September 2020 arXiv papers — page 12

Xiaoli Ma, Yimeng Wang, Yunyu Yin, Binbin Yue

Layered magnetic transition-metal thiophosphate NiPS3 has unique two-dimensional (2D) magnetic properties and electronic behavior. The electronic band structure and corresponding magnetic state are expected to sensitive to the interlayer interaction, which can be tuned by external pressure. Here, we report an insulator-metal transition accompanied with magne

Thomas L. Griffiths

Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may differ from artificial intelligence, by considering the characteristics of the kind of computational problems that

Alexander V. Poshakinskiy, Alexander N. Poddubny

We study theoretically the second-order correlation function $g^{(2)}(t)$ for photons transmitted through a periodic Bragg-spaced array of superconducting qubits, coupled to a waveguide. We demonstrate that photon bunching and anti-bunching persist much longer than both radiative and non-radiative lifetimes of a single qubit. The photon-photon correlations b

Jolantha Escrig, Lydie Bonal, Pierre Beck, Trygve Prestgard

Non-differentiated asteroids are among the most primitive objects in our Solar System, having escaped intense heating mechanisms. To help us understand the information contained in reflectance spectra measured on asteroids, we analyzed meteorites in the laboratory. We present an in-depth analysis of a large set of reflectance spectra: 23 CV3, 15 CO3, 4 CR2 a

G. H. Hilmarsson, L. G. Spitler, E. F. Keane, T. M. Athanasiadis

Superluminous supernovae (SLSNe) and long gamma ray bursts (LGRBs) have been proposed as progenitors of repeating Fast Radio Bursts (FRBs). In this scenario, bursts originate from the interaction between a young magnetar and its surrounding supernova remnant (SNR). Such a model could explain the repeating, apparently non-Poissonian nature of FRB121102, which

Peter Fettke, Wolfgang Reisig

Modern and next generation digital infrastructures are technically based on service oriented structures, cloud services, and other architectures that compose large systems from smaller subsystems. The composition of subsystems is particularly challenging, as the subsystems themselves may be represented in different languages, modelling methods, etc. It is qu

Minh C. Tran, Douglas C. Crockett, Phi A. Phan, Stephen J. Payne

We have created a lung simulation to quantify lung heterogeneity from the results of the inspired sinewave test (IST). The IST is a lung function test that is non-invasive, non-ionising and does not require patients' cooperation. A tidal lung simulation is developed to assess this test and also a method is proposed to calculate lung heterogeneity from IS

Bayan Karimi, Hans He, Yu-Cheng Chang, Libin Wang

We investigate the basic charge and heat transport properties of charge neutral epigraphene at sub-kelvin temperatures, demonstrating nearly logarithmic dependence of electrical conductivity over more than two decades in temperature. Using graphene's sheet conductance as in-situ thermometer, we present a measurement of electron-phonon heat transport at m

Lingyu Liu

In this paper we study a ratio-dependent predator-prey model with a free boundary causing by both prey and predator over a one dimensional habitat. We study the long time behaviors of the two species and prove a spreading-vanishing dichotomy, namely, as t goes to infinity, both prey and predator successfully spread to the whole space and survive in the new e

Ryota Kodama, Takeshi Go Tsuru, Takaaki Tanaka, Hiroyuki Uchida

We have been developing a new type of X-ray pixel sensors, "XRPIX", allowing us to perform imaging spectroscopy in the wide energy band of 1-20 keV for the future Japanese X-ray satellite "FORCE". The XRPIX devices are fabricated with complementary metal-oxide-semiconductor silicon-on-insulator technology, and have the "Event-Driven reado

Lorenzo Caprini, Umberto Marini Bettolo Marconi

We study a self-propelled particle moving in a solvent with the active Ornstein Uhlenbeck dynamics in the underdamped regime to evaluate the influence of the inertia. We focus on the properties of potential-free and harmonically confined underdamped active particles, studying how the single-particle trajectories modify for different values of the drag coeffi

Shuze Zhu, Emil Annevelink, Pascal Pochet, Harley T. Johnson

Interlayer rotation angle couples strongly to the electronic states of twisted van der Waals layers. However, not every angle is energetically favorable. Recent experiments on rotation-tunable electronics reveal the existence of a discrete set of angles at which the rotation-tunable electronics assume the most stable configurations. Nevertheless, a quantitat

S. Potin, P. Beck, L. Bonal, B. Schmitt

We present here several laboratory analyses performed on the freshly fallen Mukundpura CM chondrite. Results of infrared transmission spectroscopy, thermogravimetry analysis and reflectance spectroscopy show that Mukundpura is mainly composed of phyllosilicates. The rare earth trace elements composition and ultrahigh resolution mass spectrometry of the solub

Nils J. Mikkelsen, Nicholas T. Young, Marcos D. Caballero

Despite limiting access to applicants from underrepresented racial and ethnic groups, the practice of using hard or soft GRE cut-off scores in physics graduate program admissions is still a popular method for reducing the pool of applicants. The present study considers whether the undergraduate institutions of applicants have any influence on the admissions

Carlos E. Arreche, Yi Zhang

We apply the differential Galois theory for difference equations developed by Hardouin and Singer to compute the differential Galois group for a second-order linear $q$-difference equation with rational function coefficients. This Galois group encodes the possible polynomial differential relations among the solutions of the equation. We apply our results to

Liyi Zhou, Kaihua Qin, Christof Ferreira Torres, Duc V Le

Decentralized exchanges (DEXs) allow parties to participate in financial markets while retaining full custody of their funds. However, the transparency of blockchain-based DEX in combination with the latency for transactions to be processed, makes market-manipulation feasible. For instance, adversaries could perform front-running -- the practice of exploitin

Spencer Smith, Jacques Carette

We present a new conceptual definition of 'productivity' for sustainably developing research software. Existing definitions are flawed as they are short-term biased, thus devaluing long-term impact, which we consider to be the principal goal. Taking a long-term view of productivity helps fix that problem. We view the outputs of the development proces

Kobra N. Avanaki, George C. Schatz

Semiconductor quantum light sources are favorable for a wide range of quantum photonic tasks, particularly quantum computing and quantum information processing. Here we theoretically investigate the properties of quantum emitters (QEs) as a source of entangled photons with practical quantum properties including heralding of on-demand single photons. Through

D. Bendova, J. Cepila, J. G. Contreras, V. P. Goncalves

The impact of nonlinear effects in the diffractive observables that will be measured in future electron-ion collisions is investigated. We present, for the first time, the predictions for the diffractive structure function and reduced cross sections derived using the solution to the Balitsky--Kovchegov equation with the collinearly-improved kernel and includ

Antoine Pirovano, Hippolyte Heuberger, Sylvain Berlemont, Saïd Ladjal

Deep learning methods are widely used for medical applications to assist medical doctors in their daily routines. While performances reach expert's level, interpretability (highlight how and what a trained model learned and why it makes a specific decision) is the next important challenge that deep learning methods need to answer to be fully integrated i

Liang Si, Josef Kaufmann, Jan M. Tomczak, Zhicheng Zhong

Transparent conductors-nearly an oxymoron-are in pressing demand, as ultra-thin-film technologies become ubiquitous commodities. As current solutions rely on non-abundant elements, perovskites such as SrVO3 and SrNbO3 have been suggested as next generation transparent conductors. Our ab-initio calculations and analytical insights show, however, that reducing

Calvin Tsay, Yanan Cao, Yajun Wang, Jesus Flores-Cerrillo

Demand-response operation of air separation units requires frequent changes in production rate(s), and scheduling calculations must explicitly consider process dynamics to ensure feasibility of the solutions. To this end, scale-bridging models (SBMs) approximate the scheduling-relevant dynamics of a process and its controller in a low-order representation. I

Duong Thanh Pham, Thanh Tran

A heat equation with uncertain domains is thoroughly investigated. Statistical moments of the solution is approximated by the counterparts of the shape derivative. A rigorous proof for the existence of the shape derivative is presented. Boundary integral equation methods are used to compute statistical moments of the shape derivative.

Kary Främling

Explainability has been a challenge in AI for as long as AI has existed. With the recently increased use of AI in society, it has become more important than ever that AI systems would be able to explain the reasoning behind their results also to end-users in situations such as being eliminated from a recruitment process or having a bank loan application refu

Bruno Ebner, Shawn C. Liebenberg

We propose a new $L^2$-type goodness-of-fit test for the family of beta distributions based on a conditional moment characterisation. The asymptotic null distribution is identified, and since it depends on the underlying parameters, a parametric bootstrap procedure is proposed. Consistency against all alternatives that satisfy a convergence criterion is show

Yosef Yomdin

If a smooth function of one variable has maximum one on the unit interval, and has there $d$ zeroes, then its $(d+1)$-st derivative must be "big". This is one of the simplest examples of what we call "smooth rigidity": certain geometric properties of zero sets of smooth functions $f$ imply explicit lower bounds on the high-order derivatives o

Mounia Bouabdellah, Faissal El Bouanani

In this work, we investigate the physical layer security of a jamming-based underlay cognitive hybrid satellite-terrestrial network {consisting of a} radio frequency link at the first hop and an optical feeder at the second hop. Particularly, one secondary user (SU) is transmitting data {to an end-user} optical ground station {($\boldsymbol{D}$)} through the

Ruipeng Shen

We consider the defocusing, energy subcritical wave equation $\partial_t^2 u - Δu = -|u|^{p-1} u$ in dimension $d \in \{3,4,5\}$ and prove the exterior scattering of solutions if $3\leq d \leq 5$ and $1+6/d<p<1+4/(d-2)$. More precisely, given any solution with a finite energy, there exists a solution $u_L$ to the homogeneous linear wave equation, so that the

Christian Beck, Arnulf Jentzen, Thomas Kruse

The approximative calculation of iterated nested expectations is a recurring challenging problem in applications. Nested expectations appear, for example, in the numerical approximation of solutions of backward stochastic differential equations (BSDEs), in the numerical approximation of solutions of semilinear parabolic partial differential equations (PDEs),

Özgecan Özdogan, Emil Björnson

Intelligent reflecting surfaces (IRSs), consisting of reconfigurable metamaterials, have recently attracted attention as a promising cost-effective technology that can bring new features to wireless communications. These surfaces can be used to partially control the propagation environment and can potentially provide a power gain that is proportional to the

Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu

One of the key limitations in conventional deep learning based image reconstruction is the need for registered pairs of training images containing a set of high-quality groundtruth images. This paper addresses this limitation by proposing a novel unsupervised deep registration-augmented reconstruction method (U-Dream) for training deep neural nets to reconst

Raphael Yuster

A shortcut of a directed path $v_1 v_2 \cdots v_n$ is an edge $v_iv_j$ with $j > i+1$. If $j = i+2$ the shortcut is called a hop. If all hops are present, the path is called hop complete, so the path and its hops form a square of a path. We prove that every tournament with $n \ge 4$ vertices has a Hamiltonian path with at least $(4n-10)/7$ hops, and has a ho

Nuobei Shi, Qin Zeng, Raymond Lee

In this paper, we proposed a transfer learning-based English language learning chatbot, whose output generated by GPT-2 can be explained by corresponding ontology graph rooted by fine-tuning dataset. We design three levels for systematically English learning, including phonetics level for speech recognition and pronunciation correction, semantic level for sp

Xinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat Chatterjee

We design a low complexity decentralized learning algorithm to train a recently proposed large neural network in distributed processing nodes (workers). We assume the communication network between the workers is synchronized and can be modeled as a doubly-stochastic mixing matrix without having any master node. In our setup, the training data is distributed

Tobias Berger, Ariel Weiss

Let $F$ be a CM field with totally real subfield $F^+$ and let $π$ be a $C$-algebraic cuspidal automorphic automorphic representation of $\mathrm{U}(a,b)(\mathbf{A}_{F^+})$ whose archimedean components lie in the (non-degenerate limit of) discrete series. We attach to $π$ a Galois representation $R_π:\mathrm{Gal}(\overline F/ F^+)\to{}^C\mathrm{U}(a,b)(\over

Ferdi Kara

In this paper, a non-orthogonal multiple access based cooperative relaying system (NOMA-CRS) is considered to increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposed for the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols, power sharing (PS), time sharing (TS)

Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery

Various Neural Networks employ time-consuming matrix operations like matrix inversion. Many such matrix operations are faster to compute given the Singular Value Decomposition (SVD). Previous work allows using the SVD in Neural Networks without computing it. In theory, the techniques can speed up matrix operations, however, in practice, they are not fast eno

Sanjiv Kumar Gupta, Kathryn E. Hare

Let $G/K$ be an irreducible symmetric space where $G$ is a non-compact, connected Lie group and $K$ is a compact, connected subgroup. We use decay properties of the spherical functions to show that the convolution product of any $r=r(G/K)$ continuous orbital measures has its density function in $% L^{2}(G)$ and hence is an absolutely continuous measure with

Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli

Hybrid system identification is a key tool to achieve reliable models of Cyber-Physical Systems from data. PieceWise Affine models guarantees universal approximation, local linearity and equivalence to other classes of hybrid system. Still, PWA identification is a challenging problem, requiring the concurrent solution of regression and classification tasks.

Ferdi Kara

Non-orthogonal multiple access (NOMA) and the cooperative relaying systems are two of the promising techniques to meet requirements of future wireless networks such as high spectral efficiency and wide coverage area. On the other hand, the energy efficiency has also high priority in the applications with limited energy such as sensor networks and/or internet

Deyu Zhou, Xuemeng Hu, Rui Wang

Graph Neural Networks (GNNs) that capture the relationships between graph nodes via message passing have been a hot research direction in the natural language processing community. In this paper, we propose Graph Topic Model (GTM), a GNN based neural topic model that represents a corpus as a document relationship graph. Documents and words in the corpus beco

Xuemeng Hu, Rui Wang, Deyu Zhou, Yuxuan Xiong

Advances on deep generative models have attracted significant research interest in neural topic modeling. The recently proposed Adversarial-neural Topic Model models topics with an adversarially trained generator network and employs Dirichlet prior to capture the semantic patterns in latent topics. It is effective in discovering coherent topics but unable to

Raka Dasgupta, Indrakshi Raychowdhury

We propose an analog quantum simulator for simulating real time dynamics of $(1+1)$-d non-Abelian gauge theory well within the existing capacity of ultracold atom experiments. The scheme calls for the realization of a two-state ultracold fermionic system in a 1-dimensional bipartite lattice, and the observation of subsequent tunneling dynamics. Being based o

Sa Wang, Wei Dai, Ben-Wei Zhang, Enke Wang

In high energy nuclear collisions, heavy flavor tagged jets are useful hard probes to study the properties of the quark-gluon plasma (QGP). In this talk, we present the first theoretical prediction of the $D^0$ meson radial distributions in jets relative to the jet axis both in p+p and Pb+Pb collisions at $5.02$ TeV, it shows a nice agreement with the availa

Xiancheng Li, Luca Verginer, Massimo Riccaboni, Pietro Panzarasa

With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others&#39; scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collaborations

Jinting Wu, Yujia Zhang, Xiaoguang Zhao

Hand gesture recognition plays a significant role in human-computer interaction for understanding various human gestures and their intent. However, most prior works can only recognize gestures of limited labeled classes and fail to adapt to new categories. The task of Generalized Zero-Shot Learning (GZSL) for hand gesture recognition aims to address the abov

Shivaank Agarwal, Ravindra Gudi, Paresh Saxena

The problem of segregating recyclable waste is fairly daunting for many countries. This article presents an approach for image based classification of plastic waste using one-shot learning techniques. The proposed approach exploits discriminative features generated via the siamese and triplet loss convolutional neural networks to help differentiate between 5

Noah Halberstam, Tom Hutchcroft

We study dynamic random conductance models on $\mathbb{Z}^2$ in which the environment evolves as a reversible Markov process that is stationary under space-time shifts. We prove under a second moment assumption that two conditionally independent random walks in the same environment collide infinitely often almost surely. These results apply in particular to

Jaker Hossain, Md. Mahabub Alam Moon, Bipanko Kumar Mondal, Mohammad Abdul Halim

In spite of having higher carrier mobilities and absorption coefficients of germanium (Ge) than those of silicon (Si), there has been less focus on Ge-based solar cells due to the low bandgap and high-cost of Ge wafer as well as requirement of its high-purity level. Currently, availability of high-purity Ge (HPGe), the low-cost wafer slicing method and prope

Harshdeep Singh, Nicholas McCarthy, Qurrat Ul Ain, Jeremiah Hayes

In order to design a more potent and effective chemical entity, it is essential to identify molecular structures with the desired chemical properties. Recent advances in generative models using neural networks and machine learning are being widely used by many emerging startups and researchers in this domain to design virtual libraries of drug-like compounds

Carlo Rigoni, Bent Harnist, Grégory Beaune, Jaakko V. I. Timonen

Ferrofluids are strongly magnetic fluids consisting of magnetic nanoparticles dispersed in a carrier fluid. Besides their technological applications, they have a tendency to form beautiful and intriguing patterns when subjected to external static and dynamic magnetic fields. Most of the patterns occur in systems consisting of two fluids: one ferrofluidic and

Jingyu Duan, Janne S. Lehtinen, Michael A. Fogarty, Simon Schaal

We report on ambipolar gate-defined quantum dots in silicon on insulator (SOI) nanowires fabricated using a customised complementary metal-oxide-semiconductor (CMOS) process. The ambipolarity was achieved by extending a gate over an intrinsic silicon channel to both highly doped n-type and p-type terminals. We utilise the ability to supply ambipolar carrier

Cristian Cioflan, Radu Timofte

Neural Architecture Search (NAS) has proved effective in offering outperforming alternatives to handcrafted neural networks. In this paper we analyse the benefits of NAS for image classification tasks under strict computational constraints. Our aim is to automate the design of highly efficient deep neural networks, capable of offering fast and accurate predi

Diogo Pernes, Jaime S. Cardoso

It has been known for a while that the problem of multi-source domain adaptation can be regarded as a single source domain adaptation task where the source domain corresponds to a mixture of the original source domains. Nonetheless, how to adjust the mixture distribution weights remains an open question. Moreover, most existing work on this topic focuses onl

Karin Melnick

In this survey, symmetry provides a framework for classification of manifolds with differential-geometric structures. We highlight pseudo-Riemannian metrics, conformal structures, and projective structures. A range of techniques have been developed and successfully deployed in this subject, some of them based on algebra and dynamics and some based on analysi

Jingcheng Li, Pedro Brandimarte, Manuel Vilas-Varela, Nestor Merino-Díez

The electronic properties of graphene nanoribbons (GNRs) can be precisely tuned by chemical doping. Here we demonstrate that amino (NH$_2$) functional groups attached at the edges of chiral GNRs (chGNRs) can efficiently gate the chGNRs and lead to the valence band (VB) depopulation on a metallic surface. The NH$_2$-doped chGNRs are grown by on-surface synthe

Hichame Yessou, Gencer Sumbul, Begüm Demir

This paper analyzes and compares different deep learning loss functions in the framework of multi-label remote sensing (RS) image scene classification problems. We consider seven loss functions: 1) cross-entropy loss; 2) focal loss; 3) weighted cross-entropy loss; 4) Hamming loss; 5) Huber loss; 6) ranking loss; and 7) sparseMax loss. All the considered loss

Mahla Mirzaee-Kakhki, Adrian Ernst, Daniel de las Heras, Maciej Urbaniak

Detailed control over the motion of colloidal particles is relevant in many applications in colloidal science such as lab-on-a-chip devices. Here, we use an external magnetic field to assemble paramagnetic colloidal spheres into colloidal rods of several lengths. The rods reside above a square magnetic pattern and are transported via modulation of the direct

Shahabodin Khadivi Zand

Business Processes, i.e., a set of coordinated tasks and activities to achieve a business goal, and their continuous improvements are key to the operation of any organization. In banking, business processes are increasingly dynamic as various technologies have made dynamic processes more prevalent. For example, customer segmentation, i.e., the process of gro

Michael Voit, Jeannette H. C. Woerner

We study Bessel and Dunkl processes $(X_{t,k})_{t\ge0}$ on $\mathbb R^N$ with possibly multivariate coupling constants $k\ge0$. These processes describe interacting particle systems of Calogero-Moser-Sutherland type with $N$ particles. For the root systems $A_{N-1}$ and $B_N$ these Bessel processes are related with $β$-Hermite and $β$-Laguerre ensembles. Mor

Pavol Quittner

Liouville theorems for scaling invariant nonlinear parabolic problems in the whole space and/or the halfspace (saying that the problem does not posses positive bounded solutions defined for all times $t\in(-\infty,\infty)$) guarantee optimal estimates of solutions of related initial-boundary value problems in general domains. We prove an optimal Liouville th

Syed Muhammad Asad Zaidi, Marvin Manalastas, Hasan Farooq, Ali Imran

The exponential rise in mobile traffic originating from mobile devices highlights the need for making mobility management in future networks even more efficient and seamless than ever before. Ultra-Dense Cellular Network vision consisting of cells of varying sizes with conventional and mmWave bands is being perceived as the panacea for the eminent capacity c

Michal Bitan, Malka Gorfine, Laura Rosen, David M. Steinberg

Outcomes from studies assessing exposure often use multiple measurements. In previous work, using a model first proposed by Buonoccorsi (1991), we showed that combining direct (e.g. biomarkers) and indirect (e.g. self-report) measurements provides a more accurate picture of true exposure than estimates obtained when using a single type of measurement. In thi

Holger Klapperich, Alarith Uhde, Marc Hassenzahl

Nowadays, automation not only permeates industry but also becomes a substantial part of our private, everyday lives. Driven by the idea of increased convenience and more time for the &#34;important things in life,&#34; automation relieves us from many daily chores - robots vacuum floors and automated coffee makers produce supposedly barista-quality coffee on

Stefano Nardean, Massimiliano Ferronato, Ahmad S. Abushaikha

In this work we propose a novel block preconditioner, labelled Explicit Decoupling Factor Approximation (EDFA), to accelerate the convergence of Krylov subspace solvers used to address the sequence of non-symmetric systems of linear equations originating from flow simulations in porous media. The flow model is discretized blending the Mixed Hybrid Finite Ele

Jesús Liñares, Xesús Prieto-Blanco, Daniel Balado, Gabriel M. Carral

We present a bidirectional quantum communication system based on optical phase conjugation for achieving fully autocompensating high-dimensional quantum cryptography. We prove that random phase shifts and couplings among 2N spatial and polarization optical modes described by SU(2N) transformations due to perturbations are autocompensated after a single round

Xianlin Song, Kanggao Tang, Jianshuang Wei, Lingfang Song

Photoacoustic imaging is a new imaging technology in recent years, which combines the advantages of high resolution and rich contrast of optical imaging with the advantages of high penetration depth of acoustic imaging. Photoacoustic imaging has been widely used in biomedical fields, such as brain imaging, tumor detection and so on. The signal-to-noise ratio

Simon A. Svatek, C. Bueno, Der-Yuh Lin, James Kerfoot

The conversion efficiency of ultra-thin solar cells based on layered materials has been limited by their open-circuit voltage, which is typically pinned to a value under 0.6 V. Here we report an open-circuit voltage of 1.02 V in a 120 nm-thick vertically stacked homojunction fabricated with substitutionally doped MoS2. This high open-circuit voltage is consi

Martin Heilmann, Victor Deinhart, Abbes Tahraoui, Katja Höflich

The combination of two-dimensional (2D) materials into heterostructures enabled the formation of atomically thin devices with designed properties. To achieve a high density, bottom-up integration, the growth of these 2D heterostructures via van der Waals epitaxy (vdWE) is an attractive alternative to the currently mostly employed mechanical transfer, which i

Augustin Baas, Baptiste Le Bihan

The violation of Bell inequalities seems to establish an important fact about the world: that it is non-local. However, this result relies on the assumption of the statistical independence of the measurement settings with respect to potential past events that might have determined them. Superdeterminism refers to the view that a local, and determinist, accou

Xianlin Song, Ao Teng, Jianshuang Wei, Lingfang Song

The study of the interaction between laser and brain tissue has important theoretical and practical significance for brain imaging. A two-dimensional simulation model that studies the propagation of light and heat transfer in brain tissue based on finite element has been developed by using the commercial finite element simulation software COMSOL Multiphysics

Marco Piccardo, Antonio Ambrosio

Optical vortices are the electromagnetic analogue of fluid vortices studied in hydrodynamics. In both cases the traveling wavefront, either made of light or fluid, is twisted like a corkscrew around its propagation axis - an analogy that inspired also the first proposition of the concept of optical vortex. Even though vortices are one of the most fundamental

Jacopo Amidei

Annotation reproducibility and accuracy rely on good consistency within annotators. We propose a novel method for measuring within annotator consistency or annotator Intraobserver Agreement (IA). The proposed approach is based on transitivity, a measure that has been thoroughly studied in the context of rational decision-making. The transitivity measure, in

Alexis Langlois-Rémillard, Roy Oste

We initiate the study of an algebra of symmetries for the 3D Dirac-Dunkl operator associated with the Weyl group of the exceptional root system $G_2$. For this symmetry algebra, we give both an abstract definition and an explicit realisation. We then construct ladder operators, using an intermediate result we prove for the Dirac-Dunkl symmetry algebra associ

Christie L. Alappat, Jan Laukemann, Thomas Gruber, Georg Hager

The A64FX CPU powers the current number one supercomputer on the Top500 list. Although it is a traditional cache-based multicore processor, its peak performance and memory bandwidth rival accelerator devices. Generating efficient code for such a new architecture requires a good understanding of its performance features. Using these features, we construct the

Xin Tian, Ke Xu, Xin Yang, Baocai Yin

Existing salient instance detection (SID) methods typically learn from pixel-level annotated datasets. In this paper, we present the first weakly-supervised approach to the SID problem. Although weak supervision has been considered in general saliency detection, it is mainly based on using class labels for object localization. However, it is non-trivial to u

Xianlin Song, Rui Wang, Jianshuang Wei, Lingfang Song

We studied the transmission of photons in mouse brain in both with and without intact skull states using Monte Carlo method. Photon track, optical absorption density and fluence rate were used as indicators for analysis. We found that, the photon distribution without intact skull goes farther in both longitudinal and transverse directions compared with that

Ben Day, Cătălina Cangea, Arian R. Jamasb, Pietro Liò

Neural Processes (NPs) are powerful and flexible models able to incorporate uncertainty when representing stochastic processes, while maintaining a linear time complexity. However, NPs produce a latent description by aggregating independent representations of context points and lack the ability to exploit relational information present in many datasets. This

Genrich R. Belitskii, Vyacheslav Futorny, Mikhail Muzychuk, Vladimir V. Sergeichuk

Two matrix vector spaces $V,W\subset \mathbb C^{n\times n}$ are said to be equivalent if $SVR=W$ for some nonsingular $S$ and $R$. These spaces are congruent if $R=S^T$. We prove that if all matrices in $V$ and $W$ are symmetric, or all matrices in $V$ and $W$ are skew-symmetric, then $V$ and $W$ are congruent if and only if they are equivalent. Let $F: U\ti

Shin-Ichiro Ei, Hiroyuki Ochiai, Yoshitaro Tanaka

The method of the fundamental solutions (MFS) is used to construct an approximate solution for a partial differential equation in a bounded domain. It is demonstrated by combining the fundamental solutions shifted to the points outside the domain and determining the coefficients of the linear sum to satisfy the boundary condition on the finite points of the

G. Cosentino, I. Jiménez-Serra, J. D. Henshaw, P. Caselli

Infrared Dark Clouds (IRDCs) are very dense and highly extincted regions that host the initial conditions of star and stellar cluster formation. It is crucial to study the kinematics and molecular content of IRDCs to test their formation mechanism and ultimately characterise these initial conditions. We have obtained high-sensitivity Silicon Monoxide, SiO(2-

Ferdiant Joshua Muis, Ayu Purwarianti

Automatic question generation is defined as the task of automating the creation of question given a various of textual data. Research in automatic question generator (AQG) has been conducted for more than 10 years, mainly focused on factoid question. In all these studies, the state-of-the-art is attained using sequence-to-sequence approach. However, AQG syst

Gergely Ambrus

We study higher order convexity properties of random point sets in the unit square. Given $n$ uniform i.i.d random points, we derive asymptotic estimates for the maximal number of them which are in $k$-monotone position, subject to mild boundary conditions. Besides determining the order of magnitude of the expectation, we also prove strong concentration esti

Xianglong Wu, Xiangdong Zhang

The Penrose process in the vicinity of an extremal Banãdos-Teitelboim-Zanelli(BTZ) black hole is studied. Due to the existence of negative cosmological constant, only massless particles could escape to infinity. Hence we analyse the Penrose process by one massless particle collides with another massive particle near the horizon of BTZ black holes. Calculatio

Th. V. Papavasileiou, D. A. Papadopoulos, T. S. Kosmas

In this work, at first we present a model of studying astrophysical flows of binary systems and microquasars based on the laws of relativistic magnetohydrodynamics. Then, by solving the time independent transfer equation, we estimate the primary and secondary particle distributions within the hadronic astrophysical jets as well as the emissivities of high en

David Vallés-Pérez, Susana Planelles, Vicent Quilis

We analyse the results of an Eulerian AMR cosmological simulation in order to quantify the mass growth of galaxy clusters, exploring the differences between dark matter and baryons. We have determined the mass assembly histories (MAHs) of each of the mass components and computed several proxies for the instantaneous mass accretion rate (MAR). The mass growth

Stephan Eckstein

This note shows that, for a fixed Lipschitz constant $L > 0$, one layer neural networks that are $L$-Lipschitz are dense in the set of all $L$-Lipschitz functions with respect to the uniform norm on bounded sets.

Naoya Yoshida, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto

This paper proposes a client selection method for federated learning (FL) when the computation and communication resource of clients cannot be estimated; the method trains a machine learning (ML) model using the rich data and computational resources of mobile clients without collecting their data in central systems. Conventional FL with client selection esti

Yuji Odaka

Open Calabi-Yau manifolds and log Calabi-Yau varieties have been broadly studied over decades. Regarding them as &#34;semistable&#34; objects, we propose to consider their good proper subclass, which we regard as certain poly-stable ones, morally corresponding to semistable with closed (minimal) orbits} as the classical analogue of GIT. We partially confirm

Igor Furtat, Pavel Gushchin

The paper describes a novel method of sampled-data in space (spatial variable) control of scalar semilinear systems of parabolic and hyperbolic type with unknown parameters and distributed disturbances. A finite set of sampled-data in the spatial variable measurements is available. The control law depends on the function which depends on the spatial variable

Elsa Amsellem, Frédéric Moynier, Brandon Mahan, Pierre Beck

Carbonaceous chondrites are often considered potential contributors of water and other volatiles to terrestrial planets as most of them contain significant amounts of hydrous mineral phases. As such, carbonaceous chondrites are candidate building blocks for Earth, and elucidating their thermal histories is of direct important for understanding the volatile e

Israr Ali, Aarij Mahmood Hussaan, Syed Hasan Adil

This paper describes an in depth analysis of successful and unsuccessful software Projects and the Role of Software Project Mangers in that success. One of the main reason in software project success is manager. Software houses are investing too much in this regard but the average ratio of software project failure is on the high side. Project managers experi

Israr Ali, Syed Hasan Adil, Mansoor Ebrahim

In this era of internet, E-Business and e-commerce applications are using Databases as their integral part. These Databases irrespective of the technology used are vulnerable to SQL injection attacks. These Attacks are considered very dangerous as well as very easy to use for attackers and intruders. In this paper, we are proposing a new approach to detect i

Timo Neumann, Sascha Feldmann, Philipp Moser, Jonathan Zerhoch

Materials combining the optoelectronic functionalities of semiconductors with control of the spin degree of freedom are highly sought after for the advancement of quantum technology devices. Here, we report the paramagnetic Ruddlesden-Popper hybrid perovskite Mn:(PEA)2PbI4 (PEA = phenethylammonium) in which the interaction of isolated Mn2+ ions with magnetic

Xinxin Chen

We consider the randomly biased random walk on trees in the slow movement regime as in [HS16], whose potential is given by a branching random walk in the boundary case. We study the heavy range up to the $n$-th return to the root, i.e., the number of edges visited more than $k_n$ times. For $k_n=n^θ$ with $θ\in(0,1)$, we obtain the convergence in probability

Sohei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto

Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve the reliability of wireless communications, especially at higher frequencies (e.g., millimeter-wave and terahertz technologies), through predictive handover and beamforming to solve line-of-sight (LOS) blockage problem. In this study, a rea

Zhuojun Tian, Zhaoyang Zhang, Jue Wang, Xiaoming Chen

In this paper, we propose a novel distributed alternating direction method of multipliers (ADMM) algorithm with synergetic communication and computation, called SCCD-ADMM, to reduce the total communication and computation cost of the system. Explicitly, in the proposed algorithm, each node interacts with only part of its neighboring nodes, the number of whic

Wenjia Xu, Jiuniu Wang, Yang Wang, Guangluan Xu

Image classification models have achieved satisfactory performance on many datasets, sometimes even better than human. However, The model attention is unclear since the lack of interpretability. This paper investigates the fidelity and interpretability of model attention. We propose an Explainable Attribute-based Multi-task (EAT) framework to concentrate the

Inna Vogel, Meghana Meghana

The authors of fake news often use facts from verified news sources and mix them with misinformation to create confusion and provoke unrest among the readers. The spread of fake news can thereby have serious implications on our society. They can sway political elections, push down the stock price or crush reputations of corporations or public figures. Severa

María Jesús de la Puente, Pedro Luis Clavería

Through tropical normal idempotent matrices, we introduce isocanted alcoved polytopes, computing their $f$--vectors and checking the validity of the following five conjectures: Bárány, unimodality, $3^d$, flag and cubical lower bound (CLBC). Isocanted alcoved polytopes are centrally symmetric, almost simple cubical polytopes. They are zonotopes. We show that