are complex, encompassing millions of parameters. Their deployment exerts computational, storage and energy demands, particularly on embedded platforms. Existing approaches to prune or sparsify CNNs require retraining to maintain inference accuracy. Such retraining is not feasible in some contexts. In this paper, w

Gholamreza Hajargasht, Prasada Rao

Over the past five decades a number of multilateral index number systems have been proposed for spatial and cross-country price comparisons. These multilateral indexes are usually expressed as solutions to systems of linear or nonlinear equations. In this paper, we provide general theorems that can be used to establish necessary and sufficient conditions for

Matthijs Vákár, Ohad Kammar, Sam Staton

We give an adequate denotational semantics for languages with recursive higher-order types, continuous probability distributions, and soft constraints. These are expressive languages for building Bayesian models of the kinds used in computational statistics and machine learning. Among them are untyped languages, similar to Church and WebPPL, because our sema

Yifan Tian, Yantian Hou, Jiawei Yuan

With the explosive growth in the number of pictures taken by smartphones, organizing and searching pictures has become important tasks. To efficiently fulfill these tasks, the key enabler is annotating images with proper keywords, with which keyword-based searching and organizing become available for images. Currently, smartphones usually synchronize photo a

Jingzhao Zhang, Hongyi Zhang, Suvrit Sra

We study smooth stochastic optimization problems on Riemannian manifolds. Via adapting the recently proposed SPIDER algorithm \citep{fang2018spider} (a variance reduced stochastic method) to Riemannian manifold, we can achieve faster rate than known algorithms in both the finite sum and stochastic settings. Unlike previous works, by \emph{not} resorting to b

Rafael Diniz, Alan L. V. Guedes, Sergio Colcher

ISDB-T International standard is currently adopted by most Latin America countries and is already installed in most TV sets sold in recent years in the region. To support interactive applications in Digital TV receivers, ISDB-T defines the middleware Ginga. Similar to Digital TV, Digital Radio standards also provide the means to carry interactive application

George D. J. Phillies

This note considers how hydrodynamic interactions between a pair of rods slow the motion of each rod. Rods are approximated as being nearly straight lines of pointlike beads. Hydrodynamic interactions between the beads are treated with generalizations, developed by Kynch (J. Fluid Mech. 5, 193-208 (1959)) and by Mazur and van Saarloos (Physica A 115, 21-57 (

Qi Han, Jingbo Liu

In this paper, we prove that $\boldsymbolζ$ cannot be a solution to any nontrivial algebraic differential equation whose coefficients are polynomials in $\boldsymbolΓ,\boldsymbolΓ^{(n)}$ and $\boldsymbolΓ^{(\ell n)}$ over the ring of polynomials in $\mathbf{C}$, where $\ell,n\geq1$ are positive integers.

Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg

The classical convergence analysis of SGD is carried out under the assumption that the norm of the stochastic gradient is uniformly bounded. While this might hold for some loss functions, it is violated for cases where the objective function is strongly convex. In Bottou et al. (2018), a new analysis of convergence of SGD is performed under the assumption th

Junxiang Wang, Hongyi Li, Liang Zhao

In recent years, even though Stochastic Gradient Descent (SGD) and its variants are well-known for training neural networks, it suffers from limitations such as the lack of theoretical guarantees, vanishing gradients, and excessive sensitivity to input. To overcome these drawbacks, alternating minimization methods have attracted fast-increasing attention rec

Claude Laflamme, Maurice Pouzet, Norbert Sauer, Robert Woodrow

A sibling of a relational structure $R$ is any structure $S$ which can be embedded into $R$ and, vice versa, in which $R$ can be embedded. Let $sib(R)$ be the number of siblings of $R$, these siblings being counted up to isomorphism. Thomassé conjectured that for countable relational structures made of at most countably many relations, $sib(R)$ is either $1$

Valts Blukis, Dipendra Misra, Ross A. Knepper, Yoav Artzi

We propose an approach for mapping natural language instructions and raw observations to continuous control of a quadcopter drone. Our model predicts interpretable position-visitation distributions indicating where the agent should go during execution and where it should stop, and uses the predicted distributions to select the actions to execute. This two-st

Justin C. Feng

In this article, I discuss the construction of some globally conserved currents that one can construct in the absence of a Killing vector. One is based on the Komar current, which is constructed from an arbitrary vector field and has an identically vanishing divergence. I obtain some expressions for Komar currents constructed from some generalizations of Kil

Nadeem-ul-islam, Prince A. Ganai, Sudhaker Upadhyay

In this paper, we discuss the effect of small statistical thermal fluctuations around the equilibrium on the thermodynamics of small non-rotating BTZ black hole. This is done by evaluating the leading-order corrections to the thermodynamical equation of states, namely, entropy, free energy, internal energy, pressure, enthalpy, Gibbs free energy and specific

Karen M. Leighly, Donald M. Terndrup, Adrian B. Lucy, Hyunseop Choi

It has been known for 20 years that the absorbing gas in broad absorption line quasars does not completely cover the continuum emission region, and that partial covering must be accounted for to accurately measure the column density of the outflowing gas. However, the nature of partial covering itself is not understood. Extrapolation of the SimBAL spectral s

Zhengwei Wang, Graham Healy, Alan F. Smeaton, Tomas E. Ward

There is a growing interest in using generative adversarial networks (GANs) to produce image content that is indistinguishable from real images as judged by a typical person. A number of GAN variants for this purpose have been proposed, however, evaluating GANs performance is inherently difficult because current methods for measuring the quality of their out

Eli Ben-Michael, Avi Feller, Jesse Rothstein

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The &#34;synthetic control&#34; is a weighted average of control units that balances the treated unit&#39;s pre-treatment outcomes as closely as possible. A critical feature of the original proposal is to use SCM only whe

Amiangshu Bosu, Anindya Iqbal, Rifat Shahriyar, Partha Chakroborty

The blockchain technology has potential applications in various areas such as smart-contracts, Internet of Things (IoT), land registry, supply chain management, storing medical data, and identity management. Although the Github currently hosts more than six thousand active Blockchain software (BCS) projects, few software engineering research has investigated

John A. Arredondo, Camilo Ramírez Maluendas, Luz Edith Santos Guerrero

It is well known that there exist twenty two symmetry type graphs associated to 4-orbit maps. For this ones we give the feasible values taken by the degree of the vertices and the number appropriate of edges in the boundary of each face of the map, by introducing the concepts of vertex type graph, face type graph and characteristic system.

Chenrui Yao, Yao Ma, Liangyun Chen

In this paper, we mainly study a class of biderivations and triple homomorphisms on perfect Jordan algebras. Let $J$ be a Jordan algebra and $δ:J \times J \rightarrow J$ a symmetric biderivation satisfying $δ(w , u \circ v) = w \cdot δ(u , v), \forall u,v,w \in J$. If $J$ is perfect and satisfies $Z(J) = \{0\}$, then $δ$ is of the form $δ(x , y) = γ(x \circ

Ruiwu Niu, Xiaoqun Wu, Ju-an Lu, Jinhu Lv

This paper mainly discusses the diffusion on complex networks with time-varying couplings. We propose a model to describe the adaptive diffusion process of local topological and dynamical information, and find that the Barabasi-Albert scale-free network (BA network) is beneficial to the diffusion and leads nodes to arrive at a larger state value than other n

Shourjya Sanyal, David F. Coker, Donal MacKernan

Protein activation and deactivation is central to a variety of biological mechanisms, including cellular signaling and transport. Unimolecular fluorescent resonance energy transfer (FRET) probes are a class of fusion protein sensors that allow biologists to visualize using an optical microscope whether specific proteins are activated due to the presence near

Abolfazl Jafari

We extend the non-commutative coordinates relationship into other than the Minkowski space-time. We clarify the non-commutativity dependency to the geometrical structure. As well as, we find an inverse map between Riemann&#39;s normal and global coordinates. Furthermore, we show that behavior of the corresponding coordinates non-commutativity like as a tenso

Ilke Demir, Ramesh Raskar

More than half of the world&#39;s roads lack adequate street addressing systems. Lack of addresses is even more visible in daily lives of people in developing countries. We would like to object to the assumption that having an address is a luxury, by proposing a generative address design that maps the world in accordance with streets. The addressing scheme i

Edgard Chammas, Chafic Mokbel, Laurence Likforman-Sulem

Historical documents present many challenges for offline handwriting recognition systems, among them, the segmentation and labeling steps. Carefully annotated textlines are needed to train an HTR system. In some scenarios, transcripts are only available at the paragraph level with no text-line information. In this work, we demonstrate how to train an HTR sys

Won-Il Song, Taek-Jong Kim

It is an important subject how deal with the symptom&#39;s data, input data, to improve the accuracy and efficiency of the diagnostic algorithm in the medical decision support systems. In this paper, we described a method for the numerical value of symptoms to develop the medical decision support system that diagnose a large number of diseases, not one or tw

Pu Qiao, Xingzhi Zhan

A consequence of Ore&#39;s classic theorem characterizing the maximal graphs with given order and diameter is a determination of the largest such graphs. We give a very short and simple proof of this smaller result, based on a well-known elementary observation.

Frédéric Mynard

We study the completeness and ultracompleteness numbers of a convergence space. In the case of a completely regular topological space, the completeness number is countable if and only if the space is $Č$ech-complete, and the ultracompleteness number is countable if and only if the space is ultracomplete. We show that the completeness number of a space is equ

Aliezer Martínez-Mesa, Llinersy Uranga Piña

Optical micro-manipulation techniques has evolved into powerful tools to efficiently steer the motion of microscopical particles on periodic and quasi-periodic potentials, driven by the external electromagnetic field. Here, the dynamics of molecular diffusion on optical lattices is analysed within the framework of the theory of open systems, for polar molecu

Misha Gromov

We study metrics with positive scalar curvatures in domains with corners and suggest possible extensions of the concept of positive scalar curvature to singular spaces.

P. F. Antonietti, G. Manzini, M. Verani

In this work, we exploit the capability of virtual element methods in accommodating approximation spaces featuring high-order continuity to numerically approximate differential problems of the form $Δ^p u =f$, $p\ge1$. More specifically, we develop and analyze the conforming virtual element method for the numerical approximation of polyharmonic boundary valu

Misha Gromov

We study/construct (proper and non-proper) Morse functions on complete Riemannian manifolds, the level hypersurfaces of which have positive mean curvatures at all non-critical points. We show, for instance, that if a complete Rieannin manifold admits no such (not necessarily proper) function, then it contains a (possibly, singular) complete (possibly, compac

Iaakov Exman

Conceptual Integrity is the most important consideration for software system design, as stated by Frederick Brooks. Brooks also suggested that Conceptual Integrity can be attained by means of design principles, such as Propriety, and Orthogonality. However, Brooks&#39; principles have not been formalized, posing obstacles to their application in practice, an

Navdeep K. Panesar, Alphonse C. Sterling, Ronald L. Moore, Sanjiv K. Tiwari

Recent observations show that the buildup and triggering of minifilament eruptions that drive coronal jets result from magnetic flux cancelation at the neutral line between merging majority- and minority-polarity magnetic flux patches. We investigate the magnetic setting of ten on-disk small-scale UV/EUV jets (jetlets), smaller than coronal X-ray jets but la

Iddo Tzameret, Stephen A. Cook

Aiming to provide weak as possible axiomatic assumptions in which one can develop basic linear algebra, we give a uniform and integral version of the short propositional proofs for the determinant identities demonstrated over $GF(2)$ in Hrubes-Tzameret [SICOMP&#39;15]. Specifically, we show that the multiplicativity of the determinant function and the Cayley

Hongwei Li, Andrii Zhygallo, Bjoern Menze

Brain image segmentation is used for visualizing and quantifying anatomical structures of the brain. We present an automated ap-proach using 2D deep residual dilated networks which captures rich context information of different tissues for the segmentation of eight brain structures. The proposed system was evaluated in the MICCAI Brain Segmentation Challenge

Virginia Trimble, Kip S. Thorne

Fifty years ago, borrowing an idea from our Russian friends Guseinov and Zeldovich, we looked for very compact stars (neutron stars and black holes, in modern terminology) as optically-invisible components of single-line spectroscopic binaries. We didn&#39;t find any, but our method was very close to the processes that soon identified neutron stars in the X-

Soubarna Banik, Mikko Lauri, Simone Frintrop

Objects of different classes can be described using a limited number of attributes such as color, shape, pattern, and texture. Learning to detect object attributes instead of only detecting objects can be helpful in dealing with a priori unknown objects. With this inspiration, a deep convolutional neural network for low-level object attribute classification,

Marcelo Epstein

A novel formulation of statics in terms of the exterior algebra of an affine space is shown to be the underlying mathematical structure of Vlasov&#39;s thin-walled beam theory in structural mechanics.

Ashish Chanana, Neda Loftizadeh, Hugo O. Condori Quispe, Prashanth Gopalan

Three-dimensional (3D) semimetals have been predicted and demonstrated to have a wide variety of interesting properties associated with its linear energy dispersion. In analogy to two-dimensional (2D) Dirac semimetals, such as graphene, Cd3As2, a 3D semimetal, has shown ultra-high mobility, large Fermi velocity, and has been hypothesized to support plasmons

C. T. H. Davies, K. Hornbostel, J. Komijani, J. Koponen

We derive the Operator Product Expansion whose vacuum expectation value gives the time-moments of the pseudoscalar heavy-light current-current correlator up to and including terms in $α_s^2$ multiplying $\langle\overlineψψ\rangle/M^3$ and terms in $α_s$ multiplying $\langle α_s G^2 \rangle/M^4$, where $M$ is the heavy-quark mass. Using lattice QCD results fo

Reza Mirzazadeh, Mohammad Hossein Moattar, Majid Vafaei Jahan

The most common malware detection approaches which are based on signature matching and are not sufficient for metamorphic malware detection, since virus kits and metamorphic engines can produce variants with no resemblance to one another. Metamorphism provides an efficient way for eluding malware detection software kits. Code obfuscation methods like dead-co

Andrew Hryniowski, Alexander Wong

Automated deep neural network architecture design has received a significant amount of recent attention. However, this attention has not been equally shared by one of the fundamental building blocks of a deep neural network, the neurons. In this study, we propose PolyNeuron, a novel automatic neuron discovery approach based on learned polyharmonic spline act

Ralf-Dieter Scholz

Among about 1.8 million Gaia DR2 high proper motion stars with $μ>60$ mas/yr and moderately significant parallaxes ($\varpi>3σ_{\varpi}$), we have selected 109 high-speed star candidates with Galactic rest frame tangential velocities (corrected for solar motion) $v_{t,g}$$>$700 km/s, well above the local Galactic escape velocity. After applying various Gaia

Peirong Wang, Pengfei Li, Farzana Chowdhury, Li Zhang

In this paper, we first present a centralized traffic control model based on the emerging dynamic path flows. This new model in essence views the whole target network as one integral piece in which traffic propagates based on traffic flow dynamics, vehicle paths, and traffic control. In light of this centralized traffic control concept, most requirements for

William Kuszmaul

We present an algorithm for approximating the edit distance $\operatorname{ed}(x, y)$ between two strings $x$ and $y$ in time parameterized by the degree to which one of the strings $x$ satisfies a natural pseudorandomness property. The pseudorandomness model is asymmetric in that no requirements are placed on the second string $y$, which may be constructed

Yushan Siriwardhana, Pawani Porambage, Madhusanka Liyanage, Jaspreet Singh Walia

In addition to the high degree of flexibility and customization required by different vertical sectors, 5G calls for a network architecture that ensures ultra-responsive and ultra-reliable communication links. The novel concept called micro-operator (uO) enables a versatile set of stakeholders to operate local 5G networks within their premises with a guarant

James Fraser

One of the prominent areas of research in graph theory is the degree-diameter problem, in which we seek to determine how many vertices a graph may have when constrained to a given degree and diameter. Different variants of this problem are obtained by considering further restrictions on the graph, such as whether it is directed, undirected, mixed, vertex-tra

Greg Martin, Lee Troupe

The celebrated Erdős--Kac theorem says, roughly speaking, that the values of additive functions satisfying certain mild hypotheses are normally distributed. In the intervening years, similar normal distribution laws have been shown to hold for certain non-additive functions and for amenable arithmetic functions over certain subsets of the natural numbers. Co

Rui-jie Wu, Yi-Xiu Kong, Gui-yuan Shi, Yi-Cheng Zhang

We induce the NonBacktracking Expansion Branch method to analyze the k-core pruning process on the monopartite graph G which does not contain any self-loop or multi-edge. Different from the traditional approaches like the generating functions or the degree distribution evolution equations which are mathematically difficult to solve, this method provides a si

Maximilian Hollstein, Nina Rohringer

We present an approach for initiating and tracing ultra-fast electron dynamics in core-excited atoms, molecules and solids. The approach is based on stimulated resonant inelastic x-ray scattering induced by a single, chirped, broadband XUV/x-ray pulse. A first interaction with this pulse prepares a core-excited state wave packet by resonant core-excitation.

Haiyan Liu, Francesco Del Galdo, Jeanine Houwing-Duistermaat

This paper aims at predicting lung function values based on patients historical lung function values and serum biomarkers in Scleroderma patients. The progression of disease is measured by three lung function indexes (FVC, TLC, DLCO). Values of four biomarkers (TIMP1, P3NP, HA, NT-proBNP) are available. The data are sparse (6 months intervals) and irregular

Yuankai Huo, James G. Terry, Jiachen Wang, Vishwesh Nath

Coronary artery calcium (CAC) is biomarker of advanced subclinical coronary artery disease and predicts myocardial infarction and death prior to age 60 years. The slice-wise manual delineation has been regarded as the gold standard of coronary calcium detection. However, manual efforts are time and resource consuming and even impracticable to be applied on l

Ovidiu Dan, Vaibhav Parikh, Brian D. Davison

IP Geolocation databases are widely used in online services to map end user IP addresses to their geographical locations. However, they use proprietary geolocation methods and in some cases they have poor accuracy. We propose a systematic approach to use publicly accessible reverse DNS hostnames for geolocating IP addresses. Our method is designed to be comb

Shoham Letzter

For graphs $H$ and $F$, let $\operatorname{ex}(n, H, F)$ be the maximum possible number of copies of $H$ in an $F$-free graph on $n$ vertices. The study of this function, which generalises the well-studied Turán numbers of graphs, was initiated recently by Alon and Shikhelman. We show that if $F$ is a tree then $\operatorname{ex}(n, H, F) = Θ(n^r)$ for some

U. Satya Sainadh, M. Anil Kumar

We consider an optical and mechanical mode interacting through both linear and quadratic dispersive couplings in a general cavity-optomechanical set-up. The parity and strength of an intrinsic quadratic optomechanical coupling (QOC) provides an opportunity to control the optomechanical (OM) interaction. We quantify this interaction by studying normal-mode sp