October 2020 arXiv papers — page 45

Francesco Milano, Antonio Loquercio, Antoni Rosinol, Davide Scaramuzza

Recent works in geometric deep learning have introduced neural networks that allow performing inference tasks on three-dimensional geometric data by defining convolution, and sometimes pooling, operations on triangle meshes. These methods, however, either consider the input mesh as a graph, and do not exploit specific geometric properties of meshes for featu

Quentin Ansel, Steffen J. Glaser, Dominique Sugny

We study the selective and robust time-optimal rotation control of several spin-1/2 particles with different offset terms. For that purpose, the Pontryagin Maximum Principle is applied to a model of two spins, which is simple enough for analytic computations and sufficiently complex to describe inhomogeneity effects. We find that selective and robust control

Michael Rathjen

Several theorems about the equivalence of familiar theories of reverse mathematics with certain well-ordering principles have been proved by recursion-theoretic and combinatorial methods (Friedman, Marcone, Montalban et al.) and with far-reaching results by proof-theoretic technology (Afshari, Freund, Girard, Rathjen, Thomson, Valencia Vizcano, Weiermann et

Paul Shafer, Sebastiaan A. Terwijn

For every partial combinatory algebra (pca), we define a hierarchy of extensionality relations using ordinals. We investigate the closure ordinals of pca's, i.e. the smallest ordinals where these relations become equal. We show that the closure ordinal of Kleene's first model is $\omega_1^\textit{CK}$ and that the closure ordinal of Kleene's second model is

Jorge Rodriguez-Ramos, Felix Rico

The use of atomic force microscopy on nanomechanical measurements requires accurate calibration of the cantilever's spring constant ($k_c$) and the optical lever sensitivity ($OLS$). The thermal method, based on the cantilever's thermal fluctuations in fluid, allows estimating $k_c$ in a fast, non-invasive mode. However, differences in the cantilever geometr

Nariyoshi Chida, Tachio Terauchi

There has been much work on synthesizing and repairing regular expressions (regexes for short) from examples. These programming-by-example (PBE) methods help the users write regexes by letting them reflect their intention by examples. However, the existing methods may generate regexes whose matching may take super-linear time and are vulnerable to regex deni

Stefanie Schwaar

The q-weighted CUSUM and their corresponding estimator are well known statistics for change-point detection and estimation. They have the difficulty that the performance is highly dependent on the location of the change. An adaptive estimator with data-driven weights is presented to overcome this problem, and it is shown that the corresponding adaptive chang

Francesco Zatelli, Claudia Benedetti, Matteo G. A. Paris

We address the scattering of a quantum particle by a one-dimensional barrier potential over a set of discrete positions. We formalize the problem as a continuous-time quantum walk on a lattice with an impurity, and use the quantum Fisher information as a mean to quantify the maximal possible accuracy in the estimation of the height of the barrier. We introdu

A. Belhaj, Y. El Maadi, S. E. Ennadifi, Y. Hassouni

Motivated by particle phyiscs results, we investigate certain dyonic solutions in arbitrary dimensions. Concretely, we study the stringy constructions of such objects from concrete compactifications. Then we elaborate their tensor network realizations using multistate particle formalism.

Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, Gerard Pons-Moll

We address the problem of fitting 3D human models to 3D scans of dressed humans. Classical methods optimize both the data-to-model correspondences and the human model parameters (pose and shape), but are reliable only when initialized close to the solution. Some methods initialize the optimization based on fully supervised correspondence predictors, which is

Eric Kerfoot, Carlos Escudero King, Tefvik Ismail, David Nordsletten

Valve annuli motion and morphology, measured from non-invasive imaging, can be used to gain a better understanding of healthy and pathological heart function. Measurements such as long-axis strain as well as peak strain rates provide markers of systolic function. Likewise, early and late-diastolic filling velocities are used as indicators of diastolic functi

Alexandre Anahory Simoes, Juan Carlos Marrero, David Martin de Diego

Nonholonomic mechanics describes the motion of systems constrained by nonintegrable constraints. One of its most remarkable properties is that the derivation of the nonholonomic equations is not variational in nature. {However, in} this paper, we prove (Theorem 1.1) that for kinetic nonholonomic {systems}, the solutions starting from a fixed point $q$ are tr

Edson Otoniel, Jaziel G. Coelho, Sílvia P. Nunes, Manuel Malheiro

CTCV J2056--3014 is a nearby cataclysmic variable with an orbital period of approximately $1.76$ hours at a distance of about $853$ light-years from the Earth. Its recently reported X-ray properties suggest that J2056-3014 is an unusual accretion-powered intermediate polar that harbors a fast-spinning white dwarf (WD) with a spin period of $29.6$ s. The low

Iván Fernández-Val, Hugo Freeman, Martin Weidner

We provide estimation methods for nonseparable panel models based on low-rank factor structure approximations. The factor structures are estimated by matrix-completion methods to deal with the computational challenges of principal component analysis in the presence of missing data. We show that the resulting estimators are consistent in large panels, but suf

Roelof Bijker, Hugo García-Tecocoatzi, Alessandro Giachino, Emmanuel Ortiz-Pacheco

In this article, we present a complete classification of the negative parity $\Xi'_{c/b}$ and $\Xi_{c/b}$ $P$-wave states: 7 belonging to the $SU(3)$ flavor sextet and 7 to the flavor anti-triplet, the calculation of the $\Xi'_{c/b}$ and $\Xi_{c/b}$ strong partial decay widths into $^2\Sigma_c \bar{K}$, $^2\Xi_c^{'} \pi$, $^2\Sigma_c \bar{K}$, $^4\Xi_c^{'} \

Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn, Mattia Rossi

In this work, we propose BP-MVSNet, a convolutional neural network (CNN)-based Multi-View-Stereo (MVS) method that uses a differentiable Conditional Random Field (CRF) layer for regularization. To this end, we propose to extend the BP layer and add what is necessary to successfully use it in the MVS setting. We therefore show how we can calculate a normaliza

Olivier Graf

In this paper, we prove the global nonlinear stability of Minkowski space in the context of the spacelike-characteristic Cauchy problem for Einstein vacuum equations. Spacelike-characteristic initial data are posed on a compact 3-disk and on the future complete null hypersurface emanating from its boundary. Our result extends the seminal stability result for

Diego Alves, Gaurish Thakkar, Marko Tadić

This article presents the strategy for developing a platform containing Language Processing Chains for European Union languages, consisting of Tokenization to Parsing, also including Named Entity recognition andwith addition ofSentiment Analysis. These chains are part of the first step of an event-centric knowledge processing pipeline whose aim is to process

Eli Galanti, Yohai Kaspi

During the past few years, both the Cassini mission at Saturn and the Juno mission at Jupiter, provided measurements with unprecedented accuracy of the gravity and magnetic fields of the two gas giants. Using the gravity measurements, it was found that the strong zonal flows observed at the cloud-level of the gas giants are likely to extend thousands of kilo

Stefano Longhi

The non-Hermitian skin effect, i.e. eigenstate condensation at the edges in lattices with open boundaries, is an exotic manifestation of non-Hermitian systems. In Bloch theory, an effective non-Hermitian Hamiltonian is generally used to describe dissipation, which however is not norm-preserving and neglects quantum jumps. Here it is shown that in a self-cons

Matthew Maciejewski, Jing Shi, Shinji Watanabe, Sanjeev Khudanpur

As the performance of single-channel speech separation systems has improved, there has been a desire to move to more challenging conditions than the clean, near-field speech that initial systems were developed on. When training deep learning separation models, a need for ground truth leads to training on synthetic mixtures. As such, training in noisy conditi

Simon Eisenbarth, Sihuang Hu

A structure theorem of the group codes which are relative projective for the subgroup $\lbrace 1 \rbrace$ of $G$ is given. With this, we show that all such relative projective group codes in a fixed group algebra $RG$ are in bijection to the chains of projective group codes of length $\ell$ in the group algebra $\mathbb{F}G$, where $\mathbb{F}$ is the residu

Diego Alves, Gaurish Thakkar, Marko Tadić

This article presents the results of the evaluation campaign of language tools available for fifteen EU-official under-resourced languages. The evaluation was conducted within the MSC ITN CLEOPATRA action that aims at building the cross-lingual event-centric knowledge processing on top of the application of linguistic processing chains (LPCs) for at least 24

Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz

We address the source-free domain adaptation (SFDA) problem, where only the source model is available during adaptation to the target domain. We consider two settings: the offline setting where all target data can be visited multiple times (epochs) to arrive at a prediction for each target sample, and the online setting where the target data needs to be dire

Jinfu Zhu, Tao Xue, Liangjun Wei, Jianmin Li

The CDEX (China Dark matter Experiment) now deploys ~10 kg pPCGe (p-type Point Contact Germanium) detectors in CJPL (China Jinping Underground Laboratory). It aims to detect rare events such as dark matter and 0vbb (neutrinoless double beta decay). The discrimination of bulk and very bulk events are essential for improvements of the analysis threshold of dar

Noelia Bortolussi, Martín Mombelli

We generalize the notion of ends and coends in category theory to the realm of module categories over finite tensor categories. We call this new concept "module (co)end". This tool allows us to give different proofs to several known results in the theory of representations of finite tensor categories. As a new application, we present a description of the rel

Mahmoud A. Gaafar, He Li, Xinlun Cai, Juntao Li

Here we report the first experimental demonstration of light trapping by a refractive index front in a silicon waveguide, the optical push broom effect. The front generated by a fast pump pulse collects and traps the energy of a CW signal with smaller group velocity and tuned near to the band gap of the Bragg grating introduced in the waveguide. This situati

Rui Liu, Berrak Sisman, Haizhou Li

Attention-based end-to-end text-to-speech synthesis (TTS) is superior to conventional statistical methods in many ways. Transformer-based TTS is one of such successful implementations. While Transformer TTS models the speech frame sequence well with a self-attention mechanism, it does not associate input text with output utterances from a syntactic point of

Yali Peng, Yue Cao, Shigang Liu, Jian Yang

Recent years have witnessed the great success of deep convolutional neural networks (CNNs) in image denoising. Albeit deeper network and larger model capacity generally benefit performance, it remains a challenging practical issue to train a very deep image denoising network. Using multilevel wavelet-CNN (MWCNN) as an example, we empirically find that the de

Francesco Barbieri, Jose Camacho-Collados, Leonardo Neves, Luis Espinosa-Anke

The experimental landscape in natural language processing for social media is too fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics like sentiment analysis to irony detection or emoji prediction. Therefore, it is unclear what the current state of the art is, as there is no standardized evaluation protocol, neither a str

Jinfu Zhu, Tianhao Wang, Tao Xue, Liangjun Wei

The CDEX (China Dark matter Experiment) aims at detection of WIMPs (Weakly Interacting Massive Particles) and 0vbb (Neutrinoless double beta decay) of 76Ge. It now uses ~10 kg HPGe (High Purity Germanium) detectors in CJPL (China Jinping Underground Laboratory). The energy resolution of detectors is calculated via height spectrum of waveforms with 6-us shapi

Hendrik Bartsch, Markus Bier, S. Dietrich

Previous theoretical studies of calamitic (i.e., rod-like) ionic liquid crystals (ILCs) based on an effective one-species model led to indications of a novel smectic-A phase with a layer spacing being much larger than the length of the mesogenic (i.e., liquid-crystal forming) ions. In order to rule out the possibility that this wide smectic-A phase is merely

Ahmed Ghanim Al-Ali, Robert Phaal, Donald Sull

Companies today are racing to leverage the latest digital technologies, such as artificial intelligence, blockchain, and cloud computing. However, many companies report that their strategies did not achieve the anticipated business results. This study is the first to apply state of the art NLP models on unstructured data to understand the different clusters

Shuai Shao, Mengke Wang, Rui Xu, Yan-Jiang Wang

For classification tasks, dictionary learning based methods have attracted lots of attention in recent years. One popular way to achieve this purpose is to introduce label information to generate a discriminative dictionary to represent samples. However, compared with traditional dictionary learning, this category of methods only achieves significant improve

Shuai Shao, Rui Xu, Yan-Jiang Wang, Weifeng Liu

In recent years, the attention mechanism contributes significantly to hypergraph based neural networks. However, these methods update the attention weights with the network propagating. That is to say, this type of attention mechanism is only suitable for deep learning-based methods while not applicable to the traditional machine learning approaches. In this

Jürgen E. Schatzmann, Bernhard Haslhofer

Investors commonly exhibit the disposition effect - the irrational tendency to sell their winning investments and hold onto their losing ones. While this phenomenon has been observed in many traditional markets, it remains unclear whether it also applies to atypical markets like cryptoassets. This paper investigates the prevalence of the disposition effect i

Antonius Armanious, Björn Agnarsson, Anders Lundgren, Vladimir P. Zhdanov

Assumption-free mass quantification of nanofilms, nanoparticles, and (supra)molecular adsorbates in liquid environment remains a key challenge in many branches of science. Mechanical resonators can uniquely determine the mass of essentially any adsorbate; yet, when operating in liquid environment, the liquid dynamically coupled to the adsorbate contributes s

Horatiu Nastase, Jacob Sonnenschein

In this note we study soliton, breather and shockwave solutions in certain two dimensional field theories. These include: (i) Heisenberg's model suggested originally to describe the scattering of high energy nucleons (ii) $T\bar T$ deformations of certain canonical scalar field theories with a potential. We find explicit soliton solutions of these models wit

Ohad Rubin, Jonathan Berant

The de-facto standard decoding method for semantic parsing in recent years has been to autoregressively decode the abstract syntax tree of the target program using a top-down depth-first traversal. In this work, we propose an alternative approach: a Semi-autoregressive Bottom-up Parser (SmBoP) that constructs at decoding step $t$ the top-$K$ sub-trees of hei

Jacob Hastrup, Kimin Park, Radim Filip, Ulrik L. Andersen

Squeezed states of harmonic oscillators are a central resource for continuous-variable quantum sensing, computation and communication. Here we propose a method for the generation of very good approximations to highly squeezed vacuum states with low excess anti-squeezing using only a few oscillator-qubit coupling gates through a Rabi-type interaction Hamilton

Sarah Peluse, Kannan Soundararajan

We show that almost every entry in the character table of $S_N$ is divisible by any fixed prime as $N\to\infty$. This proves a conjecture of Miller.

Keith R. Fratus, Camille Le Calonnec, Rodolfo A. Jalabert, Guillaume Weick

We demonstrate the emergence of classical features in electronic quantum transport for the scanning gate microscopy response in a cavity defined by a quantum point contact and a micron-sized circular reflector. The branches in electronic flow characteristic of a quantum point contact opening on a two-dimensional electron gas with weak disorder are folded by

Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He

The original design of Graph Convolution Network (GCN) couples feature transformation and neighborhood aggregation for node representation learning. Recently, some work shows that coupling is inferior to decoupling, which supports deep graph propagation better and has become the latest paradigm of GCN (e.g., APPNP and SGCN). Despite effectiveness, the workin

Mukesh Kumar Singh, Shasvath J. Kapadia, Md Arif Shaikh, Deep Chatterjee

A gravitational-wave (GW) early-warning of a compact-binary coalescence event, with a sufficiently tight localisation skymap, would allow telescopes to point in the direction of the potential electromagnetic counterpart before its onset. This will enable astronomers to extract valuable information of the complex astrophysical phenomena triggered around the t

Diego Alves, Tin Kuculo, Gabriel Amaral, Gaurish Thakkar

We introduce the Universal Named-Entity Recognition (UNER)framework, a 4-level classification hierarchy, and the methodology that isbeing adopted to create the first multilingual UNER corpus: the SETimesparallel corpus annotated for named-entities. First, the English SETimescorpus will be annotated using existing tools and knowledge bases. Afterevaluating th

Xin Li, Lidong Bing, Wenxuan Zhang, Zheng Li

Cross-lingual adaptation with multilingual pre-trained language models (mPTLMs) mainly consists of two lines of works: zero-shot approach and translation-based approach, which have been studied extensively on the sequence-level tasks. We further verify the efficacy of these cross-lingual adaptation approaches by evaluating their performances on more fine-gra

Gregor Rauw, Yael Naze

The Oef category gathers rapidly rotating and evolved O-stars displaying a centrally reversed He II 4686 emission line. The origin of the variability of their photospheric and wind spectral lines is debated, with rotational modulation or pulsations as the main contenders. To shed new light on this question, we analysed high-quality and high-cadence TESS phot

Asbjorn Christian Nordentoft, Petru Constantinescu

We provide a new and simple automorphic method using Eisenstein series to study the equidistribution of modular symbols modulo primes, which we apply to prove an average version of a conjecture of Mazur and Rubin. More precisely, we prove that modular symbols corresponding to a Hecke basis of weight 2 cusp forms are asymptotically jointly equidistributed mod

Felix Krahmer, Christian Kümmerle, Oleh Melnyk

We prove new results about the robustness of well-known convex noise-blind optimization formulations for the reconstruction of low-rank matrices from underdetermined linear measurements. Our results are applicable for symmetric rank-one measurements as used in a formulation of the phase retrieval problem. We obtain these results by establishing that with hig

Gaurish Thakkar, Marcis Pinnis

In this paper, we present various pre-training strategies that aid in im-proving the accuracy of the sentiment classification task. We, at first, pre-trainlanguage representation models using these strategies and then fine-tune them onthe downstream task. Experimental results on a time-balanced tweet evaluation setshow the improvement over the previous techn

Xiaohui Wang, Ying Xiong, Yang Wei, Mingxuan Wang

Transformer, BERT and their variants have achieved great success in natural language processing. Since Transformer models are huge in size, serving these models is a challenge for real industrial applications. In this paper, we propose LightSeq, a highly efficient inference library for models in the Transformer family. LightSeq includes a series of GPU optim

Yuan Chen, Jiaqi Li, Guorui Xu, Yajin Zhou

Since its debut, SGX has been used in many applications, e.g., secure data processing. However, previous systems usually assume a trusted enclave and ignore the security issues caused by an untrusted enclave. For instance, a vulnerable (or even malicious) third-party enclave can be exploited to attack the host application and the rest of the system. In this

J. D. R. Pierel, S. Rodney, G. Vernardos, M. Oguri

One of the primary mission objectives for the Roman Space Telescope is to investigate the nature of dark energy with a variety of methods. Observations of Type Ia supernovae (SNIa) will be one of the principal anchors of the Roman cosmology program, through traditional luminosity distance measurements. This SNIa cosmology program can provide another valuable

R. S. Prasobh Sankar, Sundeep Prabhakar Chepuri

This paper focuses on channel estimation for mmWave MIMO systems with 1-bit spatial sigma-delta analog-to-digital converters (ADCs). The channel estimation performance with 1-bit spatial sigma-delta ADCs depends on the quantization noise modeling. Therefore, we present a new method for modeling the quantization noise by leveraging the deterministic input-out

Ken-ichi Kawarabayashi, Robin Thomas, Paul Wollan

A cornerstone theorem in the Graph Minors series of Robertson and Seymour is the result that every graph $G$ with no minor isomorphic to a fixed graph $H$ has a certain structure. The structure can then be exploited to deduce far-reaching consequences. The exact statement requires some explanation, but roughly it says that there exist integers $k,n$ dependin

Ji-Gui Cheng, Ya-Jun He, Yun-Feng Liang, Rui-Jing Lu

In this work, we re-analyze the Fermi-LAT observation of NGC 1275 to search for axion-like particle (ALP) effects and constrain ALP parameters. Instead of fitting the observed spectrum with ALP models, we adopt an alternative method for the analysis of this source which calculates the irregularity of the spectrum. With the newly used method, we find no spect

Fabian Alexander Mikulasch, Lucas Rudelt, Viola Priesemann

How can neural networks learn to efficiently represent complex and high-dimensional inputs via local plasticity mechanisms? Classical models of representation learning assume that input weights are learned via pairwise Hebbian-like plasticity. Here, we show that pairwise Hebbian-like plasticity only works under unrealistic requirements on neural dynamics and

Fan Lu, Guang Chen, Yinlong Liu, Zhongnan Qu

Keypoint detector and descriptor are two main components of point cloud registration. Previous learning-based keypoint detectors rely on saliency estimation for each point or farthest point sample (FPS) for candidate points selection, which are inefficient and not applicable in large scale scenes. This paper proposes Random Sample-based Keypoint Detector and

Lang Cui, Ru-Sen Lu, Wei Yu, Jun Liu

High resolution imaging of inner jets in Active Galactic Nuclei (AGNs) with VLBI at millimeter wavelengths provides deep insight into the launching and collimation mechanisms of relativistic jets. The BL Lac object, PKS 1749+096, shows a core-dominated jet pointing toward the northeast on parsec-scales revealed by various VLBI observations. In order to inves

Jin-Beom Bae, Zhihao Duan, Kimyeong Lee, Sungjay Lee

We define Modular Linear Differential Equations (MLDE) for the level-two congruence subgroups $\Gamma_\vartheta$, $\Gamma^0(2)$ and $\Gamma_0(2)$ of $\text{SL}_2(\mathbb Z)$. Each subgroup corresponds to one of the spin structures on the torus. The pole structures of the fermionic MLDEs are investigated by exploiting the valence formula for the level-two con

Priscille de Dumast, Hamza Kebiri, Chirine Atat, Vincent Dunet

The fetal cortical plate undergoes drastic morphological changes throughout early in utero development that can be observed using magnetic resonance (MR) imaging. An accurate MR image segmentation, and more importantly a topologically correct delineation of the cortical gray matter, is a key baseline to perform further quantitative analysis of brain developm

Alexey Sidnev, Ekaterina Krasikova, Maxim Kazakov

The success of deep neural networks in the traditional keypoint detection task encourages researchers to solve new problems and collect more complex datasets. The size of the DeepFashion2 dataset poses a new challenge on the keypoint detection task, as it comprises 13 clothing categories that span a wide range of keypoints (294 in total). The direct predicti

Li Chen, Esther S. Daus, Alexandra Holzinger, Ansgar Jüngel

Population cross-diffusion systems of Shigesada-Kawasaki-Teramoto type are derived in a mean-field-type limit from stochastic, moderately interacting many-particle systems for multiple population species in the whole space. The diffusion term in the stochastic model depends nonlinearly on the interactions between the individuals, and the drift term is the gr

Jun-Hao Cheng, Xiao Pan, You-Tian Zou, Xiao-Hua Li

Proton radioactivity is an important and common process of the natural radioactivity of proton-rich nuclei. In our previous work [J. H. Cheng et al., Nucl. Rhys. A 997, 121717 (2020)], we systematically studied the proton radioactivity half-lives of 53< Z <83 nuclei within the two-potential approach with Skyrme-Hartree-Fock. The calculations can well reprodu

Sayak Datta, Sajal Mukherjee

We study a viable connection between the circular-equatorial orbits and reflection symmetry across the equatorial plane of a vacuum stationary axis-symmetric spacetime in general relativity. The behavior of the circular equatorial orbits in the direction perpendicular to the equatorial plane is studied, and different outcomes in the presence and in the absen

Stéphane Nonnenmacher

The study of wave propagation outside bounded obstacles uncovers the existence of resonances for the Laplace operator, which are complex-valued generalized eigenvalues, relevant to estimate the long time asymptotics of the wave. In order to understand distribution of these resonances at high frequency, we employ semiclassical tools, which leads to considerin

Michael Neuder, Elizabeth Bradley, Edward Dlugokencky, James W. C. White

While it is tempting in experimental practice to seek as high a data rate as possible, oversampling can become an issue if one takes measurements too densely. These effects can take many forms, some of which are easy to detect: e.g., when the data sequence contains multiple copies of the same measured value. In other situations, as when there is mixing$-$in

M. Martinelli, I. Tutusaus, M. Archidiacono, S. Camera

Upcoming surveys will map the growth of large-scale structure with unprecented precision, improving our understanding of the dark sector of the Universe. Unfortunately, much of the cosmological information is encoded by the small scales, where the clustering of dark matter and the effects of astrophysical feedback processes are not fully understood. This can

Yang Wang, Marco Giordani, Michele Zorzi

The millimeter wave (mmWave) technology enables unmanned aerial vehicles (UAVs) to offer broadband high-speed wireless connectivity in fifth generation (5G) and beyond (6G) networks. However, the limited footprint of a single UAV implementing analog beamforming (ABF) requires multiple aerial stations to operate in swarms to provide ubiquitous network coverag

Huy The Nguyen, Shengwen Wang

In this paper we prove an analogue of the Brakke's $\varepsilon$-regularity theorem for the parabolic Allen-Cahn equation. In particular, we show uniform $C^{2,\alpha}$ regularity for the transition layers converging to smooth mean curvature flows as $\varepsilon\rightarrow0$. The proof utilises Allen-Cahn versions of the monotonicity formula, parabolic Lips

Chun Shen, Li Yan

We present a concise review of the recent development of relativistic hydrodynamics and its applications to heavy-ion collisions. Theoretical progress on the extended formulation of hydrodynamics towards out-of-equilibrium systems is addressed, emphasizing the so-called attractor solution. On the other hand, recent phenomenological improvements in the hydrod

Jean-Philippe Chancelier, Michel de Lara

The support of a vector in R d is the set of indices with nonzero entries. Functions of the support have the property to be 0-homogeneous and, because of that, the Fenchel conjugacy fails to provide relevant analysis. In this paper, we define the coupling Capra between R d and itself by dividing the classic Fenchel scalar product coupling by a given (source)

Mohammad Reza Dayer

The pandemic threat of COVID-19 with more than 37 million cases in which about 5 percent entering critical stage characterized by cytokine storm and hyperinflammatory condition, the state more often leads to admission to intensive care unit with rapid mortality. Janus kinase enzymes of Jak-1, Jak-2, Jak-3, and Tyk2 seem to be good targets for inhibition by m

Javier Hormigo, Sergio D. Muñoz

High-throughput QR decomposition is a key operation in many advanced signal processing and communication applications. For some of these applications, using floating-point computation is becoming almost compulsory. However, there are scarce works in hardware implementations of floating-point QR decomposition for embedded systems. In this paper, we propose a

Chi Zhang, Massoud Rezavand, Yujie Zhu, Yongchuan Yu

In this paper, we present an open-source multi-resolution and multi-physics library: SPHinXsys (pronunciation: s'finksis) which is an acronym for \underline{S}moothed \underline{P}article \underline{H}ydrodynamics (SPH) for \underline{in}dustrial comple\underline{X} \underline{sys}tems. As an open-source library, SPHinXsys is developed and released under the

Hyunbae Park, Paul R. Shapiro, Kyungjin Ahn, Naoki Yoshida

At cosmic recombination, there was supersonic relative motion between baryons and dark matter, which originated from the baryonic acoustic oscillations in the early universe. This motion has been considered to have a negligible impact on the late stage of cosmic reionization because the relative velocity quickly decreases. However, recent studies have sugges

Safa~Ashraf, Zubair Khalid, Muhammad Tahir, Momin Uppal

The increased concentration of aerosols in the air caused by ever-rising urbanization and the development of various industries has horrendous consequences on human health, environment and climate. The first step to counter adverse effects of air pollution in any region is to identify locations with a high concentration of aerosols, termed aerosol hot-spots.

V. Fomichov, J. Ivanovs

There is growing empirical evidence that spherical $k$-means clustering performs well at identifying groups of concomitant extremes in high dimensions, thereby leading to sparse models. We provide one of the first theoretical results supporting this approach, but also demonstrate some pitfalls. Furthermore, we show that an alternative cost function may be mo

Trond-Ola Hågbo, Knut Erik Teigen Giljarhus, Bjørn Helge Hjertager

The construction of a building inevitably changes the microclimate in its vicinity. Many city authorities request comprehensive wind studies before granting a building permit, which can be obtained by Computational Fluid Dynamics (CFD) simulations. When performing wind simulations, the quality of the geometry model is essential. Still, no available studies e

Sara Abdollahi, Simon Gottschalk, Elena Demidova

An increasing need to analyse event-centric cross-lingual information calls for innovative user interaction models that assist users in crossing the language barrier. However, datasets that reflect user interaction traces in cross-lingual settings required to train and evaluate the user interaction models are mostly missing. In this paper, we present the Eve

Dennis Eschweiler, Malte Rethwisch, Simon Koppers, Johannes Stegmaier

Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data. To process the vast amount of image data generated by current digitized imaging techniques, automated approaches are demanded more than ever. Segmentation approaches used for morphological analyses, however, are often prone to produce unnaturally shaped predicti

Masato I. N. Kobayashi, Tsuyoshi Inoue, Shu-Ichiro Inutsuka, Kengo Tomida

We systematically perform hydrodynamics simulations of 20 km s^-1 converging flows of the warm neutral medium (WNM) to calculate the formation of the cold neutral medium (CNM), especially focusing on the mean properties of the multiphase interstellar medium (ISM), such as the average shock front position and the mean density on a 10 pc scale. Our results sho

Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang

Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad of specialized knowledge and often delivering limited performance. In this paper, we propose to automatically learn PDRs via an end-to-end deep reinforcement learning agent. We e

Valerie Brien, A. Dauscher, P. Weisbecker, J. Ghanbaja

Pulsed laser deposition from a Nd:YAG laser was employed in production of hundreds of nanometer thick quasicrystalline Ti-Zr-Ni films on glass substrate. The influence of deposition temperature Ts on the structure, morphology and microstructure of the films across their thickness was investigated. The morphology and microstructure features were evaluated by

Evgeni Nurminski

This paper is devoted to the general problem of projection onto a polyhedral convex cone generated by a finite set of generators.This problem is reformulated into projection onto the polytope obtained by simple truncation of the original cone. Then it can be solved with just two closely related projections onto the same bounded polytope. This approach's comp

Valerie Brien, Anne Dauscher, F. Machizaud

Optical reflectivity as a simple diagnostic method for testing structural quality of icosahedral quasicrystals 2 The optical reflectivity of Al-based and Ti-based quasicrystalline and approximant samples were investigated versus the quality of their structural morphology using optical reflectometry, X-ray diffraction and transmission electron microscopy. The

Kaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutière

This paper proposes a theoretical analysis of recommendation systems in an online setting, where items are sequentially recommended to users over time. In each round, a user, randomly picked from a population of $m$ users, requests a recommendation. The decision-maker observes the user and selects an item from a catalogue of $n$ items. Importantly, an item c

Diego M. Arribas, Yuan Zhao, Il Memming Park

The standard approach to fitting an autoregressive spike train model is to maximize the likelihood for one-step prediction. This maximum likelihood estimation (MLE) often leads to models that perform poorly when generating samples recursively for more than one time step. Moreover, the generated spike trains can fail to capture important features of the data

C. Thorpe, J. Nowak, K. Niewczas, J. T. Sobczyk

We study the properties of the Cabibbo suppressed quasielastic production of $\Lambda$ and $\Sigma$ hyperons in antineutrino interactions with nuclei, including the effects of modified form factor axial mass, the second class current and SU(3) flavour violations. The hyperon and nucleon are subjected to the nuclear potential and the outgoing hyperon can unde

K. Medjanik, O. Fedchenko, O. Yastrubchak, J. Sadowski

Recent advances in the brilliance of hard-X-ray beamlines and photoelectron momentum microscopy facilitate bulk valence-band mapping and core-level-resolved hard-X-ray photoelectron diffraction (hXPD) for structural analysis in the same setup. High-quality MBE-grown (In,Ga,Mn)As films represent an ideal testing ground, because of the non-centrosymmetric GaAs

David Kipping, Adam Frank, Caleb Scharf

First contact with another civilization, or simply another intelligence of some kind, will likely be quite different depending on whether that intelligence is more or less advanced than ourselves. If we assume that the lifetime distribution of intelligences follows an approximately exponential distribution, one might naively assume that the pile-up of short-

Georges Sitja, Aude Bailly, Maurizio de Santis, Vasile Heresanu

Alumina ultrathin films obtained by high temperature oxidation of a Ni$_3$Al (111) surface are a good template to grow regular arrays of metal clusters. Up to now two hexagonal organizations called 'dot' and 'network' structures have been observed with distances between clusters of 4.1 and 2.4 nm, respectively. In the present article we report on an investig

Janne Heittokangas, Jun Wang, Zhi-Tao Wen, Hui Yu

The $\varphi$-order was introduced in 2009 for meromorphic functions in the unit disc, and was used as a growth indicator for solutions of linear differential equations. In this paper, the properties of meromorphic functions in the complex plane are investigated in terms of the $\varphi$-order, which measures the growth of functions between the classical ord

Matúš Medo, Manuel S. Mariani, Linyuan Lü

With vast amounts of high-quality information at our fingertips, how is it possible that many people believe that the Earth is flat and vaccination harmful? Motivated by this question, we quantify the implications of an opinion formation mechanism whereby an uninformed observer gradually forms opinions about a world composed of subjects interrelated by a sig

Cillian Harney, Stefano Pirandola

The characterisation of Quantum Channel Discrimination (QCD) offers critical insight for future quantum technologies in quantum metrology, sensing and communications. The task of multi-channel discrimination creates a scenario in which the discrimination of multiple quantum channels can be equated to the idea of pattern recognition, highly relevant to the ta

Benjamin Finley, Jaume Benseny, Alexandr Vesselkov, Jaspreet Walia

The adoption of Internet of Things (IoT) technologies in businesses is increasing and thus enterprise IoT (EIoT) is seemingly shifting from hype to reality. However, the actual use of EIoT over significant timescales has not been empirically analyzed. In other words, the reality remains unexplored. Furthermore, despite the variety of EIoT verticals, the use

Florian Barth, Stefan Funke, Tobias Skovgaard Jepsen, Claudius Proissl

We present analysis techniques for large trajectory data sets that aim to provide a semantic understanding of trajectories reaching beyond them being point sequences in time and space. The presented techniques use a driving preference model w.r.t. road segment traversal costs, e.g., travel time and distance, to analyze and explain trajectories. In particular

Arun Verma, Manjesh K. Hanawal, Csaba Szepesvári, Venkatesh Saligrama

In this paper, we study Contextual Unsupervised Sequential Selection (USS), a new variant of the stochastic contextual bandits problem where the loss of an arm cannot be inferred from the observed feedback. In our setup, arms are associated with fixed costs and are ordered, forming a cascade. In each round, a context is presented, and the learner selects the

Yuhan Zhang, Cheng Chang

This paper models the US-China trade conflict and attempts to analyze the (optimal) strategic choices. In contrast to the existing literature on the topic, we employ the expected utility theory and examine the conflict mathematically. In both perfect information and incomplete information games, we show that expected net gains diminish as the utility of winn

Monika Eisenmann, Tony Stillfjord, Måns Williamson

We consider a stochastic version of the proximal point algorithm for optimization problems posed on a Hilbert space. A typical application of this is supervised learning. While the method is not new, it has not been extensively analyzed in this form. Indeed, most related results are confined to the finite-dimensional setting, where error bounds could depend