October 2020 arXiv papers — page 98

Areti Kotsi, Tom Lusco, Evangelos Mitsakis, Steve Sill

Cooperative Intelligent Transportation Systems (C-ITS) constitute technologies which enable vehicles to communicate with each other and/ or with the infrastructure. C-ITS include systems and services which use different components, in order to share and exchange information via diverse communication interfaces. Since various C-ITS deployment initiatives have

Tahir Miriyev, Alessandro Contu, Kevin Schafers, Ion Gabriel Ion

In this work we considered several hybrid modelling approaches for forecasting energy spot prices in EPEC market. Hybridization is performed through combining a Naive model, Fourier analysis, ARMA and GARCH models, a mean-reversion and jump-diffusion model, and Recurrent Neural Networks (RNN). Training data was given in terms of electricity prices for 2013-2

Marek Adamczyk, Brian Brubach, Fabrizio Grandoni, Karthik A. Sankararaman

We consider the Stochastic Matching problem, which is motivated by applications in kidney exchange and online dating. In this problem, we are given an undirected graph. Each edge is assigned a known, independent probability of existence and a positive weight (or profit). We must probe an edge to discover whether or not it exists. Each node is assigned a posi

Ankur Verma

Lately, personalized marketing has become important for retail/e-retail firms due to significant rise in online shopping and market competition. Increase in online shopping and high market competition has led to an increase in promotional expenditure for online retailers, and hence, rolling out optimal offers has become imperative to maintain balance between

Ewa Nowara, Daniel McDuff, Ashok Veeraraghavan

Attention is a powerful concept in computer vision. End-to-end networks that learn to focus selectively on regions of an image or video often perform strongly. However, other image regions, while not necessarily containing the signal of interest, may contain useful context. We present an approach that exploits the idea that statistics of noise may be shared

Patrick Das Gupta

Freeman J. Dyson, a brilliant theoretical physicist and a gifted mathematician, passed away on 28 February 2020 at the age of 96. A vignette of his outstanding contributions to physical sciences, ranging from the subject of quantum electrodynamics to gravitational waves, is provided in this article. Dyson's futuristic ideas concerning the free will of `i

Rene van der Vegt

The Goldbach conjecture that, every even integer is the sum of two primes, has been open since 1742. This paper details a road map to a proof of Goldbachs conjecture based on a function that estimates the number of Goldbach pairs. It is shown that the estimate of the number of Goldbach pairs increases as the even integer increases and that the error term is

Tarek Saanouni

This note studies the asymptotic behavior of global solutions to the fourth-order generalized Hartree equation $$i\dot u+Δ^2 u\pm(I_α*|u|^p)|u|^{p-2}u=0.$$ Indeed, for both attractive and repulsive sign, the scattering is obtained in the mass super-critical and energy sub-critical regimes, with radial setting.

Todd Mullen, Richard Nowakowski, Danielle Cox

In the chip-firing variant, Diffusion, chips flow from places of high concentration to places of low concentration (or equivalently, from the rich to the poor). We explore this model on complete graphs, determining the number of different ways that chips can be distributed on an unlabelled complete graph and demonstrate connections to polyominoes.

Francisco M. Fernández

We analyze recent results for a harmonic oscillator in an environment with a pointlike defect. We show that the allowed oscillator frequencies predicted by the authors stem from a misinterpretation of the exact solutions of a conditionally solvable eigenvalue equation. Also the exact eigenvalues derived by those authors are meaningless because they belong to

Walid R. Ghanem, Vahid Jamali, Robert Schober

This paper investigates the resource allocation algorithm design for intelligent reflecting surface (IRS) aided multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) multicell networks, where a set of base stations cooperate to serve a set of ultra-reliable low-latency communication (URLLC) users. The IRS is deployed to en

N. A. Kuleeva, E. Z. Kuchinskii, M. V. Sadovskii

We present a short review of our studies of disorder influence upon Ginzburg - Landau expansion coefficients in Anderson - Hubbard model with attraction in the framework of the generalized DMFT+$Σ$ approximation. A wide range of attractive potentials $U$ is considered - from weak coupling limit, where superconductivity is described by BCS model, to the limit

Rafeel Riaz, Dominik R. G. Schleicher, Siegfried Vanaverbeke, Ralf S. Klessen

The stellar Initial Mass Function (IMF) seems to be close to universal in the local star-forming regions. However, this quantity of a newborn stellar population responds differently at gas metallicities $Z \sim$ $Z_\odot$ than $Z$ = 0. A view on the cosmic star formation history suggests that the cooling agents in the gas vary both in their types and molecul

Qingyi Zhan, Jinqiao Duan, Xiaofan Li, Yuhong Li

A class of Hamiltonian stochastic differential equations with multiplicative Lévy noise in the sense of Marcus, and the construction and numerical implementation methods of symplectic Euler scheme, are considered. A general symplectic Euler scheme for this kind of Hamiltonian stochastic differential equations is devised, and its convergence theorem is proved

Elena del Olmo Suárez, Ana María Fernández-Pampillón Cesteros

The purpose of this article is to present a new approach for the discovery and labelling of the implicit conceptual schema of texts through the application of the Thematic Progression theory. The underlying conceptual schema is the core component for the generation of summaries that are genuinely consistent with the semantics of the text.

Diego Rybski, Boris F. Prahl, Markus Boettle, Jürgen P. Kropp

Damage cost curves -- relating the typical damage of a natural hazard to its physical magnitude -- represent an indispensable ingredient necessary for climate change impact assessments. Combining such curves with the occurrence probability of the considered natural hazard, expected damage and related risk can be estimated. Here we study recently published ci

Bobby Samir Acharya, Alex Kinsella, Eirik Eik Svanes

We consider the heterotic string on Calabi-Yau manifolds admitting a Strominger-Yau-Zaslow fibration. Upon reducing the system in the $T^3$-directions, the Hermitian Yang-Mills conditions can then be reinterpreted as a complex flat connection on $\mathbb{R}^3$ satisfying a certain co-closure condition. We give a number of abelian and non-abelian examples, an

Axel Wismüller, Larry Stockmaster

Objective: To introduce a method for tracking results and utilization of Artificial Intelligence (tru-AI) in radiology. By tracking both large-scale utilization and AI results data, the tru-AI approach is designed to calculate surrogates for measuring important disease-related observational quantities over time, such as the prevalence of intracranial hemorrh

A. M. Yasser, G. S. Hassan, Samah K. Elshamndy, M. S. Ali

Two numerical methods are developed to reduce the solution of the radial Schrödinger equation for proposed heavy quark-antiquark interactions, into the solution of the eigenvalue problem for the infinite system of tridiagonal matrices. Our perspective is a numerical approach relies on finding the proper numerical method to investigate the static properties o

Maryam Hashemzadeh, Greta Kaufeld, Martha White, Andrea E. Martin

The representations generated by many models of language (word embeddings, recurrent neural networks and transformers) correlate to brain activity recorded while people read. However, these decoding results are usually based on the brain's reaction to syntactically and semantically sound language stimuli. In this study, we asked: how does an LSTM (long s

Felicity F. Nielson, Sean M. Colby, Dennis G. Thomas, Ryan S. Renslow

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weight

Maggie Miller, Patrick Naylor

We study trisections of smooth, compact non-orientable 4-manifolds, and introduce trisections of non-orientable 4-manifolds with boundary. In particular, we prove a non-orientable analogue of a classical theorem of Laudenbach-Poénaru. As a consequence, trisection diagrams and Kirby diagrams of closed non-orientable 4-manifolds exist. We discuss how the theor

Yinyu Nie, Yiqun Lin, Xiaoguang Han, Shihui Guo

Point completion refers to complete the missing geometries of objects from partial point clouds. Existing works usually estimate the missing shape by decoding a latent feature encoded from the input points. However, real-world objects are usually with diverse topologies and surface details, which a latent feature may fail to represent to recover a clean and

Harsh Bimal Desai, Mustafa Safa Ozdayi, Murat Kantarcioglu

Federated Learning (FL) is a distributed, and decentralized machine learning protocol. By executing FL, a set of agents can jointly train a model without sharing their datasets with each other, or a third-party. This makes FL particularly suitable for settings where data privacy is desired. At the same time, concealing training data gives attackers an opport

Isaac H. Kim

We propose a family of "exactly solvable" probability distributions to approximate partition functions of two-dimensional statistical mechanics models. While these distributions lie strictly outside the mean-field framework, their free energies can be computed in a time that scales linearly with the system size. This construction is based on a simple

Marie Cottrell, Cynthia Faure, Jérôme Lacaille, Madalina Olteanu

The anomaly detection problem for univariate or multivariate time series is a critical question in many practical applications as industrial processes control, biological measures, engine monitoring, supervision of all kinds of behavior. In this paper we propose a simple and empirical approach to detect anomalies in the behavior of multivariate time series.

Christopher N. Shingledecker, Sebastien Incerti, Alexei Ivlev, Dimitris Emfietzoglou

Cosmic rays are ubiquitous in interstellar environments, and their bombardment of dust-grain ice mantles is a possible driver for the formation of complex, even prebiotic molecules. Yet, critical data that are essential for accurate modeling of this phenomenon, such as the average radii of cosmic-ray tracks in amorphous solid water (ASW) remain unconstrained

Donald J. Docimo, Ziliang Kang, Kai A. James, Andrew G. Alleyne

This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal d

Ilan Price, Jordan Gifford-Moore, Jory Fleming, Saul Musker

We present a new dataset of approximately 44000 comments labeled by crowdworkers. Each comment is labelled as either 'healthy' or 'unhealthy', in addition to binary labels for the presence of six potentially 'unhealthy' sub-attributes: (1) hostile; (2) antagonistic, insulting, provocative or trolling; (3) dismissive; (4) condescending

Andreas Bereczuk, Barbara Dietz, Jiongning Che, Jack Kuipers

We present an in-depth study of the universal correlations of scattering-matrix entries required in the framework of non-stationary many-body scattering where the incoming states are localized wavepackets. Contrary to the stationary case the emergence of universal signatures of chaotic dynamics in dynamical observables manifests itself in the emergence of un

Miguel Dajer, Zhengxiang Ma, Leonard Piazzi, Narayan Prasad

In this paper, we survey state-of-the-art research outcomes in the burgeoning field of reconfigurable intelligent surface (RIS) in view of its potential for significant performance enhancement for next generation wireless communication networks by means of adapting the propagation environment. Emphasis has been placed on several aspects gating the commercial

Luis Trucios, Mahdi Tavakoli, Kim Adams

This paper presents a -- Learning from Demonstration -- method to perform robot movement trajectories that can be defined as you go. This way unstructured tasks can be performed, without the need to know exactly all the tasks and start and end positions beforehand. The long-term goal is for children with disabilities to be able to control a robot to manipula

Neta Dafni, Yuval Filmus, Noam Lifshitz, Nathan Lindzey

We extend the definitions of complexity measures of functions to domains such as the symmetric group. The complexity measures we consider include degree, approximate degree, decision tree complexity, sensitivity, block sensitivity, and a few others. We show that these complexity measures are polynomially related for the symmetric group and for many other dom

Sonja Schmid, Cees Dekker

Proteins are the active working horses in our body. These biomolecules perform all vital cellular functions from DNA replication and general biosynthesis to metabolic signaling and environmental sensing. While static 3D structures are now readily available, observing the functional cycle of proteins - involving conformational changes and interactions - remai

S. L. Casewell, J. Debes, I. P. Braker, M. C. Cushing

We present Spitzer observations at 3.6 and 4.5 microns and a near-infrared IRTF SpeX spectrum of the irradiated brown dwarf NLTT5306B. We determine that the brown dwarf has a spectral type of L5 and is likely inflated, despite the low effective temperature of the white dwarf primary star. We calculate brightness temperatures in the Spitzer wavebands for both

S. Mahdavi, A. R. Ashrafi, M. A. Salahshour

Suppose that $G$ is a groupoid with binary operation $\otimes$. The pair $(G,\otimes)$ is said to be a gyrogroup if the operation $\otimes$ has a left identity, each element $a \in G$ has a left inverse and the gyroassociative law and the left loop property are satisfied in $G$. In this paper, a method for constructing new gyrogroups from old ones is present

S. S. Larsen, A. J. Romanowsky, J. P. Brodie, A. Wasserman

Globular clusters (GCs) are dense, gravitationally bound systems of thousands to millions of stars. They are preferentially associated with the oldest components of galaxies, and measurements of their composition can therefore provide insight into the build-up of the chemical elements in galaxies in the early Universe. We report a massive GC in the Andromeda

Victor I. Danchev, Daniela D. Doneva

Modern multi-messenger astronomical observations and heavy ion experiments provide new insights into the structure of compact objects. Nevertheless, much ambiguity remains when it comes to super dense matter above the nuclear saturation density such as that found within neutron stars. This work explores equation of state (EOS)-independent universal relations

I. Y. Lee, A. O. Macchiavelli

We present a study of magnetic fields effects on the position resolution and energy response of hyper-pure germanium detectors. Our results provide realistic estimates of the potential impact on the resolving power of tracking-arrays from (fringe) magnetic fields present when operating together with large spectrometers. By solving the equations of motion for

V. Dudnikov

A large volume surface plasma source (SPS) with a biased converter was developed for the Los Alamos linear accelerator. A large gas-discharge chamber with a multipole magnetic wall and 2 heated cathodes can support a discharge generating plasma. A cooled converter with a diameter of 5 cm and a potential of up to -300 V bombarded by positive ions and emits se

Tom Begley, Tobias Schwedes, Christopher Frye, Ilya Feige

As the decisions made or influenced by machine learning models increasingly impact our lives, it is crucial to detect, understand, and mitigate unfairness. But even simply determining what "unfairness" should mean in a given context is non-trivial: there are many competing definitions, and choosing between them often requires a deep understanding of

Andrei V. Konstantinov, Lev V. Utkin

A method for the local and global interpretation of a black-box model on the basis of the well-known generalized additive models is proposed. It can be viewed as an extension or a modification of the algorithm using the neural additive model. The method is based on using an ensemble of gradient boosting machines (GBMs) such that each GBM is learned on a sing

Gang Xu, Andrey Gelash, Amin Chabchoub, Vladimir Zakharov

Mutual interaction of localized nonlinear waves, e.g. solitons and modulation instability patterns, is a fascinating and intensively-studied topic of nonlinear science. In this research report, we report on the observation of a novel type of breather interaction in telecommunication optical fibers, in which two identical breathers propagate with opposite gro

Corina Birghila, Tim J. Boonen, Mario Ghossoub

We examine a problem of demand for insurance indemnification, when the insured is sensitive to ambiguity and behaves according to the Maxmin-Expected Utility model of Gilboa and Schmeidler (1989), whereas the insurer is a (risk-averse or risk-neutral) Expected-Utility maximizer. We characterize optimal indemnity functions both with and without the customary

Miranda Mundt, Evan Harvey

We are research software engineers and team members in the Department of Software Engineering and Research at Sandia National Laboratories, an organization which aims to advance software engineering in the domain of computational science. Our team hopes to promote processes and principles that lead to quality, rigor, correctness, and repeatability in the imp

Naci Saldi, Serdar Yuksel

In many areas of applied mathematics, engineering, and social and natural sciences, decentralization of information is a key aspect determining how to approach a problem. In this review article, we study information structures in a probability theoretic and geometric context. We define information structures, place various topologies on them, and study close

Jean-Samuel Leboeuf, Frédéric LeBlanc, Mario Marchand

Decision trees are popular machine learning models that are simple to build and easy to interpret. Even though algorithms to learn decision trees date back to almost 50 years, key properties affecting their generalization error are still weakly bounded. Hence, we revisit binary decision trees on real-valued features from the perspective of partitions of the

Hongjie Chen, Ryan A. Rossi, Kanak Mahadik, Sungchul Kim

Deep probabilistic forecasting techniques have recently been proposed for modeling large collections of time-series. However, these techniques explicitly assume either complete independence (local model) or complete dependence (global model) between time-series in the collection. This corresponds to the two extreme cases where every time-series is disconnect

Abel B. Stern, Walter D. van Suijlekom

We define Schatten classes of adjointable operators on Hilbert modules over abelian $C^*$-algebras. Many key features carry over from the Hilbert space case. In particular, the Schatten classes form two-sided ideals of compact operators and are equipped with a Banach norm and a $C^*$-valued trace with the expected properties. For trivial Hilbert bundles, we

Daniel Maldonado-Lopez, Noboru Takeuchi, Jonathan Guerrero-Sanchez

We provide a complete and systematic first-principles study of the thermodynamic stability, structural parameters, and magnetic properties of the T1 non-collinear antiferromagnetic L1$_2$-IrMn$_3$ surface and L1$_2$-IrMn$_3$/Fe heterostructure. Furthermore, we investigate the exchange-bias effect in the heterostructure and describe its previously unknown com

David Jorrin, Martin Schvellinger

The role of local higher-twist ($τ> 3$) spin-1/2 fermionic operators of the strongly coupled ${\cal {N}}=4$ supersymmetric Yang-Mills theory on the symmetric and antisymmetric deep inelastic scattering (DIS) structure functions is investigated. The calculations are carried out in terms of the duality between ${\cal {N}}=4$ SYM theory and type IIB supergravit

Laura Capuano, Nadir Murru, Lea Terracini

The classical theory of continued fractions has been widely studied for centuries for its important properties of good approximation, and more recently it has been generalized to $p$-adic numbers where it presents many differences with respect to the real case. In this paper we investigate periodicity for the $p$-adic continued fractions introduced by Browki

C. García

This paper deals with the existence of $N$ vortex patches located at the vertex of a regular polygon with $N$ sides that rotate around the center of the polygon at a constant angular velocity. That is done for Euler and (SQG)$_β$ equations, with $β\in(0,1)$, but may be also extended to more general models. The idea is the desingularization of the Thomsom pol

Nalinda Kulathunga, Nishath Rajiv Ranasinghe, Daniel Vrinceanu, Zackary Kinsman

The nonlinearity of activation functions used in deep learning models are crucial for the success of predictive models. There are several commonly used simple nonlinear functions, including Rectified Linear Unit (ReLU) and Leaky-ReLU (L-ReLU). In practice, these functions remarkably enhance the model accuracy. However, there is limited insight into the funct

Benjamin Newman, Kevin Carlberg, Ruta Desai

Augmented-reality (AR) glasses that will have access to onboard sensors and an ability to display relevant information to the user present an opportunity to provide user assistance in quotidian tasks. Many such tasks can be characterized as object-rearrangement tasks. We introduce a novel framework for computing and displaying AR assistance that consists of

L. E. Montañez, L. M. Valentín-Coronado, D. Moctezuma, G. Flores

The growing interest in the use of clean energy has led to the construction of increasingly large photovoltaic systems. Consequently, monitoring the proper functioning of these systems has become a highly relevant issue.In this paper, automatic detection, and analysis of photovoltaic modules are proposed. To perform the analysis, a module identification step

Ben Adlam, Jaehoon Lee, Lechao Xiao, Jeffrey Pennington

Modern deep learning models have achieved great success in predictive accuracy for many data modalities. However, their application to many real-world tasks is restricted by poor uncertainty estimates, such as overconfidence on out-of-distribution (OOD) data and ungraceful failing under distributional shift. Previous benchmarks have found that ensembles of n

Ignacio Borsa, Daniel de Florian, Iván Pedron

We present the calculation for single-inclusive jet production in (longitudinally) polarized deep-inelastic lepton-nucleon scattering at next-to-next-to leading order (NNLO) accuracy, based on the Projection-to-Born method. As a necessary ingredient to achieve the NNLO results, we also introduce the next-to-leading-order (NLO) calculation for the production

Changjiang Cai, Philippos Mordohai

Deep networks for stereo matching typically leverage 2D or 3D convolutional encoder-decoder architectures to aggregate cost and regularize the cost volume for accurate disparity estimation. Due to content-insensitive convolutions and down-sampling and up-sampling operations, these cost aggregation mechanisms do not take full advantage of the information avai

Adam Peterson, Veronica Berrocal, Emma Sanchez-Vaznaugh, Brisa Sanchez

Built environment features (BEFs) refer to aspects of the human constructed environment, which may in turn support or restrict health related behaviors and thus impact health. In this paper we are interested in understanding whether the spatial distribution and quantity of fast food restaurants (FFRs) influence the risk of obesity in schoolchildren. To achie

Changjiang Cai, Matteo Poggi, Stefano Mattoccia, Philippos Mordohai

End-to-end deep networks represent the state of the art for stereo matching. While excelling on images framing environments similar to the training set, major drops in accuracy occur in unseen domains (e.g., when moving from synthetic to real scenes). In this paper we introduce a novel family of architectures, namely Matching-Space Networks (MS-Nets), with i

Thomas Kesselheim, Sahil Singla

We introduce online learning with vector costs (\OLVCp) where in each time step $t \in \{1,\ldots, T\}$, we need to play an action $i \in \{1,\ldots,n\}$ that incurs an unknown vector cost in $[0,1]^{d}$. The goal of the online algorithm is to minimize the $\ell_p$ norm of the sum of its cost vectors. This captures the classical online learning setting for $

Qing-Ge Mu, Dennis Nenno, Yan-Peng Qi, Feng-Ren Fan

A Weyl semimetal with strong electron-phonon interaction can show axionic coupling in its insulator state at low temperatures, owing to the formation of a charge density wave (CDW). Such a CDW emerges in the linear chain compound Weyl semimetal Ta$_2$Se$_8$I below 263 K, resulting in the appearance of the dynamical condensed-matter axion quasiparticle. In th

Atish Agarwala, Jeffrey Pennington, Yann Dauphin, Sam Schoenholz

The softmax function combined with a cross-entropy loss is a principled approach to modeling probability distributions that has become ubiquitous in deep learning. The softmax function is defined by a lone hyperparameter, the temperature, that is commonly set to one or regarded as a way to tune model confidence after training; however, less is known about ho

Haoyu Chen, Wenbin Lu, Rui Song

Online decision making aims to learn the optimal decision rule by making personalized decisions and updating the decision rule recursively. It has become easier than before with the help of big data, but new challenges also come along. Since the decision rule should be updated once per step, an offline update which uses all the historical data is inefficient

Łukasz Korycki, Bartosz Krawczyk

Learning from data streams is among the most vital fields of contemporary data mining. The online analysis of information coming from those potentially unbounded data sources allows for designing reactive up-to-date models capable of adjusting themselves to continuous flows of data. While a plethora of shallow methods have been proposed for simpler low-dimen

Maarten Van Damme, Jad C. Halimeh, Philipp Hauke

Gauge symmetry plays a key role in our description of subatomic matter. The vanishing photon mass, the long-ranged Coulomb law, and asymptotic freedom are all due to gauge invariance. Recent years have seen tantalizing progress in the microscopic reconstruction of gauge theories in engineered quantum simulators. Yet, many of these are plagued by a fundamenta

Andrew Blance, Michael Spannowsky

Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in solving classification problems. Our algorithm is designed for existing and near-term quantum devices. We propose a novel

Chen Zhu, Zheng Xu, Ali Shafahi, Manli Shu

When large scale training data is available, one can obtain compact and accurate networks to be deployed in resource-constrained environments effectively through quantization and pruning. However, training data are often protected due to privacy concerns and it is challenging to obtain compact networks without data. We study data-free quantization and prunin

David Sloan

We present a new action which reproduces the cosmological sector of general relativity in both the Friedmann-Lemaitre-Robertson-Walker (FLRW) and Bianchi models. This action makes no reference to the scale factor, and is of a frictional type first examined by Herglotz. We demonstrate that the extremization of this action reproduces the usual dynamics of phys

Saikat Santra, Adhip Agarwala, Subhro Bhattacharjee

We show that mutual statistics between quantum particles can be tuned to generate emergent novel few particle quantum mechanics for the boundary modes of symmetry-protected topological phases of matter. As a concrete setting, we study a system of pseudofermions, defined as quantum particles with tunable algebra, which lie on two distinct Su-Schrieffer-Heeger

Andrea López-Incera, Morgane Nouvian, Katja Ried, Thomas Müller

Social insect colonies routinely face large vertebrate predators, against which they need to mount a collective defense. To do so, honeybees use an alarm pheromone that recruits nearby bees into mass stinging of the perceived threat. This alarm pheromone is carried directly on the stinger, hence its concentration builds up during the course of the attack. He

Zili Shen, Pieter van Dokkum, Shany Danieli

NGC1052-DF2 and NGC1052-DF4 are ultra-diffuse galaxies (UDGs) that were found to have extremely low velocity dispersions, indicating that they have little or no dark matter. Both galaxies host anomalously luminous globular cluster (GC) systems, with a peak magnitude of their GC luminosity function (GCLF) that is $\sim1.5$ magnitudes brighter than the near-un

Warrick H. Ball, William J. Chaplin, Martin B. Nielsen, Lucia González-Cuesta

The Transiting Exoplanet Survey Satellite (TESS) is recording short-cadence, high duty-cycle timeseries across most of the sky, which presents the opportunity to detect and study oscillations in interesting stars, in particular planet hosts. We have detected and analysed solar-like oscillations in the bright G4 subgiant HD 38529, which hosts an inner, roughl

Willem Elbers, Carlos S. Frenk, Adrian Jenkins, Baojiu Li

Cosmology places the strongest current limits on the sum of neutrino masses. Future observations will further improve the sensitivity and this will require accurate cosmological simulations to quantify possible systematic uncertainties and to make predictions for nonlinear scales, where much information resides. However, shot noise arising from neutrino ther

Z. Ansari, A. Agnello, C. Gall

Determining photometric redshifts to high accuracy is paramount to measure distances in wide-field cosmological experiments. With only photometric information at hand, photo-zs are prone to systematic uncertainties in the intervening extinction and the unknown underlying spectral-energy distribution of different astrophysical sources. Here, we aim to resolve

Marta L. Bryan, Sivan Ginzburg, Eugene Chiang, Caroline Morley

To understand how planetary spin evolves and traces planet formation processes, we measure rotational line broadening in eight planetary-mass objects (PMOs) of various ages (1--800 Myr) using near-infrared high-resolution spectra from NIRSPEC/Keck. Combining these with published rotation rates, we compile 27 PMO spin velocities, 16 of which derive from our N

Georgios Vernardos, Grigorios Tsagkatakis, Yannis Pantazis

Gravitational lensing is a powerful tool for constraining substructure in the mass distribution of galaxies, be it from the presence of dark matter sub-halos or due to physical mechanisms affecting the baryons throughout galaxy evolution. Such substructure is hard to model and is either ignored by traditional, smooth modelling, approaches, or treated as well

Duncan A. Forbes, Jonah S. Gannon, Aaron J. Romanowsky, Adebusola Alabi

The ultra-diffuse galaxy in the NGC 5846 group (NGC 5846_UDG1) was shown to have a large number of globular cluster (GC) candidates from deep imaging as part of the VEGAS survey. Recently, Muller et al. published a velocity dispersion, based on a dozen of its GCs. Within their quoted uncertainties, the resulting dynamical mass allowed for either a dark matte

Tom Doekle Vethaak, Frederic Gustavo, Thierry Farjot, Tomas Kubart

Thin films of superconducting V$_3$Si were prepared by means of RF sputtering from a compound V$_3$Si target at room temperature onto sapphire and oxide-coated silicon wafers, followed by rapid thermal processing under secondary vacuum. The superconducting properties of the films thus produced are found to improve with annealing temperature, which is ascribe

Jenifer S. Millard, Benedikt Diemer, Stephen A. Eales, Haley L. Gomez

We investigate the evolution in galactic dust mass over cosmic time through i) empirically derived dust masses using stacked submillimetre fluxes at 850um in the COSMOS field, and ii) dust masses derived using a robust post-processing method on the results from the cosmological hydrodynamical simulation IllustrisTNG. We effectively perform a self-calibration

Marcus Brüggen, Evan Scannapieco

We carry out a suite of simulations of the evolution of cosmic-ray (CR) driven, radiatively-cooled cold clouds embedded in hot material, as found in galactic outflows. In such interactions, CRs stream towards the cloud at the Alfvén speed, which decreases dramatically at the cloud boundary, leading to a bottleneck in which pressure builds up in front of the

Siddharth Gandhi, Adam S. Jermyn

We provide a new framework to model the day side and night side atmospheres of irradiated exoplanets using 1-D radiative transfer by incorporating a self-consistent heat flux carried by circulation currents (winds) between the two sides. The advantages of our model are its physical motivation and computational efficiency, which allows for an exploration of a

F. Calura, E. Vanzella, S. Carniani, R. Gilli

We report on ALMA observations of D1, a system at z~6.15 with stellar mass M_* ~ 10^7 M_sun containing globular cluster (GC) precursors, strongly magnified by the galaxy cluster MACS J0416.1-2403. Since the discovery of GC progenitors at high redshift, ours is the first attempt to probe directly the physical properties of their neutral gas through infrared o

Areti Kotsi, Evangelos Mitsakis, Dimitris Tzanis

Cooperative Intelligent Transportation Systems (C-ITS) are technologies that enable vehicles to communicate with each other and with the road infrastructure. These innovative technologies enable road users and traffic managers to share useful information, assisting the coordination of their actions. During the last years various initiatives providing policy

Charis Chalkiadakis, Dimitris Tzanis, Evangelos Mitsakis

We live in an ever-aging world. The percentage of older citizens increases in modern societies as older citizens represent the 19.20% of the general population. In Greece, an increase of almost 7% of older citizens has been observed in the last twenty years. As old age never comes alone, age-related impairments should be considered in the effort to provide s

Chrysostomos Mylonas, Charis Chalkiadakis, Alexandros Dolianitis, Dimitris Tzanis

Despite the debate regarding the timeframe and rate of penetration of Autonomous Vehicles, their potential benefits and implications have been widely recognized. Therefore, assessing the readiness of individual countries to adopt such technologies and adapt to their introduction is of particular importance. This paper aims to enrich our understanding of EU r

Vitonofrio Crismale, Rocco Duvenhage, Francesco Fidaleo

A systematic theory of product and diagonal states is developed for tensor products of $\mathbb Z_2$-graded $*$-algebras, as well as $\mathbb Z_2$-graded $C^*$-algebras. As a preliminary step to achieve this goal, we provide the construction of a {\it fermionic $C^*$-tensor product} of $\mathbb Z_2$-graded $C^*$-algebras. Twisted duals of positive linear map

Adriana Mejia Castaño, Javier E Hernandez, Angie Mendez Llanos

With the recent COVID-19 breakup, it became necessary to implement remote classes in schools and universities to safeguard health and life. However, many students (teachers and parents, also) face great difficulties accessing and staying in class due to technology limitations, affecting their education. Using several nationally representative datasets in Col

John Cooper Faile

In this paper I present a new method of studying the densities of the Collatz trajectories generated by a set $S \subset \mathbb{N}$. This method is used to furnish an alternative proof that $d(\{y \in \mathbb{N} : \exists k \text{ where } T^k(y) < cy\}) = 1$ for all $c > 0$. Finally, I briefly discuss how the ideas presented in this paper could be used to i

Ekkehard Krüger

In this paper I report evidence that the antiferromagnetic and insulating ground state of MnO is caused by a nonadiabatic atomic-like motion as it is evidently the case in NiO. In addition, I show that the experimental findings of Goodwin et al. [Phys. Rev. Lett. (2006), 96,~047209] corroborate my suggestion that the rhombohedral-like distortion in antiferro

Cláudio Nassif Cruz, Fernando Antônio da Silva

The cosmology of &#34;Spontaneous Creation of the Universe Ex Nihilo&#34; and the cosmology of the Symmetrical Relativity offer proposals to explain the creation and evolution of the universe. In essence they are still very distinct. However, we will argue that there was an antecedent to the big bang. Thus, we will penetrate a trans-Planckian regime, where w

Paul Glasserman, Kriste Krstovski, Paul Laliberte, Harry Mamaysky

We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance thr

Laura Bussi, Vincenzo Ciancia, Fabio Gadducci

The tool voxlogica merges the state-of-the-art library of computational imaging algorithms ITK with the combination of declarative specification and optimised execution provided by spatial logic model checking. The analysis of an existing benchmark for segmentation of brain tumours via a simple logical specification reached state-of-the-art accuracy. We pres

Haoyu Chen, Wenbin Lu, Rui Song

Online decision-making problem requires us to make a sequence of decisions based on incremental information. Common solutions often need to learn a reward model of different actions given the contextual information and then maximize the long-term reward. It is meaningful to know if the posited model is reasonable and how the model performs in the asymptotic

V. V. Emel&#39;yanenko

Context: The discovery of distant trans-Neptunian objects has led to heated discussions about the structure of the outer Solar System. Aims: We study the dynamical evolution of small bodies from the Hill regions of migrating giant gaseous clumps that form in the outer solar nebula via gravitational fragmentation. We attempt to determine whether the observed

Jan L. Carrasquillo-López, Axel O. Gómez-Flores, Christopher Soto, Fernando Piñero

The current best known $[239, 21], \, [240, 21], \, \text{and} \, [241, 21]$ binary linear codes have minimum distance 98, 98, and 99 respectively. In this article, we introduce three binary Goppa codes with Goppa polynomials $(x^{17} + 1)^6, (x^{16} + x)^6,\text{ and } (x^{15} + 1)^6$. The Goppa codes are $[239, 21, 103], \, [240, 21, 104], \, \text{and} \,

Sambhav Satija, Apurv Mehra, Sudheesh Singanamalla, Karan Grover

We introduce Blockene, a blockchain that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus. Despite being lightweight, Blockene provides a high throughput of transactions and scales to a large number of participants. Blockene consumes negligible battery and data in smar

Bjørn Kjos-Hanssen

For a complexity function $C$, the lower and upper $C$-complexity rates of an infinite word $\mathbf{x}$ are \[ \underline{C}(\mathbf x)=\liminf_{n\to\infty} \frac{C(\mathbf{x}\upharpoonright n)}n,\quad \overline{C}(\mathbf x)=\limsup_{n\to\infty} \frac{C(\mathbf{x}\upharpoonright n)}n \] respectively. Here $\mathbf{x}\upharpoonright n$ is the prefix of $x$

Jonathan Ashbrock

Compressed Sensing algorithms often make use of the hard thresholding operator to pass from dense vectors to their best s-sparse approximations. However, the output of the hard thresholding operator does not depend on any information from a particular problem instance. We propose an alternative thresholding rule, Look Ahead Thresholding, that does. In this p