October 2020 arXiv papers — page 97

Hao Zhang

A self-packaged dual-band bandpass filter (DBBPF) with high isolation and low insertion loss (IL) for 5G applications is proposed in this paper. To get high stopband suppression, multiple and controllable transmission zeros (TZs) are produced. This novel DBBPF is designed with a pair of quarter-wavelength stepped-impedance resonators (QSIRs) and a half-wavel

Félix del Teso, David Gómez-Castro, Juan Luis Vázquez

We introduce three representation formulas for the fractional $p$-Laplace operator in the whole range of parameters $0<s<1$ and $1<p<\infty$. Note that for $p\ne 2$ this a nonlinear operator. The first representation is based on a splitting procedure that combines a renormalized nonlinearity with the linear heat semigroup. The second adapts the nonlinearity

Chuhan Wu, Fangzhao Wu, Yongfeng Huang

Transformer has achieved great success in the NLP field by composing various advanced models like BERT and GPT. However, Transformer and its existing variants may not be optimal in capturing token distances because the position or distance embeddings used by these methods usually cannot keep the precise information of real distances, which may not be benefic

Therese-Marie Landry, Michel L. Lapidus, Frederic Latremoliere

Noncommutative geometry provides a framework, via the construction of spectral triples, for the study of the geometry of certain classes of fractals. Many fractals are constructed as natural limits of certain sets with a simpler structure: for instance, the Sierpiński is the limit of finite graphs consisting of various affine images of an equilateral triangl

Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert

Path planning methods for autonomous unmanned aerial vehicles (UAVs) are typically designed for one specific type of mission. This work presents a method for autonomous UAV path planning based on deep reinforcement learning (DRL) that can be applied to a wide range of mission scenarios. Specifically, we compare coverage path planning (CPP), where the UAV&#39

C. R. Woods, P. Ares, H. Nevison-Andrews, M. J. Holwill

When two-dimensional crystals are brought into close proximity, their interaction results in strong reconstruction of electronic spectrum and local crystal structure. Such reconstruction strongly depends on the twist angle between the two crystals and has received growing attention due to new interesting electronic and optical properties that arise in graphe

Victor V. Flambaum, Junlan Jin, Dmitry Budker

We present a possibility of direct resonance production of pionic atoms (Coulomb bound states of a negative pion and a nucleus) with a rate of up to $\sim10^{10}$ per second using the gamma-ray beams from the Gamma Factory.

Chia-Wei Tsai, Zong-Liang Zhang, Bo-Cheng Jian, Yao-Chung Chang

Due to the exiting semi-quantum secret sharing protocol have two challenges including (1) the dealer must be the quantum user, and (2) the classical users must equip with the Trojan Horse detectors, this study wants to propose a novel mediate semi-quantum secret sharing (MSQSS) protocol to let a classical dealer can share his/her secrets to the classical age

Erik Lindell

In the early 1980's, Johnson defined a homomorphism $\mathcal{I}_{g}^1\to\bigwedge^3 H_1(S_{g},\mathbb{Z})$, where $\mathcal{I}_{g}^1$ is the Torelli group of a closed, connected and oriented surface of genus $g$ with a boundary component and $S_g$ is the corresponding surface without a boundary component. This is known as the Johnson homomorphism. We study

Varun Ramamohan, Utkarsh Agrawal, Mohit Goyal

In this paper, we propose a relaxation to the stochastic ruler method originally described by Yan and Mukai in 1992 for asymptotically determining the global optima of discrete simulation optimization problems. The `original&#39; version of the stochastic ruler and its variants require that a candidate for the next estimate of the optimal solution pass a cer

Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu, Yonina C. Eldar

In autonomous driving, radar systems play an important role in detecting targets such as other vehicles on the road. Radars mounted on different cars can interfere with each other, degrading the detection performance. Deep learning methods for automotive radar interference mitigation can succesfully estimate the amplitude of targets, but fail to recover the

Nanyu Li, Charles C. Zhou

Compressed sensing (CS) is a challenging problem in image processing due to reconstructing an almost complete image from a limited measurement. To achieve fast and accurate CS reconstruction, we synthesize the advantages of two well-known methods (neural network and optimization algorithm) to propose a novel optimization inspired neural network which dubbed

Dario Marvin, Lorenzo Nespoli, Davide Strepparava, Vasco Medici

The ability to forecast the concentration of air pollutants in an urban region is crucial for decision-makers wishing to reduce the impact of pollution on public health through active measures (e.g. temporary traffic closures). In this study, we present a machine learning approach applied to the forecast of the day-ahead maximum value of the ozone concentrat

Jirawat Saiphet, Sujin Suwanna, André R. R. Carvalho, Areeya Chantasri

The no-knowledge quantum feedback was proposed by Szigeti et al., Phys. Rev. Lett. 113, 020407 (2014), as a measurement-based feedback protocol for decoherence suppression for an open quantum system. By continuously measuring environmental noises and feeding back controls on the system, the protocol can completely reverse the measurement backaction and there

Petr Pelech, Karel Tuma, Michal Pavelka, Martin Sipka

Within the framework of natural configurations developed by Rajagopal and Srinivasa, evolution within continuum thermodynamics is formulated as evolution of a natural configuration linked with the current configuration. On the other hand, withing the General Equation for Non-Equilibrium Reversible-Irreversible Coupling (GENERIC) framework, the evolution is s

Siba Prasad Acharya, Abhik Mukherjee, Mylavarapu Sita Janaki

We consider a low temperature plasma environment in the Low Earth Orbital (LEO) region in presence of charged space debris particles. The dynamics of (2+1) dimensional nonlinear dust ion acoustic waves with weak transverse perturbation, generated in the system is found to be governed by a forced Kadomtsev-Petviashvili (KP) equation, where the forcing term de

Christopher Hahne, Amar Aggoun

Light-field cameras play a vital role for rich 3-D information retrieval in narrow range depth sensing applications. The key obstacle in composing light-fields from exposures taken by a plenoptic camera is to computationally calibrate, align and rearrange four-dimensional image data. Several attempts have been proposed to enhance the overall image quality by

Gabriele Moreno Berton, Valerio Paolicelli, Carlo Masone, Barbara Caputo

We address the task of cross-domain visual place recognition, where the goal is to geolocalize a given query image against a labeled gallery, in the case where the query and the gallery belong to different visual domains. To achieve this, we focus on building a domain robust deep network by leveraging over an attention mechanism combined with few-shot unsupe

Daniel Potts, Manfred Tasche

In this paper, we study the error behavior of the nonequispaced fast Fourier transform (NFFT). This approximate algorithm is mainly based on the convenient choice of a compactly supported window function. Here we consider the continuous Kaiser--Bessel, continuous $\exp$-type, $\sinh$-type, and continuous $\cosh$-type window functions with the same support an

Zhi Hu, Pengfei Huang, Runhong Zong

In this paper, we generalize the construction of Deligne-Hitchin twistor space by gluing two certain Hodge moduli spaces. We investigate such generalized Deligne-Hitchin twistor space as a complex analytic manifold. More precisely, we show it admits holomorphic sections with weight-one property and semi-negative energy, and it carries a balanced metric, and

Gongjun Choi, Tsutomu T. Yanagida, Norimi Yokozaki

We present a model describing the dark sector (DS) featured by two interactions remaining efficient until late times in the matter-dominated era after recombination: the interaction among dark radiations (DR), and the interaction between a small fraction of dark matter and dark radiation. The dark sector consists of (1) a dominant component cold collisionles

Qingyang Wu, Zhenzhong Lan, Kun Qian, Jing Gu

Transformers have reached remarkable success in sequence modeling. However, these models have efficiency issues as they need to store all the history token-level representations as memory. We present Memformer, an efficient neural network for sequence modeling, that utilizes an external dynamic memory to encode and retrieve past information. Our model achiev

Mariusz Puchalski, Jacek Komasa, Krzysztof Pachucki

We perform the four-body calculation of the hyperfine structure in the first rotational state $J=1$ of the H$_2$, D$_2$, and HD molecules and determine the accurate value for the deuteron electric quadrupole moment $Q_d = 0.285\,699(15)(18)$ fm$^2$ in significant disagreement with former spectroscopic determinations. Our results for the hyperfine parameters

Hui Li

Disruptive changes in vehicles and transportation have been triggered by automated, connected, electrified and shared mobility. Autonomous vehicles, like Internet data packets, are transported from one address to another through the road network. The Internet has become a general network transmission paradigm, and the Energy Internet is a successful applicat

Naoki Seto

With the recent strong developments of TianQin and Taiji, we now have an increasing chance to make a correlation analysis in the mHz band by operating them together with LISA. Assuming two LISA-like triangular detectors at general geometrical configurations, we develop a simple formulation to evaluate the network sensitivity to an isotropic gravitational wav

Holger Boche, Christian Deppe

Zero-error capacity plays an important role in a whole range of operational tasks, in addition to the fact that it is necessary for practical applications. Due to the importance of zero-error capacity, it is necessary to investigate its algorithmic computability, as there has been no known closed formula for the zero-error capacity until now. We show that th

Timothy Farnworth, Christopher Renton, Reuben Strydom, Adrian Wills

Machine vision is an important sensing technology used in mobile robotic systems. Advancing the autonomy of such systems requires accurate characterisation of sensor uncertainty. Vision includes intrinsic uncertainty due to the camera sensor and extrinsic uncertainty due to environmental lighting and texture, which propagate through the image processing algo

Moming Duan, Duo Liu, Xinyuan Ji, Renping Liu

Federated Learning (FL) enables the multiple participating devices to collaboratively contribute to a global neural network model while keeping the training data locally. Unlike the centralized training setting, the non-IID and imbalanced (statistical heterogeneity) training data of FL is distributed in the federated network, which will increase the divergen

Louisiane Devaud, Bernhard Rauer, Jakob Melchard, Matthias Kühmayer

Speckle patterns are ubiquitous in optics and have multiple applications for which the control of their spatial correlations is essential. Here, we report on a method to engineer speckle correlations behind a scattering medium through the singular value decomposition of the transmission matrix. We not only demonstrate control over the speckle grain size and

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, André Susano Pinto

In the low-data regime, it is difficult to train good supervised models from scratch. Instead practitioners turn to pre-trained models, leveraging transfer learning. Ensembling is an empirically and theoretically appealing way to construct powerful predictive models, but the predominant approach of training multiple deep networks with different random initia

Tom Vincent-Dospital, Alain Cochard, Stéphane Santucci, Knut Jørgen Måløy

We present a subcritical fracture growth model, coupled with the elastic redistribution of the acting mechanical stress along rugous rupture fronts. We show the ability of this model to quantitatively reproduce the intermittent dynamics of cracks propagating along weak disordered interfaces. To this end, we assume that the fracture energy of such interfaces

Cheng Zhao, Lei Guo

As is well-known, the classical PID control plays a dominating role in various control loops of industrial processes. However, a theory that can explain the rationale why the linear PID can successfully deal with the ubiquitous uncertain nonlinear dynamical systems and a method that can provide explicit design formulae for the PID parameters are still lackin

Rémi Carles, Van Duong Dinh, Hichem Hajaiej

We consider a two-dimensional nonlinear Schr{\"o}dinger equation proposed in Physics to model rotational binary Bose-Einstein condensates. The nonlinearity is a logarithmic modification of the usual cubic nonlinearity. The presence of both the external confining potential and rotating frame makes it difficult to apply standard techniques to directly construc

Adrien Prodhomme

Density-dependent Markov chains form an important class of continuous-time Markov chains in population dynamics. On any fixed time window [0, T ], when the scale parameter K > 0 is large such chains are well approximated by the solution of an ODE (the fluid limit), with Gaussian fluctuations superimposed upon it. In this paper we quantify the period of time

Hui Liu, Bo Zhao, Minzhi Ji, Peng Liu

Adversarial examples are well-designed input samples, in which perturbations are imperceptible to the human eyes, but easily mislead the output of deep neural networks (DNNs). Existing works synthesize adversarial examples by leveraging simple metrics to penalize perturbations, that lack sufficient consideration of the human visual system (HVS), which produc

R David Mayrhofer, Cyril Elouard, Janine Splettstoesser, Andrew N Jordan

We analyze a steady-state thermoelectric engine, whose working substance consists of two capacitively coupled quantum dots. One dot is tunnel-coupled to a hot reservoir serving as a heat source, the other one to two electrically biased reservoirs at a colder temperature, such that work is extracted under the form of a steady-state current against the bias. I

Kangqiang Li, Han Bao, Lixin Zhang

Fan et al. [$\mathit{Annals}$ $\mathit{of}$ $\mathit{Statistics}$ $\textbf{47}$(6) (2019) 3009-3031] constructed a distributed principal component analysis (PCA) algorithm to reduce the communication cost between multiple servers significantly. However, their algorithm&#39;s guarantee is only for sub-Gaussian data. Spurred by this deficiency, this paper enha

Jun Zhang, Chen Gao, Depeng Jin, Yong Li

Group buying, as an emerging form of purchase in social e-commerce websites, such as Pinduoduo, has recently achieved great success. In this new business model, users, initiator, can launch a group and share products to their social networks, and when there are enough friends, participants, join it, the deal is clinched. Group-buying recommendation for socia

Andreas Hauptmann, Danny Smyl

Electrical and elasticity imaging are promising modalities for a suite of different applications including medical tomography, non-destructive testing, and structural health monitoring. These emerging modalities are capable of providing remote, non-invasive, and low cost opportunities. Unfortunately, both modalities are severely ill-posed nonlinear inverse p

Jotsaroop Kaur, Saurabh Shrivastava

We establish improved and sharp $L^p$ estimates for the maximal bilinear Bochner-Riesz means in all dimensions $n\geq 1$. This work extends the results proved by Jeong and Lee \cite{JL}. We also recover the known results for the bilinear Bochner-Riesz means. The method of proof involves a new decomposition of the bilinear Bochner-Riesz multiplier $(1-|ξ|^2-|

Christian Tarsney, Teruji Thomas

Is the overall value of a world just the sum of values contributed by each value-bearing entity in that world? Additively separable axiologies (like total utilitarianism, prioritarianism, and critical level views) say 'yes', but non-additive axiologies (like average utilitarianism, rank-discounted utilitarianism, and variable value views) say 'no'. This dist

Shengxiang Wu, Oscar Hsu-Cheng Cheng, Boqin Zhao, Nicki Hogan

Recent studies have established that the anti-Stokes Raman signal from plasmonic metal nanostructures can be used to determine the two separate temperatures that characterize carriers inside the metal -- the temperature of photoexcited &#34;hot carriers&#34; and carriers that are thermalized with the metal lattice. However, the related signal in the Stokes s

Zhi Hu, Pengfei Huang

In this paper, we prove that for the oper stratification of the de Rham moduli space $M_{\mathrm{dR}}(X,r)$, the closed oper stratum is the unique minimal stratum with dimension $r^2(g-1)+g+1$, and the open dense stratum consisting of irreducible flat bundles with stable underlying vector bundles is the unique maximal stratum.

Morgan Jones, Matthew M. Peet

For any suitable Optimal Control Problem (OCP) there exists a value function, defined as the unique viscosity solution to the Hamilton-Jacobi-Bellman (HJB) Partial-Differential-Equation (PDE), and which can be used to design an optimal feedback controller for the given OCP. In this paper, we approximately solve the HJB-PDE by proposing a sequence of Sum-Of-S

Jiangtao Wang, Jian-Ning Fu, Weikai Zong, M. C. Smith

The LAMOST-\textit{K}2 (L\textit{K}2) project, initiated in 2015, aims to collect low-resolution spectra of targets in the \textit{K}2 campaigns, similar to LAMOST-\textit{Kepler} project. By the end of 2018, a total of 126 L\textit{K}2 plates had been observed by LAMOST. After cross-matching the catalog of the LAMOST data release 6 (DR6) with that of the \t

Nguyen Huynh Duy Khang, Pham Nam Hai

We proposed and demonstrated a simple method for detection of in-plane magnetization switching by spin-orbit torque (SOT) in bilayers of non-magnetic / magnetic materials. In our method, SOT is used not only for magnetization switching but also for detection. Our method can detect arbitrary Mx and My component without an external magnetic field, which is use

Martijn P. A. Starmans, Milea J. M. Timbergen, Melissa Vos, Michel Renckens

Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA,BRAF mutational status

Faeze Brahman, Snigdha Chaturvedi

Emotions and their evolution play a central role in creating a captivating story. In this paper, we present the first study on modeling the emotional trajectory of the protagonist in neural storytelling. We design methods that generate stories that adhere to given story titles and desired emotion arcs for the protagonist. Our models include Emotion Supervisi

Sunil Bhatt, Ankit Butola, Sheetal Raosaheb Kanade, Anand Kumar

White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts are essentially required in WL-PSIM for measuring the accurate phase of the object. Here, we present single-shot phase-sh

Huizhang Yang, Mingliang Tao, Shengyao Chen, Feng Xi

Since by the International Telecommunications Union (ITU) regulatory the radio spectrum available to spaceborne synthetic aperture radar (SAR) is restricted to certain limited frequency intervals, there are many different spaceborne SAR systems sharing common frequency bands. Due to this reason, it is reported that two spaceborne SARs at orbit cross position

Hossein Lamei Ramandi, Stevo Todorcevic

We consider a transitive relation on the power set of $\omega_1$ and show if there is a maximal element with respect to this relation then there is a Kurepa tree with no Aronszajn subtree. We also show that if there is a maximal subset of $\omega_1$, then there are Kurepa trees which are not club isomorphic. These maximal subsets of $\omega_1$ exist in many

Mahmoud Hossam, Trung Le, He Zhao, Dinh Phung

Training robust deep learning models for down-stream tasks is a critical challenge. Research has shown that down-stream models can be easily fooled with adversarial inputs that look like the training data, but slightly perturbed, in a way imperceptible to humans. Understanding the behavior of natural language models under these attacks is crucial to better d

Zhenan Fan, Halyun Jeong, Babhru Joshi, Michael P. Friedlander

The signal demixing problem seeks to separate a superposition of multiple signals into its constituent components. This paper studies a two-stage approach that first decompresses and subsequently deconvolves the noisy and undersampled observations of the superposition using two convex programs. Probabilistic error bounds are given on the accuracy with which

V. Sharma, L. Singh, H. T. Wong, M. Agartioglu

Neutrino-nucleus elastic scattering ($ν{\rm A}_{el}$) provides a unique laboratory to study the quantum-mechanical (QM) coherency effects in electroweak interactions. The deviations of the cross-sections from those of completely coherent systems can be quantitatively characterized through a coherency parameter $α( q^2 )$. The relations between $α$ and the un

Kenshiro Tashiro

In this paper, we show that every collapsed Gromov--Hausdorff limit of compact Heisenberg manifolds is isometric to a flat torus. Here we say that a sequence of sub-Riemannian manifolds collapses if their total measure with respect to the Popp's volume or the minimal Popp's volume converges to zero. In the appendix, we give the systolic inequality on sub-Rie

Nan Xu, Yanjun Huang, Hassan Askari, Zepeng Tang

Tire slip angle is a vital parameter in tire/vehicle dynamics and control. This paper proposes an accurate estimation method by the fusion of intelligent tire technology and machine-learning techniques. The intelligent tire is equipped by MEMS accelerometers attached to its inner liner. First, we describe the intelligent tire system along with the implemente

Liang Ding, Xiaowei Zhang

Stochastic kriging has been widely employed for simulation metamodeling to predict the response surface of complex simulation models. However, its use is limited to cases where the design space is low-dimensional because, in general, the sample complexity (i.e., the number of design points required for stochastic kriging to produce an accurate prediction) gr

Kelum Gajamannage

With the proliferation of sophisticated cameras in modern society, the demand for accurate and visually pleasing images is increasing. However, the quality of an image captured by a camera may be degraded by noise. Thus, some processing of images is required to filter out the noise without losing vital image features. Even though the current literature offer

Dan Peng, Ming Li

It is known that the small-world structure constitutes sufficient conditions to sustain cooperation and thus enhances cooperation. On the contrary, the network with a very long average distance is usually thought of as suppressing the emergence of the cooperation. In this paper we show that the fractal structure, of which the average distance is very long, d

Mingyu Cai, Shaoping Xiao, Baoluo Li, Zhiliang Li

This paper presents a model-free reinforcement learning (RL) algorithm to synthesize a control policy that maximizes the satisfaction probability of linear temporal logic (LTL) specifications. Due to the consideration of environment and motion uncertainties, we model the robot motion as a probabilistic labeled Markov decision process with unknown transition

Roya Beheshti, Brian Lehmann, Eric Riedl, Sho Tanimoto

We prove several classification results for the components of the moduli space of rational curves on a smooth Fano threefold. In particular, we prove a conjecture of Batyrev on the growth of the number of components as the degree increases. The key to our approach is Geometric Manin&#39;s Conjecture which predicts the number of components parameterizing free

Feiran Zhao, Keyou You

Stochastic optimal control usually requires an explicit dynamical model with probability distributions, which are difficult to obtain in practice. In this work, we consider the linear quadratic regulator (LQR) problem of unknown linear systems and adopt a Wasserstein penalty to address the distribution uncertainty of additive stochastic disturbances. By cons

Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu

Given a document and a target aspect (e.g., a topic of interest), aspect-based abstractive summarization attempts to generate a summary with respect to the aspect. Previous studies usually assume a small pre-defined set of aspects and fall short of summarizing on other diverse topics. In this work, we study summarizing on arbitrary aspects relevant to the do

Yizhu Wang, Wenyi Zhang

It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minimum Euclidean distance between a codeword and the received channel output vector, is the maximum likelihood solution and hence capacity-achieving. Nearest neighbor decoding remains a convenient and yet mismatched solution for general channels, and the key messa

Bin Pei, Yuzuru Inahama, Yong Xu

This paper is devoted to studying the averaging principle for fast-slow system of rough differential equations driven by mixed fractional Brownian rough path. The fast component is driven by Brownian motion, while the slow component is driven by fractional Brownian motion with Hurst index $H ~(1/3 < H\leq 1/2)$. Combining the fractional calculus approach to

Fereshteh Jafariakinabad, Kien A. Hua

Syntactic structure of sentences in a document substantially informs about its authorial writing style. Sentence representation learning has been widely explored in recent years and it has been shown that it improves the generalization of different downstream tasks across many domains. Even though utilizing probing methods in several studies suggests that th

Peiyao Sheng, Gerui Wang, Kartik Nayak, Sreeram Kannan

Byzantine fault-tolerant (BFT) protocols allow a group of replicas to come to a consensus even when some of the replicas are Byzantine faulty. There exist multiple BFT protocols to securely tolerate an optimal number of faults $t$ under different network settings. However, if the number of faults $f$ exceeds $t$ then security could be violated. In this paper

Michael J. Catanzaro, Vladimir Y. Chernyak, John R. Klein

We introduce the notion of a protocol, which consists of a space whose points are labeled by real numbers indexed by the set of cells of a fixed CW complex in prescribed degrees, where the labels are required to vary continuously. If the space is a one-dimensional manifold, then a protocol determines a continuous time Markov chain. When a homological gap con

Shuning Tan, Yiqun Liu, Yingping Mou, Shiping Feng

The recent experiments revealed a remarkable possibility for the absence of the disparity between the phase diagrams of the electron- and hole-doped cuprate superconductors, while such an aspect should be also reflected in the dressing of the electrons. Here the phase diagram of the electron-doped cuprate superconductors and the related exotic features of th

Yuwen Li, Ludmil T. Zikatanov

We introduce and explain key relations between a posteriori error estimates and subspace correction methods viewed as preconditioners for problems in infinite dimensional Hilbert spaces. We set the stage using the Finite Element Exterior Calculus and Nodal Auxiliary Space Preconditioning. This framework provides a systematic way to derive explicit residual e

Vladimir Dragovic, Sean Gasiorek, Milena Radnovic

We consider billiard systems within compact domains bounded by confocal conics on a hyperboloid of one sheet in the Minkowski space. We derive conditions for elliptic periodicity for such billiards. We describe the topology of those billiard systems in terms of Fomenko invariants. We provide then periodicity conditions in terms of functional Pell equations a

Ken-ji Hamada

We study a series of the Wess-Zumino actions obtained by repeatedly integrating conformal anomalies with respect to the conformal-factor field that appear at higher loops. We show that they arise as physical quantities required to make nonlocal loop correction terms diffeomorphism invariant. Specifically, in a conformally flat spacetime $ds^2=e^{2ϕ}(-dη^2 +

Adie Tri Hanindriyo, Amit Kumar Singh Yadav, Tom Ichibha, Ryo Maezono

The disiloxane molecule is a prime example of silicate compounds containing the Si-O-Si bridge. The molecule is of significant interest within the field of quantum chemistry, owing to the difficulty in theoretically predicting its properties. Herein, the linearisation barrier of disiloxane is investigated using a fixed-node diffusion Monte Carlo (FNDMC) appr

J. J. Grimmett, Bernhard Müller, Alexander Heger, Projjwal Banerjee

Hypernovae powered by magnetic jets launched from the surface of rapidly rotating millisecond magnetars are one of the leading models to explain broad-lined Type Ic supernovae (SNe Ic-BL), and have been implicated as an important source of metal enrichment in the early Universe. We investigate the nucleosynthesis in such jet-driven hypernovae using a paramet

Yu Qiang, Junchen Pei, Paul Stevenson

Energy dependence of fission observables is a key issue for wide nuclear applications. We studied real-time fission dynamics from low-energy to high excitations in the compound nucleus $^{240}$Pu with the time-dependent Hartree-Fock+BCS approach. It is shown that the evolution time of the later phase of fission towards scission is considerably lengthened at

Hang Shuai, Fangxing, Li

Natural disasters such as storms usually bring significant damages to distribution grids. This paper investigates the optimal routing of utility vehicles to restore outages in the distribution grid as fast as possible after a storm. First, the poststorm repair crew dispatch task with multiple utility vehicles is formulated as a sequential stochastic optimiza

Joseph McDonald, Kentaro Yamamoto

The existing topological representation of an orthocomplemented lattice via the clopen orthoregular subsets of a Stone space depends upon Alexander&#39;s Subbase Theorem, which asserts that a topological space $X$ is compact if every subbasic open cover of $X$ admits of a finite subcover. This is an easy consequence of the Ultrafilter Theorem - whose proof d

Diego M. Rodrigues, Danning Li, Eduardo Folco Capossoli, Henrique Boschi-Filho

In this work we study finite density effects in spontaneous chiral symmetry breaking as well as chiral phase transition under the influence of a background magnetic field in $ 2+1 $ dimensions. For this purpose, we use an improved holographic softwall model based on an interpolated dilaton profile. We find inverse magnetic catalysis at finite density. We obs

Faustin Adiceam

A 1965 problem due to Danzer asks whether there exists a set with finite density in Euclidean space intersecting any convex body of volume one. A suitable weakening of the volume constraint leads to the (much more recent) problem of constructing \emph{dense forests}. These are discrete point sets getting uniformly close to long enough line segments. Progress

Matthew L. Leavitt, Ari Morcos

Representational sparsity is known to affect robustness to input perturbations in deep neural networks (DNNs), but less is known about how the semantic content of representations affects robustness. Class selectivity-the variability of a unit&#39;s responses across data classes or dimensions-is one way of quantifying the sparsity of semantic representations.

D. Michilli, K. W. Masui, R. Mckinven, D. Cubranic

The Canadian Hydrogen Intensity Mapping Experiment (CHIME) has become a leading facility for detecting fast radio bursts (FRBs) through the CHIME/FRB backend. CHIME/FRB searches for fast transients in polarization-summed intensity data streams that have 24-kHz spectral and 1-ms temporal resolution. The intensity beams are pointed to pre-determined locations

Rollin Omari, R. I. McKay, Tom Gedeon

Raven&#39;s Progressive Matrices have been widely used for measuring abstract reasoning and intelligence in humans. However for artificial learning systems, abstract reasoning remains a challenging problem. In this paper we investigate how neural networks augmented with biologically inspired spiking modules gain a significant advantage in solving this proble

Shang Gao, Ling-Fang Lin, Andrew F. May, Binod K. Rai

Spin-1/2 chains with alternating antiferromagnetic (AF) and ferromagnetic (FM) couplings exhibit quantum entanglement like the integer-spin Haldane chains and might be similarly utilized for quantum computations. Such alternating AF-FM chains have been proposed to be realized in the distorted honeycomb-lattice compound Na$_2$Cu$_2$TeO$_6$, but to confirm thi

Selma Rizvic, Dusanka Boskovic, Vensada Okanovic, Sanda Sljivo

Interactive digital storytelling becomes a popular choice for information presentation in many fields. Its application spans from media industry and business information visualization, through digital cultural heritage, serious games, education, to contemporary theater and visual arts. The benefits of this form of multimedia presentation in education are gen

Evangelos Mitsakis, Areti Kotsi, Vasileios Psonis

Cooperative Intelligent Transportation Systems (C-ITS) enable vehicles communication with each other (Vehicle-to-Vehicle, V2V) and with roadside infrastructure (Vehicle-to-Infrastructure, V2I). In the context of traffic efficiency, C-ITS technologies could assist in road network status visualization and monitoring, through data exchange, improving this way t

Peter Howard

Working with a general class of linear Hamiltonian systems specified on $\mathbb{R}$, we develop a framework for relating the Maslov index to the number of eigenvalues the systems have on intervals of the form $[λ_1, λ_2)$ and $(-\infty, λ_2)$. We verify that our framework can be implemented for Sturm-Liouville systems, fourth-order potential systems, and a

Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer

Federated Learning (FL) is a decentralized machine learning protocol that allows a set of participating agents to collaboratively train a model without sharing their data. This makes FL particularly suitable for settings where data privacy is desired. However, it has been observed that the performance of FL is closely tied with the local data distributions o

Jakob Krzyston, Rajib Bhattacharjea, Andrew Stark

Transceivers used for telecommunications transmit and receive specific modulation patterns that are represented as sequences of complex numbers. Classifying modulation patterns is challenging because noise and channel impairments affect the signals in complicated ways such that the received signal bears little resemblance to the transmitted signal. Although

Tarek Saanouni

This note studies the asymptotic behavior of global solutions to the fourth-order Schrödinger equation $$i\dot u+Δ^2 u+F(x,u)=0 .$$ Indeed, for both cases, local and non-local source term, the scattering is obtained in the focusing mass super-critical and energy sub-critical regimes, with radial setting. This work uses a new approach due to Dodson-Murphy \ci

Charis Chalkiadakis, Panagiotis Iordanopoulos, Evangelos Mitsakis

Intelligent Transport Systems (ITS) and Cooperative Intelligent Transport Systems (C-ITS) are of high significance, mainly due to the benefits they have in terms of operation of the transport network. Despite ITS and C-ITS importance in the operation of the transport network, there is a major knowledge gap regarding their development, way of operation and si

Georgia Aifantopoulou, Chrysostomos Mylonas, Alexandros Dolianitis, Afroditi Stamelou

Intelligent Transport Systems (ITS) constitute a core representative of a paradigm shift in the transport sector. The extent to which the transport sector has adapted itself to this digital era relies considerably on the availability of suitable and reliable data. Currently, several data-related limitations, such as the scarcity of available datasets, hinder

Olasupo O. Ajayi, Antoine B. Bagula, Hloniphani M. Maluleke

It is widely recognised that collaboration can help fast-track the development of countries in Africa. Leveraging on the fourth industrial revolution, Africa can achieve accelerated development in health care services, educational systems and socio-economic infrastructures. While a number of conceptual frameworks have been proposed for the African continent,

Justin B. King

This paper presents a simple and accurate method for the inclusion of linear, time-invariant (LTI) networks, described by RF frequency-domain data, within equivalent baseband time-domain simulations. The time-domain representation is formulated as an equivalent baseband discrete-time impulse response, which may be convolved with the equivalent baseband form

Alexandre Moly, Alexandre Aksenov, Alim Louis Benabid, Tetiana Aksenova

Objective. Brain-computer interfaces (BCIs) create a new communication pathway between the brain and an effector without neuromuscular activation. BCI experiments highlighted high intra and inter-subjects variability in the BCI decoders. Although BCI model is generally relying on neurological markers generalizable on the majority of subjects, it requires to

Kallirroi N. Porfyri, Areti Kotsi, Evangelos Mitsakis

Cooperative Intelligent Transportation Systems (C-ITS) constitute technologies which enable vehicles to communicate with each other and with road infrastructure. Verification or testing is required for C-ITS applications, in order to assess their impact on traffic operation. In this work, a microscopic traffic simulation approach is used, to evaluate the imp

Sergey Rashkovskiy

We consider the thermodynamic approach to the description of economic systems and processes. The first and second laws of thermodynamics as applied to economic systems are derived and analyzed. It is shown that there is a deep analogy between the parameters of thermodynamic and economic systems (markets); in particular, each thermodynamic parameter can be as

Hironori Yoshioka, Tomonori Honda

A rough interface seems to be one of the possible reasons for low channel mobility (conductivity) in SiC MOSFETs. To evaluate the mobility by interface roughness, we drew a boundary line between amorphous insulator and crystalline 4H-SiC in a cross-sectional image obtained by a transmission electron microscope (TEM), by using the deep learning approach of co

Jeremy Georges-Filteau, Richard C. Hamelin, Mathieu Blanchette

Motivation The genotype assignment problem consists of predicting, from the genotype of an individual, which of a known set of populations it originated from. The problem arises in a variety of contexts, including wildlife forensics, invasive species detection and biodiversity monitoring. Existing approaches perform well under ideal conditions but are sensit

Xin Liu, Su Tian, Fei Tao, Haodong Du

Machine learning models are increasingly used in many engineering fields thanks to the widespread digital data, growing computing power, and advanced algorithms. Artificial neural networks (ANN) is the most popular machine learning model in recent years. Although many ANN models have been used in the design and analysis of composite materials and structures,

C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal

Scalable and cost-effective solutions to renewable energy storage are essential to addressing the world&#39;s rising energy needs while reducing climate change. As we increase our reliance on renewable energy sources such as wind and solar, which produce intermittent power, storage is needed to transfer power from times of peak generation to peak demand. Thi