October 2020 arXiv papers — page 112

Jingkang Yang, Weirong Chen, Litong Feng, Xiaopeng Yan

Webly supervised learning becomes attractive recently for its efficiency in data expansion without expensive human labeling. However, adopting search queries or hashtags as web labels of images for training brings massive noise that degrades the performance of DNNs. Especially, due to the semantic confusion of query words, the images retrieved by one query m

Atchade Parfait Adelomou, Elisabet Golobardes Ribe, Xavier Vilasis Cardona

The social worker scheduling problem is a class of combinatorial optimization problems that combines scheduling with routing issues. These types of problems with classical computing can only be solved, in the best of cases, in an approximate way and significantly when the input data does not grow considerably. Today, the focus on the quantum computer should

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Optimal Transport (OT) distances such as Wasserstein have been used in several areas such as GANs and domain adaptation. OT, however, is very sensitive to outliers (samples with large noise) in the data since in its objective function, every sample, including outliers, is weighed similarly due to the marginal constraints. To remedy this issue, robust formula

Yongjung Kim, Myungshin Im, Yiseul Jeon, Minjin Kim

Faint $z\sim5$ quasars with $M_{1450}\sim-23$ mag are known to be the potentially important contributors to the ultraviolet ionizing background in the post-reionization era. However, their number density has not been well determined, making it difficult to assess their role in the early ionization of the intergalactic medium (IGM). In this work, we present t

Mark Fonaryov, Michael Lindenbaum

In contrast to human vision, common recognition algorithms often fail on partially occluded images. We propose characterizing, empirically, the algorithmic limits by finding a minimal recognizable patch (MRP) that is by itself sufficient to recognize the image. A specialized deep network allows us to find the most informative patches of a given size, and ser

Felix Ospald, Kai Bergermann, Roland Herzog

Fiber optical strain sensors are used to measure the strain at a particular sensor position inside the fiber. In order to deduce the strain in the surrounding matrix material, one can employ the strain transfer principle. Its application is based on the assumption that the presence of the fiber does not impede the deformation of the matrix material in fiber

Chuanbo Wang, DM Anisuzzaman, Victor Williamson, Mrinal Kanti Dhar

Acute and chronic wounds have varying etiologies and are an economic burden to healthcare systems around the world. The advanced wound care market is expected to exceed $22 billion by 2024. Wound care professionals rely heavily on images and image documentation for proper diagnosis and treatment. Unfortunately lack of expertise can lead to improper diagnosis

Roberto Mossa, Michela Zedda

This paper studies the geometry of Cartan-Hartogs domains from the symplectic point of view. Inspired by duality between compact and noncompact Hermitian symmetric spaces, we construct a dual counterpart of Cartan-Hartogs domains and give explicit expression of global Darboux coordinates for both Cartan-Hartogs and their dual. Further, we compute their sympl

Joshua Lockhart, Samuel Assefa, Ayham Alajdad, Andrew Alexander

Supervised learning classifiers inevitably make mistakes in production, perhaps mis-labeling an email, or flagging an otherwise routine transaction as fraudulent. It is vital that the end users of such a system are provided with a means of relabeling data points that they deem to have been mislabeled. The classifier can then be retrained on the relabeled dat

Natasha Jaques, Judy Hanwen Shen, Asma Ghandeharioun, Craig Ferguson

How can we train a dialog model to produce better conversations by learning from human feedback, without the risk of humans teaching it harmful chat behaviors? We start by hosting models online, and gather human feedback from real-time, open-ended conversations, which we then use to train and improve the models using offline reinforcement learning (RL). We i

Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges, Patrick Cardinal

In this paper we propose a conditioning trick, called difference departure from normality, applied on the generator network in response to instability issues during GAN training. We force the generator to get closer to the departure from normality function of real samples computed in the spectral domain of Schur decomposition. This binding makes the generato

Georg Wolschin

The spectroscopic properties of heavy quarkonia are substantially different in the quark-gluon plasma (QGP) that is created in relativistic heavy-ion collisions as compared to the vacuum situation that can be tested in pp collisions at the same center-of-mass energy. In this article, a series of recent works about the dissociation of the Y(nS) and chi_b(nP)

Shirshendu Ganguly, Alan Hammond

The energy and geometry of maximizing paths in integrable last passage percolation models are governed by the characteristic KPZ scaling exponents of one-third and two-thirds. When represented in scaled coordinates that respect these exponents, this random field of paths may be viewed as a complex energy landscape. We investigate the structure of valleys and

Vinay Varma K

The representational capacity of modern neural network architectures has made them a default choice in various applications with high dimensional feature sets. But these high dimensional and potentially noisy features combined with the black box models like neural networks negatively affect the interpretability, generalizability, and the training time of the

T. Kamiński, W. Steffen, V. Bujarrabal, R. Tylenda

CK Vul is the remnant of an energetic eruption known as Nova 1670 that is thought to be caused by a stellar merger. The remnant is composed of (1) a large hourglass nebula of recombining gas (of 71\arcsec size), very similar to some classical planetary and pre-planetary nebulae (PPNe), and (2) of a much smaller and cooler inner remnant prominent in millimete

Aleksander Ćwiszewski, Władysław Klinikowski

We derive an estimate for the minimal period of autonomous strongly damped hyperbolic problems. Our result corresponds to the works by Yorke, Busenberg et al. for ordinary differential equations as well as Robinson and Vidal-Lopez for parabolic problems. A general approach is developed for treating both hyperbolic and parabolic problems. An example of applic

Tesla Jeltema, Stefano Profumo, Jaryd F. Ulbricht

New matter fields charged under the strong nuclear force would have dramatic phenomenological implications. Here, we systematically explore how these new states, which we postulate belong to some representation of SU(3) of quantum chromo-dynamics, could interact with Standard Model fields: We analyze all lowest-dimensional "portal" operators for any

Zahra Heydarbeygi, Maryam Amyari, Mahnaz Khanehgir

In this paper, we give some refinements for the second inequality in $\frac{1}{2}\|A\| \leq w(A) \leq \|A\|$, where $A\in B(H)$. In particular, if $A$ is hyponormal by refining the Young inequality with the Kantorovich constant $K(\cdot, \cdot)$, we show that $w(A)\leq \dfrac{1}{\displaystyle {2\inf_{\| x \|=1}}ζ(x)}\| |A|+|A^{*}|\|\leq \dfrac{1}{2}\| |A|+|A

H. Beuther, J. D. Soler, H. Linz, Th. Henning

The formation of hot stars out of the cold interstellar medium lies at the heart of astrophysical research. Understanding the importance of magnetic fields during star formation remains a major challenge. With the advent of the Atacama Large Millimeter Array, the potential to study magnetic fields by polarization observations has tremendously progressed. How

Steven Weinberg

In spacetimes of any dimensionality, the massless particle states that can be created and destroyed by a field in a given representation of the Lorentz group are severely constrained by the condition that the invariant Abelian subgroup of the little group must leave these states invariant. A number of examples are given of the massless one-particle states th

Shuichi Hirahara, Nobutaka Shimizu

In this paper, we seek a natural problem and a natural distribution of instances such that any $O(n^{c-ε})$-time algorithm fails to solve most instances drawn from the distribution, while the problem admits an $n^{c+o(1)}$-time algorithm that correctly solves all instances. Specifically, we consider the $K_{a,b}$ counting problem in a random bipartite graph,

Pushpak Jagtap, George J. Pappas, Majid Zamani

This paper focuses on the controller synthesis for unknown, nonlinear systems while ensuring safety constraints. Our approach consists of two steps, a learning step that uses Gaussian processes and a controller synthesis step that is based on control barrier functions. In the learning step, we use a data-driven approach utilizing Gaussian processes to learn

Jubee Sohn, Margaret J. Geller, Ho Seong Hwang, Daniel G. Fabricant

HectoMAP is a dense, red-selected redshift survey to a limiting $r = 21.3$ covering 55 square degrees in a contiguous 1.5$^\circ$ strip across the northern sky. This region is also covered by the Subaru/Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) photometric survey enabling a range of applications that combine a dense foreground redshift survey wi

Laura Ares, Alfredo Luis

Violations of Bell inequalities in classical optics have been demonstrated in terms of field mean intensities and correlations, however, the quantum meaning of violations point to statistics and probabilities. We present a violation of Bell inequalities for classical fields in terms of probabilities, where we convert classical-field intensities into probabil

Tsai-Shien Chen, Man-Yu Lee, Chih-Ting Liu, Shao-Yi Chien

Vehicle re-identification (re-ID) matches images of the same vehicle across different cameras. It is fundamentally challenging because the dramatically different appearance caused by different viewpoints would make the framework fail to match two vehicles of the same identity. Most existing works solved the problem by extracting viewpoint-aware feature via s

Nader Sehatbakhsh, Ellie Daw, Onur Savas, Amin Hassanzadeh

As machine learning becomes a more mainstream technology, the objective for governments and public sectors is to harness the power of machine learning to advance their mission by revolutionizing public services. Motivational government use cases require special considerations for implementation given the significance of the services they provide. Not only wi

Filippo Pantellini

Uranus is the only planet in the Solar System whose rotation axis and orbital plane are nearly parallel to each other. Uranus is also the planet with the largest angle between the rotation axis and the direction of its magnetic dipole (roughly $59^\circ$). Consequently, the shape and structure of its magnetospheric tail is very different to those of all othe

Rinat Kashaev

Based on continued fractions with subtractions, we identify the set of real numbers with the set of infinite integer sequences with all terms but the first one greater or equal to two. Each such sequence produces in a canonical way a unique strictly decreasing Cauchy sequence of rationals which converges to the corresponding real number. The correspondence i

Virginia Carnevali, Ilaria Siloi, Rosa Di Felice, Marco Fornari

Quantum annealers have grown in complexity to the point that quantum computations involving few thousands of qubits are now possible. In this paper, \textcolor{black}{with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, t

Eric Braaten, Li-Ping He, Jun Jiang

XEFT is a low-energy effective field theory for charm mesons and pions that provides a systematically improvable description of the $X(3872)$ resonance. To simplify calculations beyond leading order, we introduce a new formulation of XEFT with a dynamical field for a pair of charm mesons in the resonant channel. We simplify the renormalization of XEFT by int

Abhisekh Sankaran

We consider classes of arbitrary (finite or infinite) graphs of bounded shrub-depth, specifically the class $\mathrm{TM}_{r, p}(d)$ of $p$-labeled arbitrary graphs whose underlying unlabeled graphs have tree models of height $d$ and $r$ labels. We show that this class satisfies an extension of the classical Löwenheim-Skolem property into the finite and for $

Marco Avesani, Hamid Tebyanian, Paolo Villoresi, Giuseppe Vallone

Randomness is a central feature of quantum mechanics and an invaluable resource for both classical and quantum technologies. Commonly, in Device-Independent and Semi-Device-Independent scenarios, randomness is certified using projective measurements and the amount of certified randomness is bounded by the dimension of the measured quantum system. In this wor

S. Bagnulo, J. D. Landstreet

The sample of white dwarfs included in the local 20 pc volume documents, fairly accurately, the total production of white dwarfs over roughly 10 Gyr of stellar evolution in this part of the Milky Way Galaxy. In this sample, we have been systematically searching for magnetic white dwarfs. Here we report the discovery of six new magnetic white dwarfs, with a f

John W. Villanova, Salvador Barraza-Lopez

SnSe monolayers experience a temperature induced two-dimensional Pnm2$_1 \to$ P4/nmm structural transformation precipitated by the softening of vibrational modes. The standard theoretical treatment of thermoelectricity---which relies on a zero temperature phonon dispersion and on a zero temperature electronic structure---is incapable of describing thermoelec

J. Speicher, D. R. Ballantyne, J. Malzac

Understanding the persistent emission is crucial for studying type I X-ray bursts, which provide insight into neutron star properties. Although accretion disc coronae appear to be common in many accreting systems, their fundamental properties remain insufficiently understood. Recent work suggests that Type I X-ray bursts from accreting neutron stars provide

Qi Wang, Detlef Lohse, Olga Shishkina

We offer a unifying theory for turbulent purely internally heated convection, generalizing the unifying theories of Grossmann and Lohse (2000, 2001) for Rayleigh--Bénard turbulence and of Shishkina, Grossmann and Lohse (2016) for turbulent horizontal convection, which are both based on the splitting of the kinetic and thermal dissipation rates in respective

Minh N. Vu, My T. Thai

In Graph Neural Networks (GNNs), the graph structure is incorporated into the learning of node representations. This complex structure makes explaining GNNs' predictions become much more challenging. In this paper, we propose PGM-Explainer, a Probabilistic Graphical Model (PGM) model-agnostic explainer for GNNs. Given a prediction to be explained, PGM-Ex

Daniela De Silva, Giorgio Tortone

We consider the vectorial analogue of the thin free boundary problem introduced in \cite{CRS} as a realization of a nonlocal version of the classical Bernoulli problem. We study optimal regularity, nondegeneracy, and density properties of local minimizers. Via a blow-up analysis based on a Weiss type monotonicity formula, we show that the free boundary is th

J. J. Velazquez-Garcia, J. Wong, K. Basuroy, D. Storozhuk

Investigating metal organic systems with time-resolved photocrystallography poses a unique challenge while interpreting the time dependent photodifference maps. In these difference Fourier maps, the signals correspond to the movement of heavy metal atoms always overpower the signals from much lighter atoms attached to them. For a systematic assessment of the

Afshin Oroojlooy, Mohammadreza Nazari, Davood Hajinezhad, Jorge Silva

We propose AttendLight, an end-to-end Reinforcement Learning (RL) algorithm for the problem of traffic signal control. Previous approaches for this problem have the shortcoming that they require training for each new intersection with a different structure or traffic flow distribution. AttendLight solves this issue by training a single, universal model for i

Ulrich Doll, Christophe Barro, Michele Todino, Konstantinos Boulouchos

Mixing, ignition and combustion behavior in a rapid compression and expansion machine operated under Premixed Charge Compression Ignition (PCCI) relevant conditions are investigated by combined passive optical and laser-optical high-speed diagnostics. The PCCI concept is realized using a split injection schedule consisting of a long base load injection and t

Nikolaos Manginas, Ilias Chalkidis, Prodromos Malakasiotis

Although BERT is widely used by the NLP community, little is known about its inner workings. Several attempts have been made to shed light on certain aspects of BERT, often with contradicting conclusions. A much raised concern focuses on BERT's over-parameterization and under-utilization issues. To this end, we propose o novel approach to fine-tune BERT

Guangming Wang, Xinrui Wu, Zhe Liu, Hesheng Wang

Scene flow represents the 3D motion of every point in the dynamic environments. Like the optical flow that represents the motion of pixels in 2D images, 3D motion representation of scene flow benefits many applications, such as autonomous driving and service robot. This paper studies the problem of scene flow estimation from two consecutive 3D point clouds.

Aaron S. Eisman, Nishant R. Shah, Carsten Eickhoff, George Zerveas

Anginal symptoms can connote increased cardiac risk and a need for change in cardiovascular management. This study evaluated the potential to extract these symptoms from physician notes using the Bidirectional Encoder from Transformers language model fine-tuned on a domain-specific corpus. The history of present illness section of 459 expert annotated primar

Alberto Marchisio, Vojtech Mrazek, Muhammad Abdullah Hanif, Muhammad Shafique

Deep Neural Networks (DNNs) have been established as the state-of-the-art algorithm for advanced machine learning applications. Recently proposed by the Google Brain's team, the Capsule Networks (CapsNets) have improved the generalization ability, as compared to DNNs, due to their multi-dimensional capsules and preserving the spatial relationship between

Ton Chanh Le, Timos Antonopoulos, Parisa Fathololumi, Eric Koskinen

There is growing interest in termination reasoning for non-linear programs and, meanwhile, recent dynamic strategies have shown they are able to infer invariants for such challenging programs. These advances led us to hypothesize that perhaps such dynamic strategies for non-linear invariants could be adapted to learn recurrent sets (for non-termination) and/

Firdous A. Shah, Waseem Z. Lone

The linear canonical transform (LCT) has attained respectable status within a short span and is being broadly employed across several disciplines of science and engineering including signal processing, optical and radar systems, electrical and communication systems, quantum physics etc, mainly due to the extra degrees of freedom and simple geometrical manife

Federico Amato, Fabian Guignard, Philippe Jacquet, Mikhail Kanevski

The presence of irrelevant features in the input dataset tends to reduce the interpretability and predictive quality of machine learning models. Therefore, the development of feature selection methods to recognize irrelevant features is a crucial topic in machine learning. Here we show how the General Regression Neural Network used with an anisotropic Gaussi

Khaldoon Ghanem, Kai Guther, Ali Alavi

In a recent paper, we proposed the adaptive shift method for correcting the undersampling bias of the initiator-FCIQMC. The method allows faster convergence with the number of walkers to the FCI limit than the normal initiator method, particularly for large systems. In its application to strongly correlated molecules, however, the method is prone to overshoo

Georgii Veprev

In this work, we study the slow entropy type invariant of a dynamical system proposed by A. M. Vershik. We provide an explicit construction of a system whose class of scaling entropy sequences is empty. For this unstable case, we introduce an upgraded notion of the invariant, generalize subadditivity results, and provide a complete series of examples.

Guto Leoni Santos, Pierangelo Rosati, Theo Lynn, Judith Kelner

Mobile network traffic prediction is an important input in to network capacity planning and optimization. Existing approaches may lack the speed and computational complexity to account for bursting, non-linear patterns or other important correlations in time series mobile network data. We compare the performance of two deep learning architectures - Long Shor

Sopan Khosla, Carolyn Rose

Coreference resolution (CR) is an essential part of discourse analysis. Most recently, neural approaches have been proposed to improve over SOTA models from earlier paradigms. So far none of the published neural models leverage external semantic knowledge such as type information. This paper offers the first such model and evaluation, demonstrating modest ga

Xiaolei Liu, Zhenhai Yu, Qifeng Liang, Chunyin Zhou

Orthorhombic (space group: Pnma) Nb2P5 is a high-pressure phase that is quenchable to ambient pressure, which could viewed as the zigzag infinite P chain-inserted NbP2. We report herein the high-pressure crystal growth of Nb2P5 and the discovery of its superconducting transition at Tc ~ 2.6 K. The electrical resistivity, magnetization, and specific heat capa

Marco Di Giovanni, Marco Brambilla

Large pre-trained language representation models (LMs) have recently collected a huge number of successes in many NLP tasks. In 2018 BERT, and later its successors (e.g. RoBERTa), obtained state-of-the-art results in classical benchmark tasks, such as GLUE benchmark. After that, works about adversarial attacks have been published to test their generalization

Petr A. Golovach, Paloma T. Lima, Charis Papadopoulos

Given a graph class $\mathcal{H}$, the task of the $\mathcal{H}$-Square Root problem is to decide, whether an input graph $G$ has a square root $H$ from $\mathcal{H}$. We are interested in the parameterized complexity of the problem for classes $\mathcal{H}$ that are composed by the graphs at vertex deletion distance at most $k$ from graphs of maximum degree

Rajat Patel, Francis Ferraro

We demonstrate the complementary natures of neural knowledge graph embedding, fine-grain entity type prediction, and neural language modeling. We show that a language model-inspired knowledge graph embedding approach yields both improved knowledge graph embeddings and fine-grain entity type representations. Our work also shows that jointly modeling both stru

Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, Goran Glavaš

The success of large pretrained language models (LMs) such as BERT and RoBERTa has sparked interest in probing their representations, in order to unveil what types of knowledge they implicitly capture. While prior research focused on morphosyntactic, semantic, and world knowledge, it remains unclear to which extent LMs also derive lexical type-level knowledg

Mikhail Khovanov

The paper explores the relation between noncommutative power series and topological theories of one-dimensional cobordisms decorated by labelled zero-dimensional submanifolds. These topological theories give rise to several types of tensor envelopes of noncommutative recognizable power series, including the categories built from the syntactic algebra and syn

Yuya Higashikawa, Naoki Katoh, Junichi Teruyama, Koji Watase

We address the facility location problems on dynamic flow path networks. A dynamic flow path network consists of an undirected path with positive edge lengths, positive edge capacities, and positive vertex weights. A path can be considered as a road, an edge length as the distance along the road and a vertex weight as the number of people at the site. An edg

Agnid Banerjee, Prashanta Garain, Juha Kinnunen

We establish a local boundedness estimate for weak subsolutions to a doubly nonlinear parabolic fractional $p$-Laplace equation. Our argument relies on energy estimates and a parabolic nonlocal version of De Giorgi's method. Furthermore, by means of a new algebraic inequality, we show that positive weak supersolutions satisfy a reverse Hölder inequality.

Ethan Wilcox, Peng Qian, Richard Futrell, Ryosuke Kohita

Humans can learn structural properties about a word from minimal experience, and deploy their learned syntactic representations uniformly in different grammatical contexts. We assess the ability of modern neural language models to reproduce this behavior in English and evaluate the effect of structural supervision on learning outcomes. First, we assess few-s

Chen He, Luana Micallef, Liye He, Gopal Peddinti

Understanding the quality of insight has become increasingly important with the trend of allowing users to post comments during visual exploration, yet approaches for qualifying insight are rare. This paper presents a case study to investigate the possibility of characterizing the quality of insight via the interactions performed. To do this, we devised the

Guylaine Poulin-Vittrant, Kevin Nadaud, Chandrakanth Reddy Chandraiahgari, Daniel Alquier

Piezoelectric capacitive NanoGenerators (NG) based on vertically grown crystalline zinc oxide nanowires (ZnO-NWs) have been fabricated using a low-cost and scalable hydrothermal method on gold-coated silicon substrates, which served as both a seed layer and a conductive bottom electrode. Morphological and structural characterizations demonstrate that the obt

Bingkai Sheng, Yuanyuan Wang, Xinyang Wang, Lang Yu

In this work, we investigate not only the pole masses but also the screening masses of neutral pions at finite temperature and magnetic field by utilizing the random phase approximation (RPA) approach in the framework of the two-flavor Nambu--Jona-Lasinio (NJL) model. And two equivalent formalisms in the presence of a magnetic field, i.e. the Landau level re

J. Chappell, E. Adli, R. Agnello, M. Aladi

Plasma wakefield dynamics over timescales up to 800 ps, approximately 100 plasma periods, are studied experimentally at the Advanced Wakefield Experiment (AWAKE). The development of the longitudinal wakefield amplitude driven by a self-modulated proton bunch is measured using the external injection of witness electrons that sample the fields. In simulation,

Monakhov V. S., Sokhor I. L

We conclude from the results of Hanguang Meng and Xiuyun Guo some corollaries about the existence of strictly 2-maximal subgroups in groups. We give examples of groups that illustrate properties of strictly 2-maximal subgroups.

Roland Pongou

Sex differences in early age mortality have been explained in prior literature by differences in biological make-up and gender discrimination in the allocation of household resources. Studies estimating the effects of these factors have generally assumed that offspring sex ratio is random, which is implausible in view of recent evidence that the sex of a chi

Ofir Arviv, Ruixiang Cui, Daniel Hershcovich

This paper describes the HUJI-KU system submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2020 Conference for Computational Language Learning (CoNLL), employing TUPA and the HIT-SCIR parser, which were, respectively, the baseline system and winning system in the 2019 MRP shared task. Both are transition-based parser

Eviatar B. Procaccia, Itamar Procaccia

Diffusion Limited Aggregation (DLA) has served for forty years as a paradigmatic example for the creation of fractal growth patterns. In spite of thousands of references no exact result for the fractal dimension $D$ of DLA is known. In this Letter we announce an exact result for off-lattice DLA grown on a line, $D=3/2$. The result relies on representing DLA

Antonio Cerone, Markus Roggenbach, James Davenport, Casey Denner

This white paper argues that formal methods need to be better rooted in higher education curricula for computer science and software engineering programmes of study. To this end, it advocates (i) improved teaching of formal methods; (ii) systematic highlighting of formal methods within existing, `classical' computer science courses; and (iii) the inclusi

Jie-Shuang Wang, Zong-Kai Peng, Jin-Hang Zou, Bin-Bin Zhang

We perform a stringent search for precursor emission of short gamma-ray bursts (SGRBs) from the Fermi/GBM data and find 16 precursor events with $\gtrsim4.5σ$ significance. We find that the durations of the main SGRB emission ($T_{\rm GRB}$) and the precursor emission ($T_{\rm pre}$), as well as the waiting time ($T_{\rm wt}$) in between, are roughly compara

Simon Fichtner, Georg Schönweger, Tom-Niklas Kreutzer, Fabian Lofink

The discovery of ferroelectricity in AlScN allowed the first clear observation of the effect in the wurtzite crystal structure, resulting in a material with a previously unprecedented combination of very large coercive fields (2-5 MV/cm) and remnant polarizations (70-110 $μ$C/cm$^2$). We obtained initial insight into the switching dynamics of AlScN, which su

Jui-Hui Chung, Ying-Jer Kao

The key idea behind the renormalization group (RG) transformation is that properties of physical systems with very different microscopic makeups can be characterized by a few universal parameters. However, finding the optimal RG transformation remains difficult due to the many possible choices of the weight factors in the RG procedure. Here we show, by ident

Jianbo Liu, Pengjie Wang, Yinren Shou, Zhusong Mei

We report the experimental results of simultaneous measurements on the electron and X-ray spectra from near-critical-density (NCD) double-layer targets irradiated by relativistic femtosecond pulses at the intensity of 5E19 W/cm^2. The dependence of the electron and X-ray spectra on the density and thickness of the NCD layer was studied. For the optimal targe

Cesare Certosini, Renzo Capitani, Claudio Annicchiarico

Motion Sickness (MS) is an issue of most transportation systems. Several countermeasures for such problem in cars are proposed in the literature, but most of them are qualitative, behavioural or involving complex chassis systems. With the growing interest in self-employed vehicles, the issue of MS may be so important that it undermines their benefits in term

Kalpesh Krishna, John Wieting, Mohit Iyyer

Modern NLP defines the task of style transfer as modifying the style of a given sentence without appreciably changing its semantics, which implies that the outputs of style transfer systems should be paraphrases of their inputs. However, many existing systems purportedly designed for style transfer inherently warp the input's meaning through attribute tr

Philipp Darius, Fabian Stephany

Twitter influences political debates. Phenomena like fake news and hate speech show that political discourse on micro-blogging can become strongly polarised by algorithmic enforcement of selective perception. Some political actors actively employ strategies to facilitate polarisation on Twitter, as past contributions show, via strategies of 'hashjacking&

Jack Wilkinson, Jonathan Huang, Antonia Marsden, Michael Harhay

Randomised controlled trials in reproductive medicine are often subject to outcome truncation, where study outcomes are only defined in a subset of participants. Examples include birthweight (measurable only in the subgroup of participants who give birth) and miscarriage (which can only occur in participants who become pregnant). These are typically analysed

Jie Xu, Jun Xi, Hua Dong, Namyoung Ahn

Interfaces between the perovskite active layer and the charge-transport layers (CTLs) play a critical role in both efficiency and stability of halide-perovskite photovoltaics. One of the major concerns is that surface defects of perovskite could cause detrimental nonradiative recombination and material degradation. In this work, we addressed this challenging

Bernadette Charron-Bost, Patrick Lambein-Monette

When networked systems of autonomous agents carry out complex tasks, the control and coordination sought after generally depend on a few fundamental control primitives. Chief among these primitives is consensus, where agents are to converge to a common estimate within the range of initial values, which becomes average consensus when the joint limit should be

Mohammad Sababheh, Hamid Reza Moradi

In this article, we further explore convex functions by revealing new bounds, resulting from stronger convexity behavior. In particular, we define the so called radical convex functions and study their properties. We will see that such convex functions are bounded above by new curves, rather than straight lines. Applications including discrete and continuous

Ethan Levien, Jiseon Min, Jane Kondev, Ariel Amir

The observation that phenotypic variability is ubiquitous in isogenic populations has led to a multitude of experimental and theoretical studies seeking to probe the causes and consequences of this variability. Whether it be in the context of antibiotic treatments or exponential growth in constant environments, non-genetic variability has shown to have signi

Francois Meyer, Martha Lewis

Words can have multiple senses. Compositional distributional models of meaning have been argued to deal well with finer shades of meaning variation known as polysemy, but are not so well equipped to handle word senses that are etymologically unrelated, or homonymy. Moving from vectors to density matrices allows us to encode a probability distribution over di

D. Munshi, T. Namikawa, J. D. McEwen, T. D. Kitching

We study the morphology of convergence maps by perturbatively reconstructing their Minkowski Functionals (MFs). We present a systematics study using a set of three generalised skew-spectra as a function of source redshift and smoothing angular scale. Using an approach based on pseudo-$S_{\ell}$s (PSL) we show how these spectra will allow reconstruction of MF

Guillermo Alesandroni

Generalizing the concept of dense hypergraph, we say that a hypergraph is weakly dense, if no k in the half-open interval [2,sqrt(n)) is the degree of more than k^2 vertices. In our main result, we prove the famous Erdos-Faber-Lovasz conjecture when the hypergraph is weakly dense.

Abhishek Gautam, Alper Celik, Mahdi Azarpeyvand

A numerical and experimental study on double degree of freedom Helmholtz resonator based acoustic liners is performed in this paper, with the motivation to improve the understanding of their sound attenuation mechanism. A single degree of freedom liner is designed and manufactured, as baseline, to compare with the double degree of freedom acoustic liners. Th

Prithvi Suresh, Naveen Narayanan, Chakilam Vijay Pranav, Vineeth Vijayaraghavan

Continuous monitoring of cardiac activity is paramount to understanding the functioning of the heart in addition to identifying precursors to conditions such as Atrial Fibrillation. Through continuous cardiac monitoring, early indications of any potential disorder can be detected before the actual event, allowing timely preventive measures to be taken. Elect

Shreenanda Ghosh, Felix Brückner, Artem Nikitin, Vadim Grinenko

We present a piezoelectric-driven uniaxial pressure cell that is optimized for muon spin relaxation and neutron scattering experiments, and that is operable over a wide temperature range including cryogenic temperatures. To accommodate the large samples required for these measurement techniques, the cell is designed to generate forces up to 1000 N, and to mi

Yaroslav Alekseev

In this paper we study an extension of the Polynomial Calculus proof system where we can introduce new variables and take a square root. We prove that an instance of the subset-sum principle, the binary value principle, requires refutations of exponential bit size over rationals in this system. Part and Tzameret proved an exponential lower bound on the size

Luis Puche Rondon, Leonardo Babun, Ahmet Aris, Kemal Akkaya

The rise of IoT devices has led to the proliferation of smart buildings, offices, and homes worldwide. Although commodity IoT devices are employed by ordinary end-users, complex environments such as smart buildings, smart offices, conference rooms, or hospitality require customized and highly reliable solutions. Those systems called Enterprise Internet of Th

Yuyuan Yu, Guoxu Zhou, Ning Zheng, Shengli Xie

Tensor ring (TR) decomposition is a powerful tool for exploiting the low-rank nature of multiway data and has demonstrated great potential in a variety of important applications. In this paper, nonnegative tensor ring (NTR) decomposition and graph regularized NTR (GNTR) decomposition are proposed, where the former equips TR decomposition with local feature e

Debora Princepe, Marcus A. M. de Aguiar

Mitochondrial genetic material is widely used for phylogenetic reconstruction and as a barcode for species identification. Here we study how mito-nuclear interactions affect the accuracy of species identification by mtDNA, as well as the speciation process itself. We simulate the evolution of a population of individuals who carry a recombining nuclear genome

Eloïse Berson, Catherine Soladié, Nicolas Stoiber

For the last decades, the concern of producing convincing facial animation has garnered great interest, that has only been accelerating with the recent explosion of 3D content in both entertainment and professional activities. The use of motion capture and retargeting has arguably become the dominant solution to address this demand. Yet, despite high level o

Francesco Ragusa, Antonino Furnari, Salvatore Livatino, Giovanni Maria Farinella

Wearable cameras allow to collect images and videos of humans interacting with the world. While human-object interactions have been thoroughly investigated in third person vision, the problem has been understudied in egocentric settings and in industrial scenarios. To fill this gap, we introduce MECCANO, the first dataset of egocentric videos to study human-

Tatyana Vasilchikova, Vladimir Nalbandyan, Igor Shukaev, Hyun-Joo Koo

An orthorhombic compound, NaMnSbO4, represents a square net of magnetic Mn2+ ions residing in vertex-shared oxygen octahedra. Its static and dynamic magnetic properties were studied using magnetic susceptibility, specific heat, magnetization, electron spin resonance (ESR), nuclear magnetic resonance (NMR) and density functional calculations. Thermodynamic da

Jan-Christoph Schlage-Puchta

We give a new proof of a theorem by P. Mihailescu which states that the equation $x^p-y^q=1$ is unsolvable with $x, y$ integral and $p, q$ odd primes, unless the congruences $p^q \equiv p\pmod{q^2}$ and $q^p\equiv q \pmod{p^2}$ hold.

F. A. Driessen, N. D. Kee, J. O. Sundqvist, S. P. Owocki

Line-driven stellar winds from massive (OB) stars are subject to a strong line-deshadowing instability. Recently, spectropolarimetric surveys have collected ample evidence that a subset of Galactic massive stars hosts strong surface magnetic fields. We investigate here the propagation and stability of magneto-radiative waves in such a magnetised, line-driven

Inbar Oren, Jonathan Herzig, Nitish Gupta, Matt Gardner

Generalization of models to out-of-distribution (OOD) data has captured tremendous attention recently. Specifically, compositional generalization, i.e., whether a model generalizes to new structures built of components observed during training, has sparked substantial interest. In this work, we investigate compositional generalization in semantic parsing, a

Giulia Bernardini, Paola Bonizzoni, Paweł Gawrychowski

Reconstructing the evolutionary history of a set of species is a central task in computational biology. In real data, it is often the case that some information is missing: the Incomplete Directed Perfect Phylogeny (IDPP) problem asks, given a collection of species described by a set of binary characters with some unknown states, to complete the missing stat

Maria Axenovich, António Girão, Richard Snyder, Lea Weber

Kostochka and Thomason independently showed that any graph with average degree $Ω(r\sqrt{\log r})$ contains a $K_r$ minor. In particular, any graph with chromatic number $Ω(r\sqrt{\log r})$ contains a $K_r$ minor, a partial result towards Hadwiger's famous conjecture. In this paper, we investigate analogues of these results in the directed setting. There