March 2019 arXiv papers

Gustavo D. Gil, Julie M. Walker, Nabil Zemiti, Allison M. Okamura

The current generation of surgeons requires extensive training in teleoperation to develop specific dexterous skills, which are independent of medical knowledge. Training curricula progress from manipulation tasks to simulated surgical tasks but are limited in time. To tackle this, we propose to integrate surgical robotic training together with Haptic Feedba

Arya Mazumdar, Soumyabrata Pal

Source coding is the canonical problem of data compression in information theory. In a locally encodable source coding, each compressed bit depends on only few bits of the input. In this paper, we show that a recently popular model of semi-supervised clustering is equivalent to locally encodable source coding. In this model, the task is to perform multiclass

Valentina Baccetti, Robert B. Mann, Daniel R. Terno

We consider spherically-symmetric black holes in semiclassical gravity. For a collapsing radiating thin shell we derive a sufficient condition on the exterior geometry that ensures that a black hole is not formed. This is also a sufficient condition for an infalling test particle to avoid the apparent horizon of an existing black hole and approach it only wi

Kouichi Taira

In this paper, we study the mapping property form $L^p$ to $L^q$ of the resolvent of the Fourier multiplier operators and scattering theory of generalized Schrödinger operators. Though the first half of the subject is studied in [4], we extend their result to away from the duality line and we also study the Hölder continuity of the resolvent.

Matt Visser

The Firoozbakht, Nicholoson, and Farhadian conjectures can be phrased in terms of increasingly powerful conjectured bounds on the prime gaps $g_n := p_{n+1}-p_n$. \[ g_n \leq p_n \left(p_n^{1/n} -1 \right)\qquad\qquad\qquad (n \geq 1; \; Firoozbakht). \] \[ g_n \leq p_n \left((n\ln n)^{1/n} -1 \right)\qquad\qquad (n>4; \; Nicholson). \] \[ g_n \leq p_n \left

Wei Hu, Tianyu Pan, Dehan Kong, Weining Shen

With the rapid growth of neuroimaging technologies, a great effort has been dedicated recently to investigate the dynamic changes in brain activity. Examples include time course calcium imaging and dynamic brain functional connectivity. In this paper, we propose a novel nonparametric matrix response regression model to characterize the nonlinear association

Cristian Quinzacara, Paola Meza, Almeira Sampson, Mauricio Valenzuela

We construct a generic class of models for complex scalar fields -- minimally coupled to gravity and electromagnetism -- with the property that their energy-momentum tensor and the electric current vanish for certain massive configurations. These are electromagnetically and gravitationally {\it stealth fields}. We shall see that the latter configurations can

James Saunderson

We describe a new approach to certifying the global nonnegativity of multivariate polynomials by solving hyperbolic optimization problems---a class of convex optimization problems that generalize semidefinite programs. We show how to produce families of nonnegative polynomials (which we call hyperbolic certificates of nonnegativity) from any hyperbolic polyn

Victor J. W. Guo, Michael J. Schlosser

We provide several new $q$-congruences for truncated basic hypergeometric series with the base being an even power of $q$. Our results mainly concern congruences modulo the square or the cube of a cyclotomic polynomial and complement corresponding ones of an earlier paper containing $q$-congruences for truncated basic hypergeometric series with the base bein

Andrei Agrachev, Khazhgali Kozhasov, André Uschmajew

We establish a new extremal property of the classical Chebyshev polynomials in the context of best rank-one approximation of tensors. We also give some necessary conditions for a tensor to be a minimizer of the ratio of spectral and Frobenius norms.

A. M. Tsvelik

It is shown that the application of sufficiently strong magnetic field to the odd-frequency paired Pair Density Wave state described in Phys. Rev. B 94, 165114 (2016) leads to formation of a low temperature metallic state with zero Hall response. Applications of these ideas to the recent experiments on stripe-ordered La_{1.875}Ba_{0.125}CuO_4 are discussed.

Franz Wilhelm Schlöder, J. Timo Essig

We construct an explicit de Rham isomorphism relating the cohomology rings of Banagl's de Rham and spatial approach to intersection space cohomology for stratified pseudomanifolds with isolated singularities. Intersection space (co-)homology is a modified (co-)homology theory extending Poincaré Duality to stratified pseudomanifolds. The novelty of our re

Sven Reichardt, Ludger Wirtz

We present an ab initio computational approach for the calculation of resonant Raman intensities, including both excitonic and non-adiabatic effects. Our diagrammatic approach, which we apply to two prototype, semiconducting layered materials, allows a detailed analysis of the impact of phonon-mediated exciton-exciton scattering on the intensities. In the ca

Botao Hao, Boxiang Wang, Pengyuan Wang, Jingfei Zhang

Tensors are becoming prevalent in modern applications such as medical imaging and digital marketing. In this paper, we propose a sparse tensor additive regression (STAR) that models a scalar response as a flexible nonparametric function of tensor covariates. The proposed model effectively exploits the sparse and low-rank structures in the tensor additive reg

J. Heideman, D. Perez-Loureiro, R. Grzywacz, C. R. Thornsberry

A new high-precision detector for studying neutrons from beta-delayed neutron emission and direct reaction studies is proposed. The Neutron dEtector with Xn Tracking (NEXT) array is designed to maintain high intrinsic neutron detection efficiency while reducing uncertainties in neutron energy measurements. A single NEXT module is composed of thin segments of

Ralf Bürkle, Amichay Vardi, Doron Cohen, James R. Anglin

We propose currently feasible experiments using small, isolated systems of ultracold atoms to investigate the effects of dynamical chaos in the microscopic onset of irreversibility. A control parameter is tuned past a critical value, then back to its initial value; hysteresis appears as a finite probability that the atoms fail to return to their initial stat

Irawan Nurhas, Stefan Geisler, Jan Pawlowski

System design for well-being needs an appropriate tool to help designers to determine relevant requirements that can help human well-being to flourish. Personas come as a simple yet powerful tool in the early development stage of the user interface design. Considering well-being determinants in the early design process provide benefits for both the user and

Martino Borello, Francesca Dalla Volta, Giovanni Zini

Let $G$ be the simple group ${\rm PSL}(3,2^p)$, where $p$ is a prime number. For any subgroup $H$ of $G$, we compute the Möbius function of $H$ in the subgroup lattice of $G$. To this aim, we describe the intersections of maximal subgroups of $G$. We point out some connections of the Möbius function with other combinatorial objects, and, in this context, we

Francisco Soto-Eguibar, Héctor M. Moya-Cessa

We present a method to generate NOON states with three photons by injecting photons in an array of three waveguides. Conditional measurements project the wave function in a given (desired) state. In passing, we show how the array of three waveguides, that effectively reproduces the interaction of three fields, may be reduced to the interaction of two fields.

Luca Ambrogioni, Marcel A. J. van Gerven

In this paper we introduce a family of stochastic gradient estimation techniques based of the perturbative expansion around the mean of the sampling distribution. We characterize the bias and variance of the resulting Taylor-corrected estimators using the Lagrange error formula. Furthermore, we introduce a family of variance reduction techniques that can be

Dagur Tómas Ásgeirsson, Pat Devlin

In this paper, we use the notion of twisted subgroups (i.e., subsets of group elements closed under the binary operation $(a,b) \mapsto aba$) to provide the first structural characterization of optimal play in the Explorer-Director game, introduced as the Magnus-Derek game by Nedev and Muthukrishnan and generalized to finite groups by Gerbner. In particular,

S. Hollands, A. Ishibashi

We consider the relative entropy between the vacuum state and a coherent state in linearized quantum gravity around a stationary black hole spacetime. Combining recent results by Casini et al. and Longo with the Raychaudhuri equation, the following result is obtained: Let $\frak A$ be the algebra of observables assoiciated with a region that is the causal fu

Ioannis Mavromatis, Andrea Tassi, Robert J. Piechocki

Future Connected and Autonomous Vehicles (CAVs) will be equipped with a large set of sensors. The large amount of generated sensor data is expected to be exchanged with other CAVs and the road-side infrastructure. Both in Europe and the US, Dedicated Short Range Communications (DSRC) systems, based on the IEEE 802.11p Physical Layer, are key enabler for the

Paolo Barucca

Core-periphery structure is an emerging property of a wide range of complex systems and indicate the presence of group of actors in the system with an higher number of connections among them and a lower number of connections with a sparsely connected periphery. The dynamics of a complex system which is interacting on a given graph structure is strictly conne

Marc Chaumont

For almost 10 years, the detection of a hidden message in an image has been mainly carried out by the computation of Rich Models (RM), followed by classification using an Ensemble Classifier (EC). In 2015, the first study using a convolutional neural network (CNN) obtained the first results of steganalysis by Deep Learning approaching the performances of the

Joseph L. Heyman, Abhishek Gupta

The rank of a bimatrix game is defined as the rank of the sum of the payoff matrices of the two players. The rank of a game is known to impact both the most suitable computation methods for determining a solution and the expressive power of the game. Under certain conditions on the payoff matrices, we devise a method that reduces the rank of the game without

V. K. Kozin

The BCFW recursion relation in $\mathcal{N}=4$ super-Yang-Mills theory is solved using Yang-Baxter $R$-operators in the NMHV sector. Explicit expressions for $\mathcal{R}$-invariants are obtained in terms of the chains of $R$-operators acting on an appropriate basic state.

Minchae Jung, Walid Saad, Gyuyeol Kong

Large intelligent surfaces (LISs) constitute a new and promising wireless communication paradigm that relies on the integration of a massive number of antenna elements over the entire surfaces of man-made structures. The LIS concept provides many advantages, such as the capability to provide reliable and space-intensive communications by effectively establis

Hao Liu, James Creswell, Konstantina Dachlythra

We study the problem of EB-leakage that is associated with incomplete polarized CMB sky. In the blind case that assumes no additional information about the statistical properties and amplitudes of the signal from the missing sky region, we prove that the recycling method (Liu et al.~2018) gives the unique best estimate of the EB-leakage. Compared to the prev

Jianzong Pi, Joseph L. Heyman, Abhishek Gupta

In this paper, we first devise two algorithms to determine whether or not a bimatrix game has a strategically equivalent zero-sum game. If so, we propose an algorithm that computes the strategically equivalent zero-sum game. If a given bimatrix game is not strategically equivalent to a zero-sum game, we then propose an approach to compute a zero-sum game who

Botong Wang

We construct irreducible complex projective varieties such that the Lyubeznik numbers of their affine cones depend on the choices of projective embeddings. The main ingredient is the recent work of Reichelt-Saito-Walther, where the Lyubeznik numbers are reinterpreted using perverse sheaves and reducible projective varieties with dependent Lyubeznik numbers a

Ahmed Ali, Alexander Ya. Parkhomenko

Recently, the LHCb Collaboration have updated their analysis of the resonant $J/ψp$ mass spectrum in the decay $Λ_b^0 \to J/ψp K^-$. In the combined Run~1 and Run~2 LHCb data, three peaks are observed, with the former $P_c(4450)^+$ state split into two narrow states, $P_c(4440)^+$ and $P_c(4457)^+$, having the masses $M=(4440.3\pm 1.3^{+4.1}_{-4.7})$ MeV and

Nicholas Heller, Niranjan Sathianathen, Arveen Kalapara, Edward Walczak

The morphometry of a kidney tumor revealed by contrast-enhanced Computed Tomography (CT) imaging is an important factor in clinical decision making surrounding the lesion's diagnosis and treatment. Quantitative study of the relationship between kidney tumor morphology and clinical outcomes is difficult due to data scarcity and the laborious nature of man

Joerg Evermann, Henry Kim

Blockchain technology, originally popularized by cryptocurrencies, has been proposed as an infrastructure technology with applications in many areas of business management. Blockchains provide an immutable record of transactions, which makes them useful in situations where business actors may not fully trust each other. The distributed nature of blockchains

Jack Dunger, Steven D. Biller

Simulation studies have been carried out to explore the ability to discriminate between single-site and multi-site energy depositions in large scale liquid scintillation detectors. A robust approach has been found that is predicted to lead to a significant statistical separation for a large variety of event classes, providing a powerful tool to discriminate

George Adam, Jonathan Lorraine

Automatic methods for generating state-of-the-art neural network architectures without human experts have generated significant attention recently. This is because of the potential to remove human experts from the design loop which can reduce costs and decrease time to model deployment. Neural architecture search (NAS) techniques have improved significantly

Pierre Dreyfuss, Haroune Houamed

In this paper, for the 3-D Navier-Stokes-Boussinesq system with horizontal dissipation, where there is no smoothing effect on the vertical derivatives, we prove a uniqueness result of solutions $ (u,ρ)\in L^{\infty}_T\big( H^{0,s}\times H^{0,1-s}\big)$ with $ (\nabla_h u,\nabla_hρ)\in L^{2}_T\big( H^{0,s}\times H^{0,1-s}\big)$ and $s\in [1/2,1]$. As a conseq

Narcis Miguel, Camilla Colombo

The coupled attitude and orbit dynamics of solar sails is studied. The shape of the sail is a simplified quasi-rhombic-pyramid that provides the structure helio-stablility properties. After adimensionalisation, the system is put in the form of a fast-slow dynamical system where the different time scales are explicitely related to the physical parameters of t

Huyan Huang, Yipeng Liu, Ce Zhu

Low-rank tensor completion recovers missing entries based on different tensor decompositions. Due to its outstanding performance in exploiting some higher-order data structure, low rank tensor ring has been applied in tensor completion. To further deal with its sensitivity to sparse component as it does in tensor principle component analysis, we propose robu

Zhiwei Fan, Boris A. Malomed

We consider a dual-core nonlinear waveguide with the parity-time (PT) symmetry, realized in the form of equal gain and loss terms carried by the coupled cores. To expand a previously found stability region for solitons in this system, and explore possibilities for the development of dynamical control of the solitons, we introduce "management" in the

Debraj Das, Shamik Gupta

For a model long-range interacting system of classical Heisenberg spins, we study how fluctuations, such as those arising from having a finite system size or through interaction with the environment, affect the dynamical process of relaxation to Boltzmann-Gibbs equilibrium. Under deterministic spin precessional dynamics, we unveil the full range of quasistat

Aditi Jha, Sumeet Agarwal

Visual scene understanding often requires the processing of human-object interactions. Here we seek to explore if and how well Deep Neural Network (DNN) models capture features similar to the brain's representation of humans, objects, and their interactions. We investigate brain regions which process human-, object-, or interaction-specific information,

Yue Wu, Nick Polydorides

Inspired by the latest developments in multilevel Monte Carlo (MLMC) methods and randomised sketching for linear algebra problems we propose a MLMC estimator for real-time processing of matrix structured random data. Our algorithm is particularly effective in handling high-dimensional inner products and matrix multiplication, in applications of image analysi

V. N. Zadorozhnyi, E. B. Yudin

The article deals with two classes of growing random graphs following the preferential attachment rule with a linear weight function, L-graphs, and hybrid Pennock graphs. We determine the exact final vertex degree distribution and the exact final two-dimensional arcs degree distributions of graphs under consideration. The study proves that each hybrid Pennoc

Eran Avraham, Oren Bergman

We recently conjectured a set of dualities relating two-dimensional orthogonal gauge theories with $\mathcal{N}=(4,4)$ supersymmetry, analogous to Hori's dualities with $\mathcal{N}=(2,2)$ supersymmetry. Here we provide a quantitative test of this conjecture by computing the elliptic genera of the dual pairs and showing that they agree. The elliptic genu

Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng

We revisit the one-shot Neural Architecture Search (NAS) paradigm and analyze its advantages over existing NAS approaches. Existing one-shot method, however, is hard to train and not yet effective on large scale datasets like ImageNet. This work propose a Single Path One-Shot model to address the challenge in the training. Our central idea is to construct a

J. L. Zhang, C. M. Wang, C. Y. Guo, X. D. Zhu

Thermoelectric effects are more sensitive and promising probes to topological properties of emergent materials, but much less addressed compared to other physical properties. Zirconium pentatelluride (ZrTe$_{5}$) has inspired active investigations recently because of its multiple topological nature. We study the thermoelectric effects of ZrTe$_{5}$ in a magn

Liat Sless, Gilad Cohen, Bat El Shlomo, Shaul Oron

Occupancy grid mapping is an important component in road scene understanding for autonomous driving. It encapsulates information of the drivable area, road obstacles and enables safe autonomous driving. Radars are an emerging sensor in autonomous vehicle vision, becoming more widely used due to their long range sensing, low cost, and robustness to severe wea

W. Katherine Tan, Patrick J. Heagerty

Scalable and accurate identification of specific clinical outcomes has been enabled by machine-learning applied to electronic medical record (EMR) systems. The development of classification models requires the collection of a complete labeled data set, where true clinical outcomes are obtained by human expert manual review. For example, the development of na

Madhav Suresh, Zuohao She, William Wallace, Adel Lahlou

A private data federation enables data owners to pool their information for querying without disclosing their secret tuples to one another. Here, a client queries the union of the records of all data owners. The data owners work together to answer the query using privacy-preserving algorithms that prevent them from learning unauthorized information about the

P. Dabhade, H. J. A. Rottgering, J. Bagchi, T. W. Shimwell

Giant radio galaxies (GRGs) are a subclass of radio galaxies which have grown to megaparsec scales. GRGs are much rarer than normal sized radio galaxies (< 0.7 Mpc) and the reason for their gigantic sizes is still debated. Here, we report the biggest sample of GRGs identified to date. These objects were found in the LOFAR Two-metre Sky Survey (LoTSS) first d

Kimihiko Fukushima, Kazumitsu Sakai

A crossing probability for the critical four-state Potts model on an $L\times M$ rectangle on a square lattice is numerically studied. The crossing probability here denotes the probability that spin clusters cross from one side of the boundary to the other. First, by employing a Monte Carlo method, we calculate the fractal dimension of a spin cluster interfa

Michael Harrison

A smooth fibration of $\mathbb{R}^3$ by oriented lines is given by a smooth unit vector field $V$ on $\mathbb{R}^3$, for which all of the integral curves are oriented lines. Such a fibration is called skew if no two fibers are parallel, and it is called nondegenerate if $\nabla V$ vanishes only in the direction of $V$. Nondegeneracy is a form of local skewne

Xing Chen, Wang Kang, Daoqian Zhu, Na Lei

Magnetic skyrmions are topological quasiparticles with great potential for applications in future information storage and processing devices because of their nanoscale size, high stability, and large velocity. Recently, the high-frequency properties of skyrmions have been explored for magnon nanodevices. Here we systematically study the dynamics of an isolat

Tatsuoki Kato, Tomoki Nakamigawa, Tadashi Sakuma

A graph puzzle ${\rm Puz}(G)$ of a graph $G$ is defined as follows. A configuration of ${\rm Puz}(G)$ is a bijection from the set of vertices of a board graph to the set of vertices of a pebble graph, both graphs being isomorphic to some input graph $G$. A move of pebbles is defined as exchanging two pebbles which are adjacent on both a board graph and a peb

Vladimir Kozlov, Nikolai G. Kuznetsov, Evgeniy Lokharu

The two-dimensional free-boundary problem describing steady gravity waves with vorticity on water of finite depth is considered. Under the assumption that the vorticity is a negative constant whose absolute value is sufficiently large, we construct a solution with the following properties. The corresponding flow is unidirectional at infinity and has a solita

Mirko Ebbers, Matthias Löwe

Equi-Energy Sampling (EES, for short) is a method to speed up the convergence of the Metropolis chain, when the latter is slow. We show that there are still models like the mean-field Potts model, where EES does not converge rapidly in certain temperature regimes. Indeed we will show that EES is slowly mixing on the mean-field Potts model, in a regime below

Reto E. Koenig, Lukas Laederach, Cédric von Allmen

This paper describes a new but state-of-the-art approach to provide authenticity in mqtt sessions using the means of zero-knowledge-proofs. This approach completely voids session hijacking for the mqtt protocol and provides authenticity without the need for any network-security nor channel-security nor broker-based predefined ACLs. The presented approach doe

Eduard Belitser, Nurzhan Nurushev

In the first part, we develop a general framework for projection structures and study several inference problems within this framework. We propose procedures based on data dependent measures (DDM) and make connections with empirical Bayes and penalization methods. The main inference problem is the uncertainty quantification (UQ), but on the way we solve the

Hui Yang, Wenming Zou

In this paper, we study the asymptotic behavior of positive solutions of the fractional Hardy-Hénon equation $$ (-Δ)^σu = |x|^αu^p ~~~~~~~~~~~ in ~~ B_1 \backslash \{0\} $$ with an isolated singularity at the origin, where $σ\in (0, 1)$ and the punctured unit ball $B_1 \backslash \{0\} \subset \mathbb{R}^n$ with $n \geq 2$. When $-2σ< α< 2σ$ and $\frac{n+α}{

Gianluca Calcagni, Sachiko Kuroyanagi, Sylvain Marsat, Mairi Sakellariadou

Dimensional flow, the scale dependence of the dimensionality of spacetime, is a feature shared by many theories of quantum gravity (QG). We present the first study of the consequences of QG dimensional flow for the luminosity distance scaling of gravitational waves in the frequency ranges of LIGO and LISA. We find generic modifications with respect to the st

Ekta Chaubey, Stefan Weinzierl

We present the two-loop master integrals relevant to the ${\mathcal O}(αα_s)$-corrections to the decay $H \rightarrow b \bar{b}$ through a $H t \bar{t}$-coupling. We keep the full dependence on the heavy particle masses, but neglect the $b$-quark mass. The occurring square roots can be rationalised and the result is expressed in terms of multiple polylogarit

Christian Maes, Karel Netočný

The force on a probe induced by a nonequilibrium medium is in general nongradient. We detail the mechanism of that feature via nonequilibrium response theory. The emergence of nongradient forces is due to a systematic &#34;twist&#34; of the excess frenesy with respect to the entropy flux, in response to changes in the coupling or in the position of the probe

Gitta Kutyniok, Philipp Petersen, Mones Raslan, Reinhold Schneider

We derive upper bounds on the complexity of ReLU neural networks approximating the solution maps of parametric partial differential equations. In particular, without any knowledge of its concrete shape, we use the inherent low-dimensionality of the solution manifold to obtain approximation rates which are significantly superior to those provided by classical

Kenichi Shimizu

Let $\mathcal{C}$ be a finite tensor category, and let $\mathcal{M}$ be an exact left $\mathcal{C}$-module category. The relative Serre functor of $\mathcal{M}$ is an endofunctor $\mathbb{S}$ on $\mathcal{M}$ together with a natural isomorphism $\underline{\mathrm{Hom}}(M, N)^* \cong \underline{\mathrm{Hom}}(N, \mathbb{S}(M))$ for $M, N \in \mathcal{M}$, whe

Yahya Hassanzadeh-Nazarabadi, Alptekin Küpçü, Öznur Özkasap

As an append-only distributed database, blockchain is utilized in a vast variety of applications including the cryptocurrency and Internet-of-Things (IoT). The existing blockchain solutions have downsides in communication and storage efficiency, convergence to centralization, and consistency problems. In this paper, we propose LightChain, which is the first

Enxhell Luzhnica, Ben Day, Pietro Lio&#39;

We propose a novel graph pooling operation using cliques as the unit pool. As this approach is purely topological, rather than featural, it is more readily interpretable, a better analogue to image coarsening than filtering or pruning techniques, and entirely nonparametric. The operation is implemented within graph convolution network (GCN) and GraphSAGE arc

Samarth Sinha, Sayna Ebrahimi, Trevor Darrell

Active learning aims to develop label-efficient algorithms by sampling the most representative queries to be labeled by an oracle. We describe a pool-based semi-supervised active learning algorithm that implicitly learns this sampling mechanism in an adversarial manner. Unlike conventional active learning algorithms, our approach is task agnostic, i.e., it d

Soheil Mehrabkhani

We propose a supervised learning algorithm for machine learning applications. Contrary to the model developing in the classical methods, which treat training, validation, and test as separate steps, in the presented approach, there is a unified training and evaluating procedure based on an iterative band filtering by the use of a fast Fourier transform. The

Hui Liu, Tian-Shi Xiong, Wei Zhang, Jun-Hong An

Topological phases with a widely tunable number of edge modes have been extensively studied as a typical class of exotic states of matter with potentially important applications. Although several models have been shown to support such phases, they are not easy to realize in solid-state systems due to the complexity of various intervening factors. Inspired by

Aybike Catal-Ozer

Non-Abelian T-duality (NATD) is a solution generating transformation for supergravity backgrounds with non-Abelian isometries. We show that NATD can be described as a coordinate dependent O(d,d) transformation, where the dependence on the coordinates is determined by the structure constants of the Lie algebra associated with the isometry group. Besides makin

Hao Wang, Xun Guo, Linfeng Zhang, Han Wang

We propose a hybrid scheme that interpolates smoothly the Ziegler-Biersack-Littmark (ZBL) screened nuclear repulsion potential with a newly developed deep learning potential energy model. The resulting DP-ZBL model can not only provide overall good performance on the predictions of near-equilibrium material properties but also capture the right physics when

Parwat Singh Anjana, Hagit Attiya, Sweta Kumari, Sathya Peri

This paper proposes an efficient framework to execute Smart Contract Transactions (SCTs) concurrently based on object semantics, using optimistic Single-Version Object-based Software Transactional Memory Systems (SVOSTMs) and Multi-Version OSTMs (MVOSTMs). In our framework, a multi-threaded miner constructs a Block Graph (BG), capturing the object-conflicts

Lorenzo Gallerani Resca

I conjecture non-zero photon and gluon bare masses derived from a cosmological scale. That entails the existence of photon and gluon Bose-Einstein (BE) condensates in a comoving Friedmann-Lemaitre-Robertson-Walker geometry. I derive tantalizing results that set the inter-particle distance in these BE condensates almost at the nucleon scale and a correspondin

Ioannis Papadimitriou

We determine the general structure of quantum anomalies for the $R$-multiplet of four dimensional $\mathcal{N}=1$ supersymmetric quantum field theories in the presence of background fields for an arbitrary number of Abelian flavor multiplets. By solving the Wess-Zumino consistency conditions for off-shell new minimal supergravity in four dimensions with an a

Runjie Lily Xu, Miguel Munoz Rojo, S. M. Islam, Aditya Sood

Aluminum nitride (AlN) plays a key role in modern power electronics and deep-ultraviolet photonics, where an understanding of its thermal properties is essential. Here we measure the thermal conductivity of crystalline AlN by the 3$ω$ method, finding it ranges from 674 ${\pm}$ 56 W/m/K at 100 K to 186 ${\pm}$ 7 W/m/K at 400 K, with a value of 237 ${\pm}$ 6 W

William J. Henney, S. J. Arthur

Stellar bow shocks, bow waves, and dust waves all result from the action of a star&#39;s wind and radiation pressure on a stream of dusty plasma that flows past it. The dust in these bows emits prominently at mid-infrared wavelengths in the range 8 to 60 micron. We propose a novel diagnostic method, the tau-eta diagram, for analyzing these bows, which is bas

Shiping Cao, Hua Qiu

We consider the Sobolev type spaces $H^σ(K)$ with $σ\geq 0$, where $K$ is a post-critically finite self-similar set with the natural boundary. Firstly, we compare different classes of Sobolev spaces $H^σ_N(K),H^σ_D(K)$ and $H^σ(K)$, {and observe} a sequence of critical orders of $σ$ in our comparison theorem. Secondly, We present a general atomic decompositi

Michael R. Walker, Joseph A. O&#39;Sullivan

The significance of the broken ray transform (BRT) is due to its occurrence in a number of modalities spanning optical, x-ray, and nuclear imaging. When data are indexed by the scatter location, the BRT is both linear and shift invariant. Analyzing the BRT as a linear system provides a new perspective on the inverse problem. In this framework we contrast pri

Hauyu Baobab Liu

Previous (sub)millimeter observations have found that the spectral indices of dust emission from some young stellar objects are lower than that of the black body emission in the Rayleigh-Jeans limit (i.e., 2.0). In particular, the recent Atacama Large Millimeter Array observations have spatially resolved that the innermost regions of the protoplanetary disks

Chengsheng Mao, Liang Yao, Yuan Luo

Laboratory testing and medication prescription are two of the most important routines in daily clinical practice. Developing an artificial intelligence system that can automatically make lab test imputations and medication recommendations can save costs on potentially redundant lab tests and inform physicians of a more effective prescription. We present an i

Chengsheng Mao, Liang Yao, Yuan Luo

Image representation is a fundamental task in computer vision. However, most of the existing approaches for image representation ignore the relations between images and consider each input image independently. Intuitively, relations between images can help to understand the images and maintain model consistency over related images, leading to better explaina

Gisele Detomazi Almeida, Fabrício Cristófani, Fábio Natali

In this paper, we present the first result concerning the orbital stability of periodic traveling waves for the modified Kawahara equation. Our method is based on the Fourier expansion of the periodic wave in order to know the behaviour of the nonpositive spectrum of the associated linearized operator around the periodic wave combined with a recent developme

Toshimichi Usuba

We construct a normal countably tight $T_1$ space $X$ with $t(X_δ) >2^ω$. This is an answer to the question posed by Dow-Juhász-Soukup-Szentmiklóssy-Weiss. We also show that if the continuum is not so large, then the tightness of $G_δ$-modifications of countably tight spaces can be arbitrary large up to the least $ω_1$-strongly compact cardinal.

Juan Pablo Acosta López

We determine all groups definable in Presburger arithmetic, up to a finite index subgroup.

Patrick Rodler, Michael Eichholzer

When ontologies reach a certain size and complexity, faults such as inconsistencies, unsatisfiable classes or wrong entailments are hardly avoidable. Locating the incorrect axioms that cause these faults is a hard and time-consuming task. Addressing this issue, several techniques for semi-automatic fault localization in ontologies have been proposed. Often,

Elman Mansimov, Omar Mahmood, Seokho Kang, Kyunghyun Cho

A molecule&#39;s geometry, also known as conformation, is one of a molecule&#39;s most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has with other molecules. Conventional conformation generation methods minimize hand-designed molecular force field energy functions that are often not well corr

Xilai Li, Yingbo Zhou, Tianfu Wu, Richard Socher

Addressing catastrophic forgetting is one of the key challenges in continual learning where machine learning systems are trained with sequential or streaming tasks. Despite recent remarkable progress in state-of-the-art deep learning, deep neural networks (DNNs) are still plagued with the catastrophic forgetting problem. This paper presents a conceptually si

Manish Kumar, Rajneesh Bhardwaj

We numerically and experimentally investigate evaporation of a sessile droplet on a heated substrate. We develop a finite element (FE) model in two-dimensional axisymmetric coordinates to solve coupled transport of heat in the droplet and substrate, and of the mass of liquid vapor in surrounding ambient while assuming diffusion-limited, quasi-steady evaporat

L. Grineviciute, T. Tolenis, M. Ryu, T. Moein

A simple procedure is demonstrated for fabrication of waveplates which can be released from substrate by laser cutting. Oblique angle deposition, chemical etching and laser inscription steps were used for the final lift-off and release of micro-waveplates in HCl solution.

José-María Hidalgo-Arteaga, Fiodar Hancharou, Florian Thams, Spyros Chatzivasileiadis

Security assessment is among the most fundamental functions of power system operator. The sheer complexity of power systems exceeding a few buses, however, makes it an extremely computationally demanding task. The emergence of deep learning methods that are able to handle immense amounts of data, and infer valuable information appears as a promising alternat

Laxman K. Malla, Rajneesh Bhardwaj, Adrian Neild

We experimentally investigate the profile and morphology of the ring-like deposits obtained after evaporation of a sessile water droplet containing polystyrene colloidal particles on a hydrophilic glass substrate. In particular, the coupled effect of particle size and concentration are studied. The deposits were qualitatively visualized under an optical micr

Nagesh D. Patil, Rajneesh Bhardwaj

Understanding flow patterns and coupled transport phenomena during evaporation of droplets loaded with colloidal particles is central to design technical applications such as organizing proteins/DNA on a solid surface. We review recent reports on evaporating sessile droplets of colloidal suspensions on a solid surface. Starting from the classical mechanism o

Saeed Naif Turki Al-Rashid, Mohammed A. Z. Habeeb, Stephan LeBohec

Applying the resolution-scale relativity principle to develop a mechanics of non-differentiable dynamical paths, we find that, in one dimension, stationary motion corresponds to an Ito process driven by the solutions of a Riccati equation. We verify that the corresponding Fokker-Planck equation is solved for a probability density corresponding to the squared

Michael Romanovsky

We consider distributions of scientific journals impact factor. Analysing 9028 scientific journals with the largest impact factors, we found that the distribution of them is year-to-year stable (at least for analysed 2011-2013 years), and it has the character of the exponential Boltzmann distribution with the power law asymptotic (tail).

Arnesh Sen, Jayoti Das

The Band to Band tunneling probability strongly depends on the shape of the potential barrier. However, parabolic approximation of this shape is well acceptable but unfortunately significant amount of error is unavoidable by using quadratic polynomial in calculation of tunneling probability. De Casteljaus algorithm, followed by Bezier Curve can be modeled to

Thomas Baden-Riess

We study 4 problems in the area of scattering of time harmonic acoustic or electromagnetic waves by unbounded rough surfaces/inhomogeneous layers. Specifically we study: i) a boundary value problem (BVP) for the Helmholtz equation, in both 2 and 3 dimensions, modelling scattering of time harmonic waves due to a source that lies within a finite distance of th

Arnesh Sen, Aishik Das, Jayoti Das

The positions of poles and zeros of a filter circuit indicates how the system behaves with variation in frequency as well as it results a tool to utilize the system gain by setting the frequency range in a complex process. The existing solutions to extract the poles and zeros often include too complex calculations to use it frequently. In this paper we propo

Thai-Son Nguyen, Sebastian Stueker, Alex Waibel

In this work, we learn a shared encoding representation for a multi-task neural network model optimized with connectionist temporal classification (CTC) and conventional framewise cross-entropy training criteria. Our experiments show that the multi-task training not only tackles the complexity of optimizing CTC models such as acoustic-to-word but also result

S. Ramkumar, C. Ganesa Moorthy

Magill proved that the remainders of two locally compact Hausdorff spaces in their StoneCech compactifications are homeomorphic if and only if the lattices of their Hausdorff compactifications are lattice isomorphic. His construction for compactifications are explicitely discussed through the partitions of their StoneCech compactifications. Partitions in a S