July 2019 arXiv papers — page 68

Fatima Zahra Azayite, Said Achchab

Predicting firm's failure is one of the most interesting subjects for investors and decision makers. In this paper, a bankruptcy prediction model is proposed based on Artificial Neural networks (ANN). Taking into consideration that the choice of variables to discriminate between bankrupt and non-bankrupt firms influences significantly the model's acc

Huajun Liu, Hui Zhang, Christoph Mertz

The Long Short-Term Memory (LSTM) neural network based data association algorithm named as DeepDA for multi-target tracking in clutters is proposed to deal with the NP-hard combinatorial optimization problem in this paper. Different from the classical data association methods involving complex models and accurate prior knowledge on clutter density, filter co

Benedikt Kleinmeier, Benedikt Zönnchen, Marion Gödel, Gerta Köster

Pedestrian dynamics is an interdisciplinary field of research. Psychologists, sociologists, traffic engineers, physicists, mathematicians and computer scientists all strive to understand the dynamics of a moving crowd. In principle, computer simulations offer means to further this understanding. Yet, unlike for many classic dynamical systems in physics, ther

Muthucumaru Maheswaran, Tianzi Yang, Salman Memon

Autonomous driving is expected to provide a range of far-reaching economic, environmental and safety benefits. In this study, we propose a fog computing based framework to assist autonomous driving. Our framework relies on overhead views from cameras and data streams from vehicle sensors to create a network of distributed digital twins, called an edge twin,

Hua Wang

Let $\mathcal L=-Δ_{\mathbb H^n}+V$ be a Schrödinger operator on the Heisenberg group $\mathbb H^n$, where $Δ_{\mathbb H^n}$ is the sublaplacian on $\mathbb H^n$ and the nonnegative potential $V$ belongs to the reverse Hölder class $RH_q$ with $q\geq Q/2$. Here $Q=2n+2$ is the homogeneous dimension of $\mathbb H^n$. Assume that $\{e^{-s\mathcal L}\}_{s>0}$ i

Peter G. Morrison

An analysis of the motion of a relativistic electron under a linear constraint in four dimensions is presented. Interesting results are given that show that the state of the electron is well defined under the formalism of time optimal quantum state control. We establish compact mechanisms for achieving time dependent unitary evolution, and present new calcul

Ryan Miller, Daniel Kennefick, Julia Kennefick, Mohamed Shameer Abdeen

The density-wave theory of spiral structure proposes that star formation occurs in or near a spiral-shaped region of higher density that rotates rigidly within the galactic disk at a fixed pattern speed. In most interpretations of this theory, newborn stars move downstream of this position as they come into view, forming a downstream spiral which is tighter,

Arjun Paul, Ronnie Sebastian

Let $k$ be an algebraically closed field of characteristic $p > 0$. Let $X$ be an irreducible smooth projective curve of genus $g$ over $k$. Fix an integer $n \geq 2$, and let $S^n(X)$ be the $n$-fold symmetric product of $X$. In this article we find the $S$-fundamental group scheme and Nori's fundamental group scheme of $S^n(X)$.

Pieto Lenarda, Alessandro Coclite, Paolo Decuzzi

Distant spreading of primary lesions is modulated by the vascular dynamics of circulating tumor cells (CTCs) and their ability to establish metastatic niches. While the mechanisms regulating CTC homing in specific tissues are yet to be elucidated, it is well documented that CTCs possess different size, biological properties and deformability. A computational

Haris Aziz, Simon Rey

We consider a multi-agent resource allocation setting in which an agent's utility may decrease or increase when an item is allocated. We take the group envy-freeness concept that is well-established in the literature and present stronger and relaxed versions that are especially suitable for the allocation of indivisible items. Of particular interest is a

Dominique Fourer, François Auger

This paper addresses the problem of efficiently jointly representing a non-stationary multicomponent signal in time and frequency. We introduce a novel enhancement of the time-reassigned synchrosqueezing method designed to compute sharpened and reversible representations of impulsive or strongly modulated signals. After establishing theoretical relations of

Bruno Gavranović

Neural networks have become an increasingly popular tool for solving many real-world problems. They are a general framework for differentiable optimization which includes many other machine learning approaches as special cases. In this thesis we build a category-theoretic formalism around a class of neural networks exemplified by CycleGAN. CycleGAN is a coll

Canyi Lu, Pan Zhou

This work studies the Tensor Robust Principal Component Analysis (TRPCA) problem, which aims to exactly recover the low-rank and sparse components from their sum. Our model is motivated by the recently proposed linear transforms based tensor-tensor product and tensor SVD. We define a new transforms depended tensor rank and the corresponding tensor nuclear no

Jake Sganga, David Eng, Chauncey Graetzel, David B. Camarillo

Lung cancer is the leading cause of cancer-related death worldwide, and early diagnosis is critical to improving patient outcomes. To diagnose cancer, a highly trained pulmonologist must navigate a flexible bronchoscope deep into the branched structure of the lung for biopsy. The biopsy fails to sample the target tissue in 26-33% of cases largely because of

Klaudius Scheufele, Shashank Subramanian, Andreas Mang, George Biros

We present a novel formulation for the calibration of a biophysical tumor growth model from a single-time snapshot, MRI scan of a glioblastoma patient. Tumor growth models are typically nonlinear parabolic partial differential equations (PDEs). Thus, we have to generate a second snapshot to be able to extract significant information from a single patient sna

Faezeh Movahedi, Robert L. Kormos, Lisa Lohmueller, Laura Seese

Left ventricular assist devices (LVADs) are an increasingly common therapy for patients with advanced heart failure. However, implantation of the LVAD increases the risk of stroke, infection, bleeding, and other serious adverse events (AEs). Most post-LVAD AEs studies have focused on individual AEs in isolation, neglecting the possible interrelation, or caus

Yuan Yang, Yang Shi, Daniela Constantinescu

A teleoperated swarm must follow the unpredictable commands of its human operator while remaining connected. When the swarm communications are limited by distance and affected by delays, both the user input and the transmission delays endanger the connectivity of the swarm. This paper presents a constructive control strategy that overcomes both threats. The

C. F. Portillo, Z. W. Woldemicheal

A system of boundary-domain integral equations is derived from the bidimensional Dirichlet problem for the diffusion equation with variable coefficient using the novel parametrix from [22] different from the one in [5,18]. Mapping properties of the surface and volume parametrix based potential-type operators are analysed. Invertibility of the single layer po

Madan Gopal Jhawar, Vipindeep Vangala, Nishchay Sharma, Ankur Hayatnagarkar

Intelligent Personal Assistants (IPAs) have become widely popular in recent times. Most of the commercial IPAs today support a wide range of skills including Alarms, Reminders, Weather Updates, Music, News, Factual Questioning-Answering, etc. The list grows every day, making it difficult to remember the command structures needed to execute various tasks. An

Ross Harper, Joshua Southern

Automatic detection of emotion has the potential to revolutionize mental health and wellbeing. Recent work has been successful in predicting affect from unimodal electrocardiogram (ECG) data. However, to be immediately relevant for real-world applications, physiology-based emotion detection must make use of ubiquitous photoplethysmogram (PPG) data collected

André Gooßen, Hrishikesh Deshpande, Tim Harder, Evan Schwab

Pneumothorax is a critical condition that requires timely communication and immediate action. In order to prevent significant morbidity or patient death, early detection is crucial. For the task of pneumothorax detection, we study the characteristics of three different deep learning techniques: (i) convolutional neural networks, (ii) multiple-instance learni

Léo Bouscarrat, Antoine Bonnefoy, Thomas Peel, Cécile Pereira

This paper introduces STRASS: Summarization by TRAnsformation Selection and Scoring. It is an extractive text summarization method which leverages the semantic information in existing sentence embedding spaces. Our method creates an extractive summary by selecting the sentences with the closest embeddings to the document embedding. The model learns a transfo

Sonja Petrović

This short piece defines a Markov basis. The aim is to introduce the statistical concept to mathematicians.

Jianwei Xu

We investigate the coherence of quantum channels and establish a resource theory for quantifying the coherence of quantum channels via Choi matrix. To this aim, we define the incoherent channels and incoherent superchannels. This theory recovers the case of quantum states when we view quantum states as a special case of quantum channels and also, this theory

Simon Guiroy, Vikas Verma, Christopher Pal

In this work we study generalization of neural networks in gradient-based meta-learning by analyzing various properties of the objective landscapes. We experimentally demonstrate that as meta-training progresses, the meta-test solutions, obtained after adapting the meta-train solution of the model, to new tasks via few steps of gradient-based fine-tuning, be

Sebastián González Hermosillo de la Maza, Pavol Hell, César Hernández Cruz, Seyyed Aliasghar Hosseini

Arboricity is a graph parameter akin to chromatic number, in that it seeks to partition the vertices into the smallest number of sparse subgraphs. Where for the chromatic number we are partitioning the vertices into independent sets, for the arboricity we want to partition the vertices into cycle-free subsets (i.e., forests). Arboricity is NP-hard in general

Katsuya Kawase, Nariya Uchida

We numerically investigate the onset of multi-chimera states in a linear array of coupled oscillators. As the phase delay $α$ is increased, they exhibit a continuous transition from the globally synchronized state to the multichimera state consisting of asynchronous and synchronous domains. Large-scale simulations show that the fraction of asynchronous sites

Oualid Benamara, Fatiha Merazka

The aim of this paper is to provide two distributed versions of the Boneh-Goh-Nissim Cryptosystem (BGNC). We give a proof of the semantic security for the first one. This guaranties that our algorithm is semantically secure in the contest of active non-adaptive adversaries. Furthermore, we prove that the second version of our distributed scheme is computatio

Christy Hazel

A surface with an involution can be viewed as a $C_2$-space where $C_2$ is the cyclic group of order two. Using the classification of $C_2$-surfaces given by Dugger, we compute the $RO(C_2)$-graded Bredon cohomology of all $C_2$-surfaces in constant $\mathbb{Z}/2$ coefficients as modules over the cohomology of a point. We show the cohomology depends only on

Daniele Facinelli, Matteo Larcher, Davide Brunelli, Daniele Fontanelli

This paper addresses the problem of target detection and localisation in a limited area using multiple coordinated agents. The swarm of Unmanned Aerial Vehicles (UAVs) determines the position of the dispersion of stack effluents to a gas plume in a certain production area as fast as possible, that makes the problem challenging to model and solve, because of

Enrique Macias, Catherine Espaillat, Mayra Osorio, Guillem Anglada

We present a detailed multi-wavelength characterization of the multi-ring disk of HD 169142. We report new ALMA observations at 3 mm and analyze them together with archival 0.89 and 1.3 mm data. Our observations resolve three out of the four rings in the disk previously seen in high-resolution ALMA data. A simple parametric model is used to estimate the radi

He Zhu, Zikang Xiong, Stephen Magill, Suresh Jagannathan

Despite the tremendous advances that have been made in the last decade on developing useful machine-learning applications, their wider adoption has been hindered by the lack of strong assurance guarantees that can be made about their behavior. In this paper, we consider how formal verification techniques developed for traditional software systems can be repu

Thomas Orvis, Mythili Surendran, Yang Liu, Austin Cunniff

The authors report in situ Auger electron spectroscopy (AES) of the surfaces of complex oxides thin films grown by pulsed laser deposition (PLD). The authors demonstrate the utility of the technique in studying chemical composition by collecting characteristic Auger spectra of elements from samples such as complex oxide thin films and single crystals as well

Israel A. Laurensi R., Luciana T. Menon, Manoel Camillo O. Penna N., Alessandro L. Koerich

This paper proposes a face anti-spoofing user-centered model (FAS-UCM). The major difficulty, in this case, is obtaining fraudulent images from all users to train the models. To overcome this problem, the proposed method is divided in three main parts: generation of new spoof images, based on style transfer and spoof image representation models; training of

Saeed Rezazadeh, Fady Alajaji, Wai-Yip Chan

The problem of lossy transmission of correlated sources over memoryless two-way channels (TWCs) is considered. The objective is to develop a robust low delay and low complexity source-channel coding scheme without using error correction. A simple full-duplex channel optimized scalar quantization (COSQ) scheme that implicitly mitigates TWC interference is des

Angelo Basile, Albert Gatt, Malvina Nissim

Inspired by Labov's seminal work on stylistic variation as a function of social stratification, we develop and compare neural models that predict a person's presumed socio-economic status, obtained through distant supervision,from their writing style on social media. The focus of our work is on identifying the most important stylistic parameters to p

L. Alonso, J. A. Méndez-Bermúdez, Ernesto Estrada

We perform an extensive numerical analysis of $β$-skeleton graphs, a particular type of proximity graphs. In a $β$-skeleton graph (BSG) two vertices are connected if a proximity rule, that depends of the parameter $β\in(0,\infty)$, is satisfied. Moreover, for $β>1$ there exist two different proximity rules, leading to lune-based and circle-based BSGs. First,

Olga K. Sil'chenko, Alexei V. Moiseev, Oleg V. Egorov

We present results of long-slit and panoramic spectroscopy of extended gaseous disks in 18 nearby S0 galaxies, mostly in groups. The gas in our S0s is found to be often accreted from outside that is implied by its decoupled kinematics: at least 5 galaxies demonstrate strongly inclined large-scale ionized-gas disks smoothly coupled with their outer HI disks,

Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke

This tutorial covers and contrasts the two main methodologies in unbiased Learning to Rank (LTR): Counterfactual LTR and Online LTR. There has long been an interest in LTR from user interactions, however, this form of implicit feedback is very biased. In recent years, unbiased LTR methods have been introduced to remove the effect of different types of bias c

Olivier Guédon, Felix Krahmer, Christian Kümmerle, Shahar Mendelson

We study the geometry of centrally-symmetric random polytopes, generated by $N$ independent copies of a random vector $X$ taking values in $\mathbb{R}^n$. We show that under minimal assumptions on $X$, for $N \gtrsim n$ and with high probability, the polytope contains a deterministic set that is naturally associated with the random vector---namely, the polar

Emmanuel Lecouturier

We define and study the space of mixed modular symbols for a given finite index subgroup $Γ$ of $SL_2(\mathbf{Z})$. This is an extension of the usual space of modular symbols, which in some cases carries more information about Eisenstein series. We make use of mixed modular symbols to construct some $1$-motives related to the generalized Jacobian of modular

Daniel J. Diroff

We generalize the result of Voronov (1988) to give an expression for the super Mumford form $μ$ on the moduli spaces of super Riemann surfaces with Ramond and Neveu-Schwarz punctures. In the Ramond case we take the number of punctures to be large compared to the genus. We consider for the case of Neveu-Schwarz punctures the super Mumford form over the compon

Muskaan, Mehak Preet Dhaliwal, Aaditeshwar Seth

Online participatory media platforms that enable one-to-many communication among users, see a significant amount of user generated content and consequently face a problem of being able to recommend a subset of this content to its users. We address the problem of recommending and ranking this content such that different viewpoints about a topic get exposure i

Panos N. Alevizos, Aggelos Bletsas

This work studies inference-based resource allocation in ultra low-power, large-scale backscatter sensor networks (BSNs). Several ultra-low cost and power sensor devices (tags) are illuminated by a carrier and reflect the measured information towards a wireless core that uses conventional Marconi radio technology. The development of multi-cell BSNs requires

Michał Przykucki, Alexander Roberts, Alex Scott

Mossel and Ross raised the question of when a random colouring of a graph can be reconstructed from local information, namely the colourings (with multiplicity) of balls of given radius. In this paper, we are concerned with random $2$-colourings of the vertices of the $n$-dimensional hypercube, or equivalently random Boolean functions. In the worst case, bal

Justin D. Harris, Bo Waggoner

Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and re-train them. We propose a framework for

Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots, Siddhartha Srinivasa

Lazy graph search algorithms are efficient at solving motion planning problems where edge evaluation is the computational bottleneck. These algorithms work by lazily computing the shortest potentially feasible path, evaluating edges along that path, and repeating until a feasible path is found. The order in which edges are selected is critical to minimizing

Wenbin Zhang, Eirini Ntoutsi

Automated data-driven decision-making systems are ubiquitous across a wide spread of online as well as offline services. These systems, depend on sophisticated learning algorithms and available data, to optimize the service function for decision support assistance. However, there is a growing concern about the accountability and fairness of the employed mode

Burçin Mutlu-Pakdil, David J. Sand, Matthew G. Walker, Nelson Caldwell

The ultra-faint dwarf galaxy Leo V has shown both photometric overdensities and kinematic members at large radii, along with a tentative kinematic gradient, suggesting that it may have undergone a close encounter with the Milky Way. We investigate these signs of disruption through a combination of i) high-precision photometry obtained with the Hubble Space T

Stephen Bottos, Balakumar Balasingam

In this paper, we propose an approach to track the progression of eye-gaze while reading a block of text on computer screen. The proposed approach will help to accurately quantify reading, e.g., identifying the lines of text that were read/skipped and estimating the time spent on each line, based on commercially available inexpensive eye-tracking devices. Th

Umang Bhaskar, Gunjan Kumar

Coverage functions are an important subclass of submodular functions, finding applications in machine learning, game theory, social networks, and facility location. We study the complexity of partial function extension to coverage functions. That is, given a partial function consisting of a family of subsets of $[m]$ and a value at each point, does there exi

Rahul Pandey, Carlos Castillo, Hemant Purohit

High-quality human annotations are necessary to create effective machine learning systems for social media. Low-quality human annotations indirectly contribute to the creation of inaccurate or biased learning systems. We show that human annotation quality is dependent on the ordering of instances shown to annotators (referred as 'annotation schedule'

Igor Slinko, Anna Vorontsova, Filipp Konokhov, Olga Barinova

Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene. We reformulate the problem of ego-motion estimation as a problem of motion estimation of a 3D-scene with respect to a static camera. The entire scene motion can be represented as a combination of motions of its

C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe

Financial transactions can be considered edges in a heterogeneous graph between entities sending money and entities receiving money. For financial institutions, such a graph is likely large (with millions or billions of edges) while also sparsely connected. It becomes challenging to apply machine learning to such large and sparse graphs. Graph representation

Ashok Jallepalli, Joshua A. Levine, Robert M. Kirby

High-order finite element methods (HO-FEM) are gaining popularity in the simulation community due to their success in solving complex flow dynamics. There is an increasing need to analyze the data produced as output by these simulations. Simultaneously, topological analysis tools are emerging as powerful methods for investigating simulation data. However, mo

Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi

The wide spread usage of automated data-driven decision support systems has raised a lot of concerns regarding accountability and fairness of the employed models in the absence of human supervision. Existing fairness-aware approaches tackle fairness as a batch learning problem and aim at learning a fair model which can then be applied to future instances of

Lukas Enderich, Fabian Timm, Lars Rosenbaum, Wolfram Burgard

Due to their high computational complexity, deep neural networks are still limited to powerful processing units. To promote a reduced model complexity by dint of low-bit fixed-point quantization, we propose a gradient-based optimization strategy to generate a symmetric mixture of Gaussian modes (SGM) where each mode belongs to a particular quantization stage

Rocio M. Casablanca, Peter Dankelmann, Wayne Goddard, Ortrud R. Oellermann

For distinct vertices $u$ and $v$ in a graph $G$, the {\em connectivity} between $u$ and $v$, denoted $κ_G(u,v)$, is the maximum number of internally disjoint $u$--$v$ paths in $G$. The {\em average connectivity} of $G$, denoted $\overlineκ(G),$ is the average of $κ_G(u,v)$ taken over all unordered pairs of distinct vertices $u,v$ of $G$. Analogously, for a

Jean-Baptiste Fouvry, Ben Bar-Or, Pierre-Henri Chavanis

The long-term dynamics of long-range interacting $N$-body systems can generically be described by the Balescu-Lenard kinetic equation. However, for ${1D}$ homogeneous systems, this collision operator exactly vanishes by symmetry. These systems undergo a kinetic blocking, and cannot relax as a whole under ${1/N}$ resonant effects. As a result, these systems c

Andrey Bokovoy, Kirill Muravyev, Konstantin Yakovlev

Vision-based depth reconstruction is a challenging problem extensively studied in computer vision but still lacking universal solution. Reconstructing depth from single image is particularly valuable to mobile robotics as it can be embedded to the modern vision-based simultaneous localization and mapping (vSLAM) methods providing them with the metric informa

Adam McKay, Michael DiSanti, Michael Kelley, Matthew Knight

Comet C/2016 R2 (PanSTARRS) has a peculiar volatile composition, with CO being the dominant volatile as opposed to H$_2$O and one of the largest N$_2$/CO ratios ever observed in a comet. Using observations obtained with the \textit{Spitzer Space Telescope}, NASA's Infrared Telescope Facility, the 3.5-meter ARC telescope at Apache Point Observatory, the D

Victor G. Turrisi da Costa, Saulo Martiello Mastelini, André C. Ponce de Leon Ferreira de Carvalho, Sylvio Barbon

As more data are produced each day, and faster, data stream mining is growing in importance, making clear the need for algorithms able to fast process these data. Data stream mining algorithms are meant to be solutions to extract knowledge online, specially tailored from continuous data problem. Many of the current algorithms for data stream mining have high

Yue Wang, Yu Zhang, Zhi Tian, Geert Leus

This paper develops efficient channel estimation techniques for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems under practical hardware limitations, including an arbitrary array geometry and a hybrid hardware structure. Taking on an angle-based approach, this work adopts a generalized array manifold separation approach via Jac

N. Degenaar, L. S. Ootes, D. Page, R. Wijnands

The structure and composition of the crust of neutron stars plays an important role in their thermal and magnetic evolution, hence in setting their observational properties. One way to study the crust properties is to measure how it cools after it has been heated during an accretion outburst in a low-mass X-ray binary (LMXB). Such studies have shown that the

Ioannis Galidakis, Ioannis Papadoperakis

In this article we use the HW maps to solve arbitrary equations f=0, by providing an effective enumeration of the roots of f, as these project on and at the branches of the HW maps. This is just an enumeration of the projection points (roots) of a pin-line on the Riemann surface of f through HW.

Xin Gui, Gregory J. Finkelstein, Keyu Chen, Tommy Yong

In-situ high pressure single crystal X-ray diffraction study reveals that the quantum material CaMn$_2$Bi$_2$ undergoes a unique plane to chain structural transition between 2 and 3 GPa, accompanied by a large volume collapse. CaMn2Bi2 displays a new structure type above 2.3 GPa, with the puckered Mn honeycomb lattice of the trigonal ambient-pressure structu

Wenchao Ge, Brian C. Sawyer, Joseph W. Britton, Kurt Jacobs

In trapped-ion quantum information processing, interactions between spins (qubits) are mediated by collective modes of motion of an ion crystal. While there are many different experimental strategies to design such interactions, they all face both technical and fundamental limitations to the achievable coherent interaction strength. In general, obtaining str

K. Bundy, K. Westfall, N. MacDonald, R. Kupke

High-multiplex and deep spectroscopic follow-up of upcoming panoramic deep-imaging surveys like LSST, Euclid, and WFIRST is a widely recognized and increasingly urgent necessity. No current or planned facility at a U.S. observatory meets the sensitivity, multiplex, and rapid-response time needed to exploit these future datasets. FOBOS, the Fiber-Optic Broadb

Shiquan Ruan

In this paper, we construct recollements and ladders for exceptional curves by using reduction/insertion functors due to $p$-cycle construction. As applications to weighted projective lines, we classify recollements for the category of coherent sheaves over a weighted projective line, and give an explicit description of ladders in two different levels: the b

Jennifer Marshall, James Bullock, Adam Burgasser, Ken Chambers

The Maunakea Spectroscopic Explorer is a next-generation massively multiplexed spectroscopic facility currently under development in Hawaii. It is completely dedicated to large-scale spectroscopic surveys and will enable transformative science. In this white paper we summarize the science case and describe the current state of the project.

Shota Komatsu, Raghu Mahajan, Shu-Heng Shao

The existence of higher-spin quantum conserved currents in two dimensions guarantees quantum integrability. We revisit the question of whether classically-conserved local higher-spin currents in two-dimensional sigma models survive quantization. We define an integrability index $\mathcal{I}(J)$ for each spin $J$, with the property that $\mathcal{I}(J)$ is a

Jonathan R. Hargis, S. Albers, D. Crnojević, D. J. Sand

A census of the satellite population around dwarf galaxy primary hosts in environments outside the Local Group is essential to understanding $Λ$CDM galaxy formation and evolution on the smallest scales. We present deep optical Hubble Space Telescope imaging of the gas-rich, faint dwarf galaxy Antlia B ($M_V = -9.4$) -- a likely satellite of NGC 3109 ($D = 1.

Molly S. Peeples, Bjorn Emonts, Mark Kyprianou, Matthew T. Penny

As observational datasets become larger and more complex, so too are the questions being asked of these data. Data simulations, i.e., synthetic data with properties (pixelization, noise, PSF, artifacts, etc.) akin to real data, are therefore increasingly required for several purposes, including: (1) testing complicated measurement methods, (2) comparing mode

W. W. R. Araujo, J. F. D. F. Araujo, C. L. P. Oliveira, G. E. S. Brito

We synthesized and characterized the colloidal suspensions of $FeO \cdot Fe_{(2-x)}Nd_{x}O_{3}$ nanoparticles with $x=0.00, 0.02, 0.04, 0.06 \text{ and }0.1.$ The effect of the $Fe^{3+}$ ion replacement by $Nd^{3+}$ on the crystal structure is in-depth studied, through X-ray diffraction (XRD) and the obtained cation distribution. The magnetic properties of t

Thomas Ding, Marc Rebholz, Lennart Aufleger, Maximilian Hartmann

We demonstrate time-resolved nonlinear extreme-ultraviolet absorption spectroscopy on multiply charged ions, here applied to the doubly charged neon ion, driven by a phase-locked sequence of two intense free-electron laser pulses. Absorption signatures of resonance lines due to 2$p$--3$d$ bound--bound transitions between the spin-orbit multiplets $^3$P$_{0,1

Rafael Brandão, Joel Carbonera, Clarisse de Souza, Juliana Ferreira

The presumed data owners' right to explanations brought about by the General Data Protection Regulation in Europe has shed light on the social challenges of explainable artificial intelligence (XAI). In this paper, we present a case study with Deep Learning (DL) experts from a research and development laboratory focused on the delivery of industrial-stre

Bok Young Kim, Yoshitomo Okawachi, Jae K. Jang, Mengjie Yu

We demonstrate an approach for automated Kerr comb generation in the normal group-velocity dispersion (GVD) regime. Using a coupled-ring geometry in silicon nitride, we precisely control the wavelength location and splitting strength of avoided mode crossings to generate low-noise frequency combs with pump-to-comb conversion efficiencies of up to 41%, which

Luca Tamanini

Aim of this short note is to show that a dimension-free Harnack inequality on an infinitesimally Hilbertian metric measure space where the heat semigroup admits an integral representation in terms of a kernel is suffcient to deduce a sharp upper Gaussian estimate for such kernel. As intermediate step, we prove the local logarithmic Sobolev inequality (known

Peyman Nasehpour

We define Dedekind semidomains as semirings in which each nonzero fractional ideal is invertible. Then we find some equivalent condition for semirings to being Dedekind. For example, we prove that a Noetherian semidomain is Dedekind if and only if it is multiplication. Then we show that a subtractive Noetherian semidomain is Dedekind if and only if it is a $

Yusan Lin, Hao Yang

Fashion is a large and fast-changing industry. Foreseeing the upcoming fashion trends is beneficial for fashion designers, consumers, and retailers. However, fashion trends are often perceived as unpredictable due to the enormous amount of factors involved into designers' subjectivity. In this paper, we propose a fashion trend prediction framework and de

Yu Chen, Guan Wang

Pose estimation is a fundamental building block for robotic applications such as autonomous vehicles, UAV, and large scale augmented reality. It is also a prohibitive factor for those applications to be in mass production, since the state-of-the-art, centimeter-level pose estimation often requires long mapping procedures and expensive localization sensors, e

Silvia Sekander, Hina Tabassum, Ekram Hossain

We develop novel statistical models of the harvested energy from renewable energy sources (such as solar and wind energy) considering harvest-store-consume (HSC) architecture. We consider three renewable energy harvesting scenarios, i.e. (i) harvesting from the solar power, (ii) harvesting from the wind power, and (iii) hybrid solar and wind power. In this c

Dmitrii Marin, Zijian He, Peter Vajda, Priyam Chatterjee

Many automated processes such as auto-piloting rely on a good semantic segmentation as a critical component. To speed up performance, it is common to downsample the input frame. However, this comes at the cost of missed small objects and reduced accuracy at semantic boundaries. To address this problem, we propose a new content-adaptive downsampling technique

Jörn Koepe

The object-capability model is a security measure that consists in encoding access rights in individual objects to restrict its interactions with other objects. Since its introduction in 2013, different approaches to object-capability have been formalized and implemented. In this paper, we present the object-capability model, and present and discuss the stat

C. A. Cremonini, P. A. Grassi

We study super-Chern-Simons theory on a generic supermanifold. After a self-contained review of integration on supermanifolds, the complexes of forms (superforms, pseudo-forms and integral forms) and the extended Cartan calculus are discussed. We then introduce Picture Changing Operators. We provide several examples of computation of PCO's acting on diff

Samuel Guerin

We give some formulas for the ZZ pairing in KO theory using a long exact sequence for bivariant K theory which links real and complex theories. This is discussed under the framework of real structures given by antilinear operators verifying some symmetries. Topological phases protected by time reversal symmetry from condensed matter physics will be discussed

G. Blaj, G. Haller, C. J. Kenney

Pixel detectors typically display pixel-to-pixel gain variation of a few percent which result in reduced spectroscopic performance. We have developed a calibration method which relies on cross-correlating histograms of many pixel pairs and obtaining large sets of relative shifts. These were subsequently used to calculate absolute pixel shifts and correspondi

Nguyen Phong Hoang, Sadie Doreen, Michalis Polychronakis

The prevalence of Internet censorship has prompted the creation of several measurement platforms for monitoring filtering activities. An important challenge faced by these platforms revolves around the trade-off between depth of measurement and breadth of coverage. In this paper, we present an opportunistic censorship measurement infrastructure built on top

Stefan Kunis, Dominik Nagel

We prove lower bounds for the smallest singular value of rectangular, multivariate Vandermonde matrices with nodes on the complex unit circle. The nodes are ``off the grid'', groups of nodes cluster, and the studied minimal singular value is bounded below by the product of inverted distances of a node to all other nodes in the specific cluster. By pr

Joseph Ribaudo, Rebecca A. Koopmann, Aileen A. O'Donoghue, Aparna Venkatesan

This White Paper highlights the role Primarily Undergraduate Institutions (PUIs) play within the astronomy profession, addressing issues related to employment, resources and support, research opportunities and productivity, and educational and societal impacts, among others. Astronomers working at PUIs are passionate about teaching and mentoring undergraduat

Ci Xue, Anthony J. Remijan, Crystal L. Brogan, Todd R. Hunter

Vibrationally excited states of detected interstellar molecules have been shown to account for a large portion of unidentified spectral lines in observed interstellar spectra toward chemically rich sources. Here, we present the first interstellar detection of the first and second vibrationally excited torsional states of acetic acid ($v_\mathrm{t} = 1, 2$) t

Abdulkarim Hariri, Meshal Alawein, Aurelien Manchon

In materials lacking inversion symmetry, the spin-orbit coupling enables the direct connection between the electron's spin and its linear momentum, a phenomenon called inverse spin galvanic effect. In magnetic materials, this effect promotes current-driven torques that can be used to control the magnetization direction electrically. In this work, we inve

Michael Cubeddu, Will Finigan, Thomas Lively, Johannes Flick

Different platforms for quantum computation are currently being developed with a steadily increasing number of physical qubits. To make today's devices practical for quantum software engineers, novel programming tools with maximal flexibility have to be developed. One example to extend the applicability of quantum computers to more complex computational

Eugenia Politou, Fran Casino, Efthimios Alepis, Constantinos Patsakis

Blockchain's evolution during the past decade is astonishing: from bitcoin to over 2.000 altcoins, and from decentralised electronic payments to transactions programmable by smart contracts and complex tokens governed by decentralised organisations. While the new generation of blockchain applications is still evolving, blockchain's technical characte

Filippo Bracci

We introduce three quantities related to orbits of non-elliptic continuous semigroups of holomorphic self-maps of the unit disc, the total speed, the orthogonal speed and the tangential speed and show how they are related and what can be inferred from those.

Pankaj Vishe

A Kloosterman refinement for function fields $K=\mathbb{F}_q(t)$ is developed and used to establish the quantitative arithmetic of the set of rational points on a smooth complete intersection of two quadrics $X\subset \mathbb{P}^{n-1}_{K}$ , under the assumption that $q$ is odd and $n\geq 9$.

Hui Li, Xiaoyu Wang, Zhun Lu

We investigate the single transverse-spin asymmetry with a $\sin (2ϕ-ϕ_S)$ modulation in the pion-induced Drell-Yan process within the theoretical framework of the transverse momentum dependent factorization. The asymmetry is contributed by the convolution of the Boer-Mulders function and the transversity. We adopt the model results for the distributions of

Bo Chen, Chong Song

We study isolated singularities of two dimensional Yang-Mills-Higgs fields defined on a fiber bundle, where the fiber space is a compact Riemannian manifold and the structure group is a compact connected Lie group. In general the singularity can not be removed due to possibly non-vanishing limit holonomy around the singular points. We establish a sharp asymp

Sven Jacobsson, Lise Aabel, Mikael Coldrey, Ibrahim Can Sezgin

Advances in analog-to-digital converter (ADC) technology have opened up the possibility to directly digitize wideband radio frequency (RF) signals, avoiding the need for analog down-conversion. In this work, we consider an orthogonal frequency-division multiplexing (OFDM)-based massive multi-user (MU) multiple-input multiple-output (MIMO) uplink system that

Hyun Ho Kim, Adam W. Tsen

Research in two-dimensional (2D) materials has experienced rapid growth in the past few years. In particular, various layered compounds exhibiting quantum phenomena, such as superconductivity and magnetism, have been isolated in atomically thin form, often in spite of their chemical instability. The nature of the 2D phases can be different than their bulk co