December 2020 arXiv papers — page 123

Jochem Verrelst, Juan Pablo Rivera, Anatoly Gitelson, Jesus Delegido

With current and upcoming imaging spectrometers, automated band analysis techniques are needed to enable efficient identification of most informative bands to facilitate optimized processing of spectral data into estimates of biophysical variables. This paper introduces an automated spectral band analysis tool (BAT) based on Gaussian processes regression (GP

Fatih Nar, Erdal Yilmaz, Gustau Camps-Valls

We here introduce an automatic Digital Terrain Model (DTM) extraction method. The proposed sparsity-driven DTM extractor (SD-DTM) takes a high-resolution Digital Surface Model (DSM) as an input and constructs a high-resolution DTM using the variational framework. To obtain an accurate DTM, an iterative approach is proposed for the minimization of the target

Ivan V Kazachkov

The present paper is devoted to the mixing and heat transfer features of mutually immiscible liquids in the two-fluid turbulent heterogeneous jet flow. Many natural and technical processes deal with the turbulent jets of mutually immiscible liquids, which represent an important class of the modern multiphase system dynamics. Differential equations for the ax

Gustau Camps-Valls, Luca Martino, Daniel H. Svendsen, Manuel Campos-Taberner

Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has excelled in biophysical parameter estimation tasks from airborne and satellite observations. GP regression is based on solid Bayesian statistics and generally yields efficient and ac

Xianwei Sha, Clifford M. Krowne

Moving beyond traditional 2D materials is now desirable to have switching capabilities (e.g., transistors). Here we propose using graphyne because, as we will show in this letter, obtaining regions of the electronic bandstructure which act as valence and conduction bands, with an apparent bandgap, is found. Here for particular allotropes of graphyne, density

Leon A. Abdillah

The application of information technology in the era of big data and cloud computing has led to the trend of electronic payments through financial technology, or FinTech. One of the most popular FinTech applications in Indonesia is Go-Pay in the Gojek start-up application. This research will analyze how the FinTech Go-Pay user experience both for transaction

Ashwin Rachha, Gaurav Vanmane

The internet today has become an unrivalled source of information where people converse on content based websites such as Quora, Reddit, StackOverflow and Twitter asking doubts and sharing knowledge with the world. A major arising problem with such websites is the proliferation of toxic comments or instances of insincerity wherein the users instead of mainta

Chris Mazur, Jesse Ayers, Gaetan Hains, Youry Khmelevsky

The Gamer's Private Network (GPN) is a client/server technology created by WTFast for making the network performance of online games faster and more reliable. GPN s use middle-mile servers and proprietary algorithms to better connect online video-game players to their game's servers across a wide-area network. Online games are a massive entertainment

Jose E. Adsuara, Adrián Pérez-Suay, Jordi Muñoz-Marí, Anna Mateo-Sanchis

In many remote sensing applications one wants to estimate variables or parameters of interest from observations. When the target variable is available at a resolution that matches the remote sensing observations, standard algorithms such as neural networks, random forests or Gaussian processes are readily available to relate the two. However, we often encoun

Fangzhou Yan, Zhifu Gao, Wenshen Yang, Aijun Dong

In this paper, we attribute high braking indices $n>3$ of two magnetars SGR 0501$+$4516 and 1E 2259$+$586 to the decrease in their inclination angles using the double magnetic-dipole model proposed by Hamil et al.(2016). In this model, there are two magnetic moments inside a neutron star, one is generated by the rotation effect of a charged sphere, $M_{1}$,

José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar, Gustau Camps-Valls

Current anomaly detection algorithms are typically challenged by either accuracy or efficiency. More accurate nonlinear detectors are typically slow and not scalable. In this letter, we propose two families of techniques to improve the efficiency of the standard kernel Reed-Xiaoli (RX) method for anomaly detection by approximating the kernel function with ei

S. Salcedo-Sanz, P. Ghamisi, M. Piles, M. Werner

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resol

Francisco Javier García-Haro, Manuel Campos-Taberner, Beatriz Martínez, Sergio Sánchez-Ruiz

We describe the methodology applied for the retrieval of global LAI, FAPAR and FVC from Advanced Very High Resolution Radiometer (AVHRR) onboard the Meteorological-Operational (MetOp) polar orbiting satellites also known as EUMETSAT Polar System (EPS). A novel approach has been developed for the joint retrieval of three parameters (LAI, FVC, and FAPAR) inste

Francisco Javier García-Haro, Manuel Campos-Taberner, Jordi Muñoz-Marí, Valero Laparra

This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High-Resolution Radiometer) sensor onboard MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorol

Adrián Pérez-Suay, Gustau Camps-Valls

Establishing causal relations between random variables from observational data is perhaps the most important challenge in today's \blue{science}. In remote sensing and geosciences this is of special relevance to better understand the Earth's system and the complex interactions between the governing processes. In this paper, we focus on observational

J. Vicent, J. Verrelst, J. P. Rivera-Caicedo, N. Sabater

End-to-end mission performance simulators (E2ES) are suitable tools to accelerate satellite mission development from concet to deployment. One core element of these E2ES is the generation of synthetic scenes that are observed by the various instruments of an Earth Observation mission. The generation of these scenes rely on Radiative Transfer Models (RTM) for

Francisco M. Fernández

We obtain eigenvalues and eigenfunctions of the Schrödinger equation with a hyperbolic double-well potential. We consider exact polynomial solutions for some particular values of the potential-strength parameter and also numerical energies for arbitrary values of this model parameter. We test the numerical method by means of a suitable exact asymptotic expre

Jose Estevez, Jorge Vicent, Juan Pablo Rivera-Caicedo, Pablo Morcillo-Pallarés

Retrieval of vegetation properties from satellite and airborne optical data usually takes place after atmospheric correction, yet it is also possible to develop retrieval algorithms directly from top-of-atmosphere (TOA) radiance data. One of the key vegetation variables that can be retrieved from at-sensor TOA radiance data is the leaf area index (LAI) if al

Hamed Javidi, Dan Simon, Ling Zhu, Yan Wang

The ultimate goal of ridesharing systems is to matchtravelers who do not have a vehicle with those travelers whowant to share their vehicle. A good match can be found amongthose who have similar itineraries and time schedules. In thisway each rider can be served without any delay and also eachdriver can earn as much as possible without having too muchdeviati

Katja Berger, Jochem Verrelst, Jean-Baptiste Féret, Tobias Hank

Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy r

Mohammad Al-Fetyani, Mones Azazma

The main objective of this work is demonstrated through two main aspects. The first is the design of an adaptive neuro-fuzzy inference system (ANFIS) controller to develop the attitude and altitude of a quadcopter. The second is to establish the linearized mathematical model of the quadcopter in a simple and clear way. To show the effectiveness of the ANFIS

Roberto Rondinelli, Stefano Marmani, Valerio Ficcadenti

In this paper we extrapolate the information about Bible's characters and places, and their interrelationships, by using text mining network-based approach. We study the narrative structure of the WEB version of 5 books: the Gospel of Matthew, Mark, Luke, John and Acts of the Apostles. The main focus is the protagonists' names interrelationships in a

Jiaqi Wang, Kai Chen, Rui Xu, Ziwei Liu

Feature reassembly, i.e. feature downsampling and upsampling, is a key operation in a number of modern convolutional network architectures, e.g., residual networks and feature pyramids. Its design is critical for dense prediction tasks such as object detection and semantic/instance segmentation. In this work, we propose unified Content-Aware ReAssembly of FE

Jorge Vicent, Luis Alonso, Luca Martino, Neus Sabater

Atmospheric correction of Earth Observation data is one of the most critical steps in the data processing chain of a satellite mission for successful remote sensing applications. Atmospheric Radiative Transfer Models (RTM) inversion methods are typically preferred due to their high accuracy. However, the execution of RTMs on a pixel-per-pixel basis is imprac

Manuel Campos-Taberner, Franciso Javier García-Haro, Álvaro Moreno, María Amparo Gilabert

Leaf area index (LAI) is a key biophysical parameter used to determine foliage cover and crop growth in environmental studies. Smartphones are nowadays ubiquitous sensor devices with high computational power, moderate cost, and high-quality sensors. A smartphone app, called PocketLAI, was recently presented and tested for acquiring ground LAI estimates. In t

Fei Huang, Alexandre Sava, Kondo H. Adjallah, Wang Zhouhang

The research work presented in this paper proposes a data-driven modeling method for bearings remaining useful life estimation based on Takagi-Sugeno (T-S) fuzzy inference system (FIS). This method allows identifying the parameters of a classic T-S FIS, starting with a small quantity of data. In this work, we used the vibration signals data from a small numb

Jochem Verrelst, Zbyněk Malenovský, Christiaan Van der Tol, Gustau Camps-Valls

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams req

Weicheng Ma, Ruibo Liu, Lili Wang, Soroush Vosoughi

Metaphors are ubiquitous in human language. The metaphor detection task (MD) aims at detecting and interpreting metaphors from written language, which is crucial in natural language understanding (NLU) research. In this paper, we introduce a pre-trained Transformer-based model into MD. Our model outperforms the previous state-of-the-art models by large margi

Dylan Whang, Soroush Vosoughi

We describe the systems developed for the WNUT-2020 shared task 2, identification of informative COVID-19 English Tweets. BERT is a highly performant model for Natural Language Processing tasks. We increased BERT's performance in this classification task by fine-tuning BERT and concatenating its embeddings with Tweet-specific features and training a Supp

Chris Miller, Soroush Vosoughi

Relation and event extraction is an important task in natural language processing. We introduce a system which uses contextualized knowledge graph completion to classify relations and events between known entities in a noisy text environment. We report results which show that our system is able to effectively extract relations and events from a dataset of we

Devis Tuia, Diego Marcos, Gustau Camps-Valls

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one m

ochem Verrelst, Sara Dethier, Juan Pablo Rivera, Jordi Muñoz-Marí

Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training datasets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a

Giulio D'Agostini

The often debated issue of `ratios of small numbers of events' is approached from a probabilistic perspective, making a clear distinction between the predictive problem (forecasting numbers of events we might count under well stated assumptions, and therefore of their ratios) and inferential problem (learning about the relevant parameters of the related

Davide Gaiotto, Miroslav Rapcak

We determine the mathematical structures which govern the $Ω$ deformation of supersymmetric intersections of M2 and M5 branes. We find that the supersymmetric intersections govern many aspects of the theory of W-algebras, including degenerate modules, the Miura transform and Coulomb gas constructions. We give an algebraic interpretation of the Pandharipande-

Zvonimir Vlah, Nora Elisa Chisari, Fabian Schmidt

Intrinsic galaxy alignments yield an important contribution to the observed statistics of galaxy shapes. The general bias expansion for galaxy sizes and shapes in three dimensions has been recently described by Vlah, Chisari \& Schmidt using the general perturbative effective field theory (EFT) framework, in analogy to the clustering of galaxies. In this wor

Janet Zhong, Alexander N. Poddubny

We provide the first classification of three-photon eigenstates in a finite periodic array of two-level atoms coupled to a waveguide. We focus on the strongly subwavelength limit and show the hierarchical structure of the eigenstates in the complex plane. The main characteristic eigenstates are explored using entanglement entropy as a distinguishing feature.

Yu Yin, Joseph P. Robinson, Songyao Jiang, Yue Bai

Advances in face rotation, along with other face-based generative tasks, are more frequent as we advance further in topics of deep learning. Even as impressive milestones are achieved in synthesizing faces, the importance of preserving identity is needed in practice and should not be overlooked. Also, the difficulty should not be more for data with obscured

Galia Dafni, Ryan Gibara, Andrew Lavigne

We study the space BMO in the general setting of a measure space $\mathbb{X}$ with a fixed collection $\mathscr{G}$ of measurable sets of positive and finite measure, consisting of functions of bounded mean oscillation on sets in $\mathscr{G}$. The aim is to see how much of the familiar BMO machinery holds when metric notions have been replaced by measure-th

Xuan Gong, Xin Xia, Wentao Zhu, Baochang Zhang

In recent years, deep learning has dominated progress in the field of medical image analysis. We find however, that the ability of current deep learning approaches to represent the complex geometric structures of many medical images is insufficient. One limitation is that deep learning models require a tremendous amount of data, and it is very difficult to o

Graham Todd, Shane Steinert-Threlkeld, Christopher Potts

Agent-based models and signalling games are useful tools with which to study the emergence of linguistic communication in a tractable setting. These techniques have been used to study the compositional property of natural languages, but have been limited in how closely they model real communicators. In this work, we present a novel variant of the classic sig

Ayaz Akram, Jason Lowe-Power

Machine learning techniques have influenced the field of computer architecture like many other fields. This paper studies how the fundamental machine learning techniques can be applied towards computer architecture problems. We also provide a detailed survey of computer architecture research that employs different machine learning methods. Finally, we presen

Fereshte Khani, Percy Liang

The presence of spurious features interferes with the goal of obtaining robust models that perform well across many groups within the population. A natural remedy is to remove spurious features from the model. However, in this work we show that removal of spurious features can decrease accuracy due to the inductive biases of overparameterized models. We comp

Abdus Salam Sarkar, Emmanuel Stratakis

Solution processable two-dimensional (2D) materials have provided an ideal platform for both fundamental studies and wearable electronic applications. Apart from graphene and 2D dichalcogenides, IVA-VI monochalcogenides (MMCs) has emerged recently as a promising candidate for next generation electronic applications. However, the dispersion behavior, which is

Orenthal J. Tucker, William M. Farrell, Andrew R. Poppe

We examine how water is produced globally over the lunar surface as it orbits in/out of the magnetotail. Due to the interaction of the solar wind (SW) with Earth's magnetic field, upstream the magnetic field is compressed down to ~10 Earth radii. However, the diverted stream of SW around Earth's magnetic field results in an extended depleted region o

Minoru Eto, Adam Peterson, Fidel I. Schaposnik Massolo, Gianni Tallarita

The dynamics of both global and local vortices with non-Abelian orientational moduli is investigated in detail. Head-on collisions of these vortices are numerically simulated for parallel, anti-parallel and orthogonal internal orientations where we find interesting dynamics of the orientational moduli. A detailed study of the inter-vortex force is provided a

Yanren Hou, Feng Shi, Haibiao Zheng

In this paper, we present a novel local and parallel two-grid finite element scheme for solving the Stokes equations, and rigorously establish its a priori error estimates. The scheme admits simultaneously small scales of subproblems and distances between subdomains and its expansions, and hence can be expandable. Based on the a priori error estimates, we pr

M. MacDonald, A. Ooi, R. García-Mayoral, N. Hutchins

We conduct minimal-channel direct numerical simulations of turbulent flow over two-dimensional rectangular bars aligned in the spanwise direction. This roughness has been often described as $d$-type, as the roughness function $ΔU^+$ is thought to depend only on the outer-layer length scale (pipe diameter, channel half height or boundary layer thickness). Thi

Xinwei Li, Yuanyuan Zhang, Xiaodan Zhuang, Daben Liu

Inspired by SpecAugment -- a data augmentation method for end-to-end ASR systems, we propose a frame-level SpecAugment method (f-SpecAugment) to improve the performance of deep convolutional neural networks (CNN) for hybrid HMM based ASR systems. Similar to the utterance level SpecAugment, f-SpecAugment performs three transformations: time warping, frequency

Guilherme D. Pelegrina, Leonardo T. Duarte, Michel Grabisch, João M. T. Romano

In many ranking problems, some particular aspects of the addressed situation should be taken into account in the aggregation process. An example is the presence of correlations between criteria, which may introduce bias in the derived ranking. In these cases, aggregation functions based on a capacity may be used to overcome this inconvenience, such as the Ch

Talya Eden, Dana Ron, Will Rosenbaum

In this work, we consider the problem of sampling a $k$-clique in a graph from an almost uniform distribution in sublinear time in the general graph query model. Specifically the algorithm should output each $k$-clique with probability $(1\pm ε)/n_k$, where $n_k$ denotes the number of $k$-cliques in the graph and $ε$ is a given approximation parameter. We pr

Guilherme D. Pelegrina, Leonardo T. Duarte, João M. T. Romano

This work proposes the application of independent component analysis to the problem of ranking different alternatives by considering criteria that are not necessarily statistically independent. In this case, the observed data (the criteria values for all alternatives) can be modeled as mixtures of latent variables. Therefore, in the proposed approach, we per

J. P. P. Vieira, A. Lazarides, T. Ala-Nissila

We introduce a framework to model the evolution of a class of open quantum systems whose environments periodically undergo an instantaneous non-unitary evolution stage. For the special case of quadratic models, we show how this approach can generalise the formalism of repeated interactions to allow for the preservation of system-environment correlations. Fur

Satoshi Ohashi, Hiroshi Kobayashi, Riouhei Nakatani, Satoshi Okuzumi

Ring structures are observed by (sub-)millimeter dust continuum emission in various circumstellar disks from early stages of Class 0 and I to late stage of Class II young stellar objects (YSOs). In this paper, we study one of the possible scenarios of such ring formation in early stage, which is coagulation of dust aggregates. The dust grains grow in an insi

Daniel Brethauer, Raffaella Margutti, Danny Milisavljevic, Michael Bietenholz

We present the first coordinated soft and hard 0.3-80 keV X-ray campaign of the extragalactic supernova SN 2014C in the first $\sim$2307 d of its evolution. SN 2014C initially appeared to be an ordinary type Ib explosion but evolved into a strongly-interacting hydrogen-rich type IIn SN over $\sim1 \rm{yr}$. We observed signatures of interaction with a dense

Anuradha Welivita, Pearl Pu

Open-domain conversational agents or chatbots are becoming increasingly popular in the natural language processing community. One of the challenges is enabling them to converse in an empathetic manner. Current neural response generation methods rely solely on end-to-end learning from large scale conversation data to generate dialogues. This approach can prod

Alex Reneau, Jason R. Wilson

It is crucial for any assistive robot to prioritize the autonomy of the user. For a robot working in a task setting to effectively maintain a user's autonomy it must provide timely assistance and make accurate decisions. We use four independent high-precision, low-recall models, a mutual gaze model, task model, confirmatory gaze model, and a lexical mode

Nicola Kistler, Adrien Schertzer

We consider the problem of undirected polymers (tied at the endpoints) in random environment, also known as the unoriented first passage percolation on the hypercube, in the limit of large dimensions. By means of the multiscale refinement of the second moment method we obtain a fairly precise geometrical description of optimal paths, i.e. of polymers with mi

Hussein Al-Jlailaty, Mohammad M. Mansour

Inertial sensors based on micro-electromechanical systems (MEMS) technology, such as accelerometers and angular rate sensors, are cost-effective solutions used in inertial navigation systems in a broad spectrum of applications that estimate position, velocity and orientation of a system with respect to an inertial reference frame. The task of an orientation

Yuanze Luo, Timothy Heckman, Hsiang-Chih Hwang, Kate Rowlands

While all models for the evolution of galaxies require the accretion of gas to sustain their growth via on-going star formation, it has proven difficult to directly detect this inflowing material. In this paper we use data of nearby star-forming galaxies in the SDSS IV Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey to search for evidence

Koushik Pal, Yi Xia, Chris Wolverton

We investigate the microscopic mechanism of ultralow lattice thermal conductivity ($κ_l$) of TlInTe$_2$ and its weak temperature dependence using a unified theory of lattice heat transport that considers contributions arising from the particle-like propagation as well as wave-like tunneling of phonons. While we use the Peierls-Boltzmann transport equation (P

Daniel Vrinceanu, Roberto Onofrio, Hossein R. Sadeghpour

Scattering phenomena between charged particles and highly excited Rydberg atoms are of critical importance in many processes in plasma physics and astrophysics. While a Maxwell-Boltzmann (MB) energy distribution for the charged particles is often assumed for calculations of collisional rate coefficients, in this contribution we relax this assumption and use

Anthony M. DeGennaro, Francis J. Alexander

The goal of this paper is to make Optimal Experimental Design (OED) computationally feasible for problems involving significant computational expense. We focus exclusively on the Mean Objective Cost of Uncertainty (MOCU), which is a specific methodology for OED, and we propose extensions to MOCU that leverage surrogates and adaptive sampling. We focus on red

Armando M. V. Corro, Carlos M. C. Riveros, Marcelo L. Ferro

In this paper we describe the $ε$-isothermic surfaces in the pseudo-Euclidean 3-space and we obtain the pseudo-Calapso equation. In sequence, we classify the Dupin surfaces in pseudo-Euclidean 3-space having distinct principal curvatures and provide explicit coordinates for such surfaces. As application of the theory, we give explicit solutions to the pseudo

Christian Makaya, Amalendu Iyer, Jonathan Salfity, Madhu Athreya

Computing at the edge is increasingly important since a massive amount of data is generated. This poses challenges in transporting all that data to the remote data centers and cloud, where they can be processed and analyzed. On the other hand, harnessing the edge data is essential for offering data-driven and machine learning-based applications, if the chall

Kristina R. Colbert, Frank C. Errickson, David Anthoff, Chris E. Forest

Integrated assessment models (IAMs) are valuable tools that consider the interactions between socioeconomic systems and the climate system. Decision-makers and policy analysts employ IAMs to calculate the marginalized monetary cost of climate damages resulting from an incremental emission of a greenhouse gas. Used within the context of regulating anthropogen

S. V. Danielyan, A. E. Guterman, T. W. Ng

The concepts of differentiation and integration for matrices were introduced for studying zeros and critical points of complex polynomials. Any matrix is differentiable, however not all matrices are integrable. The purpose of this paper is to investigate the integrability property and characterize it within the class of diagonalizable matrices. In order to d

Steffi Olesi Muhanji, Samuel Golding, Tad Montgomery, Clifton Below

The electricity distribution system is fundamentally changing due to the widespread adoption of variable renewable energy resources (VREs), network-enabled digital physical devices, and active consumer engagement. VREs are uncertain and intermittent in nature and pose various technical challenges to power systems control and operations thus limiting their pe

Sihui Zheng, Cong Shen, Xiang Chen

Communication has been known to be one of the primary bottlenecks of federated learning (FL), and yet existing studies have not addressed the efficient communication design, particularly in wireless FL where both uplink and downlink communications have to be considered. In this paper, we focus on the design and analysis of physical layer quantization and tra

Victor Senoguchi Borges, Iryna Kashuba, Vladimir V. Sergeichuk, Eduardo Ventilari Sodré

We classify all linear operators $A:V\to V$ satisfying $(Au,v)=(u,A^rv)$ and all linear operators satisfying $(Au,A^rv)=(u,v)$ with $r=2,3,\dots$ on a complex, real, or quaternion vector space with scalar product given by a nonsingular symmetric, skew-symmetric, Hermitian, or skew-Hermitian form.

Joel C. Zinn, Dennis Stello, Yvonne Elsworth, Rafael A. García

Studies of Galactic structure and evolution have benefitted enormously from Gaia kinematic information, though additional, intrinsic stellar parameters like age are required to best constrain Galactic models. Asteroseismology is the most precise method of providing such information for field star populations $\textit{en masse}$, but existing samples for the

N. Granados Hernández, S. Vargas Domínguez

Solar active regions and the processes that occur in them have been extensively studied and analyzed and many types of models and characterizations have been proposed for the occurrence of different eruptive events that take place in the solar atmosphere. The most characteristic of these regions are those that have opposite magnetic polarity, which, in their

Hugues Thomas

Recent attempts at introducing rotation invariance or equivariance in 3D deep learning approaches have shown promising results, but these methods still struggle to reach the performances of standard 3D neural networks. In this work we study the relation between equivariance and invariance in 3D point convolutions. We show that using rotation-equivariant alig

L. Moncelsi, P. A. R. Ade, Z. Ahmed, M. Amiri

A detection of curl-type ($B$-mode) polarization of the primary CMB would be direct evidence for the inflationary paradigm of the origin of the Universe. The BICEP/Keck Array (BK) program targets the degree angular scales, where the power from primordial $B$-mode polarization is expected to peak, with ever-increasing sensitivity and has published the most st

A. C. S. Readhead, V. Ravi, I. Liodakis, M. L. Lister

PKS 1413+135 is one of the most peculiar blazars known. Its strange properties led to the hypothesis almost four decades ago that it is gravitationally lensed by a mass concentration associated with an intervening galaxy. It exhibits symmetric achromatic variability, a rare form of variability that has been attributed to gravitational milli-lensing. It has b

A. George, M. V. Fistul, M. Gruenewald, D. Kaiser

Monolayer transition metal dichalcogenides (TMD) have numerous potential applications in ultrathin electronics and photonics. The exposure of TMD based devices to light generates photo-carriers resulting in an enhanced conductivity, which can be effectively used, e.g., in photodetectors. If the photo-enhanced conductivity persists after removal of the irradi

Saleh O. Allehabi, V. A. Dzuba, V. V. Flambaum, A. V. Afanasjev

We perform atomic relativistic many-body calculations of the field isotope shifts and calculations of corresponding nuclear parameters for all stable even-even isotopes of Yb$^+$ ion. We demonstrate that if we take nuclear parameters of the Yb isotopes from a range of the state-the-art nuclear models which all predict strong quadrupole nuclear deformation, t

Johannes Puschnig, Magnus Näslund, Axel Schwope, Stefan Wallner

In the last decade numerous Sky Quality Meters (SQMs) were installed throughout the globe, aiming to assess the temporal change of the night sky brightness (NSB), and thus the change in light pollution. However, it has become clear that SQM readings may be affected by aging effects such as degradation of the sensor sensitivity and/or loss of transmissivity o

Bashar Alhnaity, Stefanos Kollias, Georgios Leontidis, Shouyong Jiang

Multi-step prediction is considered of major significance for time series analysis in many real life problems. Existing methods mainly focus on one-step-ahead forecasting, since multiple step forecasting generally fails due to accumulation of prediction errors. This paper presents a novel approach for predicting plant growth in agriculture, focusing on predi

Vitalij M. Bondarenko, Vyacheslav Futorny, Anatolii P. Petravchuk, Vladimir V. Sergeichuk

I.M. Gelfand and V.A. Ponomarev (1969) proved that the problem of classifying pairs (A,B) of commuting nilpotent operators on a vector space contains the problem of classifying an arbitrary t-tuple of linear operators. Moreover, it contains the problem of classifying representations of an arbitrary quiver, and so it is considered as hopeless. We give a simpl

Tao Zhou, Mathew Cherukara, Charudatta Phatak

Lorentz transmission electron microscopy is a unique characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials at high spatial resolution. The quantitative information such as magnetization and electric potentials is carried by the phase of the electron wave, and is lost during imaging.

Pedro J. Colmenares

This work sets the exact equations for the quasiclassical response function and susceptibility of a Brownian particle immersed in a bath of quantum harmonic oscillators driving by nonlinear harmonic potentials. A delta force perturbation gives rise to a response whose susceptibility is the combination of a linear term, own of the harmonic oscillator, plus a

Y. Sultan Abylkairov, Omar Darwish, J. Colin Hill, Blake D. Sherwin

Internal Linear Combination (ILC) methods are some of the most widely used multi-frequency cleaning techniques employed in CMB data analysis. These methods reduce foregrounds by minimizing the total variance in the coadded map (subject to a signal-preservation constraint), although often significant foreground residuals or biases remain. A modification to th

Arantxa Casanova, Michal Drozdzal, Adriana Romero-Soriano

Although recent complex scene conditional generation models generate increasingly appealing scenes, it is very hard to assess which models perform better and why. This is often due to models being trained to fit different data splits, and defining their own experimental setups. In this paper, we propose a methodology to compare complex scene conditional gene

A. W. Shaw, R. M. Plotkin, J. C. A. Miller-Jones, J. Homan

Black hole X-ray binaries in the quiescent state (Eddington ratios typically $\lesssim$10$^{-5}$) display softer X-ray spectra (photon indices $Γ\sim2$) compared to higher-luminosity black hole X-ray binaries in the hard state ($Γ\sim1.7$). However, the cause of this softening, and its implications for the underlying accretion flow, are still uncertain. Here

Andrew Y. Joe, Luis A. Jauregui, Kateryna Pistunova, Andrés M. Mier Valdivia

Excitons are composite bosons that can feature spin singlet and triplet states. In usual semiconductors, without an additional spin-flip mechanism, triplet excitons are extremely inefficient optical emitters. Transition metal dichalcogenides (TMDs), with their large spin-orbit coupling, have been of special interest for valleytronic applications for their co

Y. Tarricq, C. Soubiran, L. Casamiquela, T. Cantat-Gaudin

Open Clusters (OCs) can trace with a great accuracy the evolution of the Galactic disk. The aim of this work is to study the kinematical behavior of the OC population over time. We take advantage of the latest age determinations of OCs to investigate the correlations of the 6D phase space coordinates and orbital properties with age. We also investigate the r

Huyuan Chen, Mousomi Bhakta, Hichem Hajaiej

In this paper, we show the existence of a sequence of eigenvalues for a Dirichlet problem involving two mixed fractional operators with different orders. We provide lower and upper bounds for the sum of the eigenvalues. Applications of mixed fractional operators with different orders include medicine, plasma physics, and population dynamics.

J. C. Gómez-Larrañaga, F. González-Acuña, Wolfgang Heil

We describe a method for counting the number of $1$-connected trivalent $2$-stratifolds with a given number of singular curves and $2$-manifold components.

Dmitri I. Panyushev, Oksana S. Yakimova

Let $\mathfrak g$ be a semisimple Lie algebra, $\mathfrak h\subset\mathfrak g$ a reductive subalgebra such that $\mathfrak h^\perp$ is a complementary $\mathfrak h$-submodule of $\mathfrak g$. In 1983, Bogoyavlenski claimed that one obtains a Poisson commutative subalgebra of the symmetric algebra ${\mathcal S}(\mathfrak g)$ by taking the subalgebra ${\mathc

Minh Bui, Michael Lu, Reza Hojabr, Mo Chen

Hamilton-Jacobi reachability analysis is a powerful technique used to verify the safety of autonomous systems. This method is very good at handling non-linear system dynamics with disturbances and flexible set representations. A drawback to this approach is that it suffers from the curse of dimensionality, which prevents real-time deployment on safety-critic

Ajaykumar Unagar, Yuan Tian, Manuel Arias-Chao, Olga Fink

Lithium-Ion (Li-I) batteries have recently become pervasive and are used in many physical assets. To enable a good prediction of the end of discharge of batteries, detailed electrochemical Li-I battery models have been developed. Their parameters are typically calibrated before they are taken into operation and are typically not re-calibrated during operatio

Asmaa Boujibar, Samantha Howell, Shuang Zhang, Grethe Hystad

Cluster analysis of presolar silicon carbide grains based on literature data for 12C/13C, 14N/15N, δ30Si/28Si, and δ29Si/28Si including or not inferred initial 26Al/27Al data, reveals nine clusters agreeing with previously defined grain types but also highlighting new divisions. Mainstream grains reside in three clusters probably representing different paren

Surangkhana Rukdee, Sagi Ben-Ami, Andrew Szentgyorgyi, Mercedes López-Morales

The upcoming Extremely Large Telescopes (ELTs) are expected to have the collecting area required to detect potential biosignature gases in the atmosphere of rocky planets around nearby low-mass stars. Some efforts are currently focusing on searching for molecular oxygen (O2), since O2 is a known biosignature on Earth. One of the most promising methods to sea

Veysel Kocaman, David Talby

Following the global COVID-19 pandemic, the number of scientific papers studying the virus has grown massively, leading to increased interest in automated literate review. We present a clinical text mining system that improves on previous efforts in three ways. First, it can recognize over 100 different entity types including social determinants of health, a

Mai Gehrke, Michael Pinsker

We show that pseudovarieties of finitely generated algebras, i.e., classes $C$ of finitely generated algebras closed under finite products, homomorphic images, and subalgebras, can be described via a uniform structure $U$ on the free algebra for $C$: the members of $C$ then are precisely those finitely generated algebras $A$ for which the natural mapping fro

Jiarui Xing, Sona Ghadimi, Mohammad Abdishektaei, Kenneth C. Bilchick

This paper presents a novel method to automatically identify late-activating regions of the left ventricle from cine Displacement Encoding with Stimulated Echo (DENSE) MR images. We develop a deep learning framework that identifies late mechanical activation in heart failure patients by detecting the Time to the Onset of circumferential Shortening (TOS). In

Mohammad Keshavarzi, Oladapo Afolabi, Luisa Caldas, Allen Y. Yang

The availability of rich 3D datasets corresponding to the geometrical complexity of the built environments is considered an ongoing challenge for 3D deep learning methodologies. To address this challenge, we introduce GenScan, a generative system that populates synthetic 3D scan datasets in a parametric fashion. The system takes an existing captured 3D scan

Damian R Sowinski, Matthew DJ McGarry, Elijah Van Houten, Scott Gordon-Wylie

Magnetic Resonance Elastography allows noninvasive visualization of tissue mechanical properties by measuring the displacements resulting from applied stresses, and fitting a mechanical model. Poroelasticity naturally lends itself to describing tissue -- a biphasic medium, consisting of both solid and fluid components. This article reviews the theory of poro

M. Fabbrichesi, C. M. Nieto, A. Tonero, A. Ugolotti

We minimally extend the Standard Model field content by adding new vector-like fermions at the TeV scale to allow gauge coupling unification at a realistic scale. We embed the model into a $SU(5)$ grand unified theory that is asymptotically safe and features an interacting fixed point for the gauge coupling. There are no Landau poles of the $U(1)$ gauge and

Tarun Tummuru, Oguzhan Can, Marcel Franz

A superconductor with $p_x+ip_y$ order has long fascinated the physics community because vortex defects in such a system host Majorana zero modes. Here we propose a simple construction of a chiral superconductor using proximitized quantum wires and twist angle engineering as basic ingredients. We show that a weakly coupled parallel array of such wires forms