May 2022 arXiv papers — page 94

Avanti Athreya, Zachary Lubberts, Youngser Park, Carey E Priebe

Analyzing changes in network evolution is central to statistical network inference, as underscored by recent challenges of predicting and distinguishing pandemic-induced transformations in organizational and communication networks. We consider a joint network model in which each node has an associated time-varying low-dimensional latent vector of feature dat

Pavel Baláž

$90^\circ$ pinned magnetic domain walls can be observed in thin magnetic layers attached to a ferroelectric substrate. The main stabilization mechanism of the noncollinear magnetic texture is the strain transfer which is responsible for imprinting of the ferroelectic domains into the uniaxial anisotropy of the ferromagnet. Here, we investigate by means of mi

Daniel Singh

In this thesis I give a new description for the moduli space of stable n pointed curves of genus zero and explicitly specify a natural isomorphism and inverse between them that preserves many important properties. I also give a natural description for the universal curve of this space. These descriptions are explicit and defined in a straight forward way. I

Alicia Shin

Aim: There is increasing interest in the role of chronic inflammation on pathogenesis of various disease, and one of its markers, high NLR is associated with various mortality and morbidity risk. Insulin resistance (IR) might be one potential associate factors, as suggested in preclinical studies. However, epidemiological studies are scarce which investigate

Catherine Meusburger

We define a Turaev-Viro-Barrett-Westbury state sum model of triangulated 3-manifolds with surface, line and point defects. Surface defects are oriented embedded 2d PL submanifolds and are labeled with bimodule categories over spherical fusion categories with bimodule traces. Line and point defects form directed graphs on these surfaces and labeled with bimod

Shuo Cheng, Guoxian Song, Wan-Chun Ma, Chao Wang

We present a framework that uses GAN-augmented images to complement certain specific attributes, usually underrepresented, for machine learning model training. This allows us to improve inference quality over those attributes for the facial recognition tasks.

Aaron Berk, Simone Brugiapaglia, Tim Hoheisel

This paper provides a variational analysis of the unconstrained formulation of the LASSO problem, ubiquitous in statistical learning, signal processing, and inverse problems. In particular, we establish smoothness results for the optimal value as well as Lipschitz properties of the optimal solution as functions of the right-hand side (or measurement vector)

Philippe Laban, Chien-Sheng Wu, Wenhao Liu, Caiming Xiong

Precisely assessing the progress in natural language generation (NLG) tasks is challenging, and human evaluation to establish a preference in a model's output over another is often necessary. However, human evaluation is usually costly, difficult to reproduce, and non-reusable. In this paper, we propose a new and simple automatic evaluation method for NLG ca

Ziyue Wu, David Benkeser

Complex distributions of the healthcare expenditure pose challenges to statistical modeling via a single model. Super learning, an ensemble method that combines a range of candidate models, is a promising alternative for cost estimation and has shown benefits over a single model. However, standard approaches to super learning may have poor performance in set

João G. F. Campos, Azadeh Mohammadi

This paper investigates a model containing $\phi^4$ kinks interacting with fermions. The fermion back-reaction is included in the equations of motion, which affects the kink-antikink collisions. We show that the fermion field generates a force that can be either attractive or repulsive. Moreover, we investigate three different scenarios, which exhibit a wide

Debangan Dey, Vadim Zipunnikov

Clinical and epidemiological studies encode participant information in multivariate vectors with mixed type variables on continuous, truncated, ordinal, and binary scales. Semiparametric Gaussian Copula (SGC) assumes that observed data is generated by latent multivariate normal random variables which marginals are monotonically transformed and then truncated

Cenalo Vaz

"Time" has different meanings in classical general relativity and in quantum theory. While all choices of a time function yield the same local classical geometries, quantum theories built on different time functions are not unitarily equivalent. This incompatibility is most vivid in model systems for which exact quantum descriptions in different time variabl

Himanshu Sharma

Bounce Rate of different E-commerce websites depends on the different factors based upon the different devices through which traffic share is observed. This research paper focuses on how the type of products sold by different E-commerce websites affects the bounce rate obtained through Mobile/Desktop. It tries to explain the observations which counter the ge

Loïc Chaumont, Thomas Pellas

A L\'evy process is said to creep through a curve if, at its first passage time across this curve, the process reaches it with positive probability. We first study this property for bivariate subordinators. Given the graph $\{(t,f(t)):t\ge0\}$ of any continuous, non increasing function $f$ such that $f(0)>0$, we give an expression of the probability that a b

Katsuhisa Koshino

In this paper, we give a characterization of compact sets in $L^p$-spaces on metric measure spaces, which is a generalization of the Kolmogorov-Riesz theorem. Using the criterion, we investigate the topological type of the space consisting of lipschitz maps with bounded supports.

Yilin Yang, Tomas Fieg, Marina Sokolova

This paper focuses on Sentiment Analysis of Covid-19 related messages from the r/Canada and r/Unitedkingdom subreddits of Reddit. We apply manual annotation and three Machine Learning algorithms to analyze sentiments conveyed in those messages. We use VADER and TextBlob to label messages for Machine Learning experiments. Our results show that removal of shor

Jadie Adams, Shireen Elhabian

Statistical shape modeling (SSM) directly from 3D medical images is an underutilized tool for detecting pathology, diagnosing disease, and conducting population-level morphology analysis. Deep learning frameworks have increased the feasibility of adopting SSM in medical practice by reducing the expert-driven manual and computational overhead in traditional S

Joao Henrique Inacio de Souza, Jose Carlos Marinello, Abolfazl Amiri, Taufik Abrao

Providing minimum quality-of-service (QoS) in crowded wireless communications systems, with high user density, is challenging due to the network structure with limited transmit power budget and resource blocks. Smart resource allocation methods, such as user scheduling, power allocation, and modulation and coding scheme selection, must be implemented to cope

Luis Briceño-Arias, Fernando Roldán

In this article we provide a splitting method for solving monotone inclusions in a real Hilbert space involving four operators: a maximally monotone, a monotone-Lipschitzian, a cocoercive, and a monotone-continuous operator. The proposed method takes advantage of the intrinsic properties of each operator, generalizing the forward-back-half forward splitting

Alexander Vera, Boyang Zheng, Wilson Yanez, Kaijie Yang

A scalable platform to synthesize ultrathin heavy metals may enable high efficiency charge-to-spin conversion for next-generation spintronics. Here we report the synthesis of air-stable, epitaxially registered monolayer Pb underneath bilayer graphene on SiC (0001) by confinement heteroepitaxy (CHet). Diffraction, spectroscopy, and microscopy reveal CHet-base

Haakon Robinson, Suraj Pawar, Adil Rasheed, Omer San

The success of the current wave of artificial intelligence can be partly attributed to deep neural networks, which have proven to be very effective in learning complex patterns from large datasets with minimal human intervention. However, it is difficult to train these models on complex dynamical systems from data alone due to their low data efficiency and s

Andrew Fraser, Brian Lavallee, Blair D. Sullivan

In a representative democracy, the electoral process involves partitioning geographical space into districts which each elect a single representative. These representatives craft and vote on legislation, incentivizing political parties to win as many districts as possible (ideally a plurality). Gerrymandering is the process by which district boundaries are m

Kejian Qu, Daniel P. Shoemaker

Few materials undergo cooperative Jahn-Teller (JT) transitions at low temperatures, but zircon-type oxides are one class that includes DyVO$_4$, which transforms from a tetragonal to an orthorhombic structure at around 13.6 K, with a narrow transition temperature range within 0.5 K. Since many rare-earth ions can be accommodated in the structure, there shoul

Peter Warren, Nandhini Raju, Hossein Ebrahimi, Milos Krsmanovic

Cylindrical specimens of Martian and Lunar regolith simulants were molded using a salt water binder and sintered at various temperatures for comparing microstructure, mechanical properties and shrinkage. Material microstructure are reported using optical microscope and material testing is done using an MTS universal testing machine. The experimental protocol

Jyotima Patel, Biswanath Dutta

There is enormous growth in various fields of research. This development is accompanied by new problems. To solve these problems efficiently and in an optimized manner, algorithms are created and described by researchers in the scientific literature. Scientific algorithms are vital for understanding and reusing existing work in numerous domains. However, alg

Zhizhang Wang, Ling Xiao

In [19], we prove that if an entire, spacelike, convex hypersurface $\mathcal{M}_{u_0}$ has bounded principal curvatures, then the $\sigma_k^{1/\alpha}$ (power of $\sigma_k$) curvature flow starting from $\mathcal{M}_{u_0}$ admits a smooth convex solution $u$ for $t>0.$ Moreover, after rescaling, the flow converges to a convex self-expander $\tilde{\mathcal{

Hector Suni Puma, Christian S. Rodrigues

In this paper, we study stochastic stability of a dynamical system with shadowing property, which evolves under small random perturbation. We prove that time averages along the pseudo-trajectory converge with respect to stationary measure for the randomly perturbed dynamics. In particular, we prove that stationary measures converge to physical measures when

Nader Khammassi, Randy W. Morris, Shavindra Premaratne, Florian Luthi

Execution of quantum algorithms requires a quantum computer architecture with a dedicated quantum instruction set that is capable of supporting translation of workloads into actual quantum operations acting on the qubits. State-of-the-art qubit control setups typically utilize general purpose test instruments such as arbitrary waveform generators (AWGs) to g

Matteo Bonforte, Jørgen Endal

We establish boundedness estimates for solutions of generalized porous medium equations of the form $$ \partial_t u+(-\mathfrak{L})[u^m]=0\quad\quad\text{in $\mathbb{R}^N\times(0,T)$}, $$ where $m\geq1$ and $-\mathfrak{L}$ is a linear, symmetric, and nonnegative operator. The wide class of operators we consider includes, but is not limited to, L\'evy operato

Zhizhang Wang, Ling Xiao

In this paper, we study fully nonlinear curvature flows of noncompact spacelike hypersurfaces in Minkowski space. We prove that if the initial hypersurface satisfies certain conditions, then the flow exists for all time. Moreover, we show that after rescaling the flow converges to the future timelike hyperboloid, which is a self-expander.

Rony Shohet, Mohamed Kandil, Y. Wang, J. J. McArthur

Building performance has been shown to degrade significantly after commissioning, resulting in increased energy consumption and associated greenhouse gas emissions. Continuous Commissioning using existing sensor networks and IoT devices has the potential to minimize this waste by continually identifying system degradation and re-tuning control strategies to

Frédéric Caupin

When a fluid is constrained to a fixed, finite volume, the conditions for liquid-vapor equilibrium are different from the infinite volume or constant pressure cases. There is even a range of densities for which no bubble can form, and the liquid at a pressure below the bulk saturated vapor pressure remains indefinitely stable. As fluid density in mineral inc

Yury Tyurin, Anastasia Tyurina

We present a decomposition of finitely supported filters ( aka instrument function PSF) as a composition of invertible and non-invertible filters. The invertible component can be inverted directly and the non-invertible component is shown to decrease the resolution of the acquired signal.

Zhiyu Zhang, Ashok Cutkosky, Ioannis Ch. Paschalidis

Practical online learning tasks are often naturally defined on unconstrained domains, where optimal algorithms for general convex losses are characterized by the notion of comparator adaptivity. In this paper, we design such algorithms in the presence of switching cost - the latter penalizes the typical optimism in adaptive algorithms, leading to a delicate

Anthony M. Polloreno, Graeme Smith

The Quantum Approximate Optimization Algorithm (QAOA) was originally developed to solve combinatorial optimization problems, but has become a standard for assessing the performance of quantum computers. Fully descriptive benchmarking techniques are often prohibitively expensive for large numbers of qubits ($n \gtrsim 10$), so the QAOA often serves in practic

Tarek Mealy, Filippo Capolino

We demonstrate that exceptional points of degeneracy (EPDs) are obtained in two coupled waveguides without resorting to gain and loss. We show the general concept that modes resulting from a proper coupling of forward and backward waves exhibit EPDs of order two and that there the group velocity vanishes. We verify our insight by using coupled mode theory an

Junyeong Ahn, Su-Yang Xu, Ashvin Vishwanath

Emergent axion electrodynamics in magneto-electric media is expected to provide novel ways to detect and control material properties with electromagnetic fields. However, despite being studied intensively for over a decade, its theoretical understanding remains mostly confined to the static limit. Here, we introduce a theory of axion electrodynamics at gener

Kevin Nguetchouang, Theophile Dubuc, Stella Bitchebe, Alain Tchana

Contrary to the other resources such as CPU, memory, and network, for which virtualization is efficiently achieved through direct access, disk virtualization is peculiar. In this paper, we make four contributions. Our first contribution is the characterization of disk utilization in a public large-scale cloud infrastructure. It reveals the presence of long s

Michael Hanus

Logic programming is a flexible programming paradigm due to the use of predicates without a fixed data flow. To extend logic languages with the compact notation of functional programming, there are various proposals to map evaluable functions into predicates in order to stay in the logic programming framework. Since amalgamated functional logic languages off

Damir Korenčić, Ivan Grubišić

What is the relation between a word and its description, or a word and its embedding? Both descriptions and embeddings are semantic representations of words. But, what information from the original word remains in these representations? Or more importantly, which information about a word do these two representations share? Definition Modeling and Reverse Dic

Weizhao Tang, Lucianna Kiffer, Giulia Fanti, Ari Juels

Most permissionless blockchain networks run on peer-to-peer (P2P) networks, which offer flexibility and decentralization at the expense of performance (e.g., network latency). Historically, this tradeoff has not been a bottleneck for most blockchains. However, an emerging host of blockchain-based applications (e.g., decentralized finance) are increasingly se

Gregor Lenz, Serge Picaud, Sio-Hoi Ieng

We present the first publicly available Android framework to stream data from an event camera directly to a mobile phone. Today's mobile devices handle a wider range of workloads than ever before and they incorporate a growing gamut of sensors that make devices smarter, more user friendly and secure. Conventional cameras in particular play a central role in

Carlos Saavedra, Deepak Pandey, Wolfgang Alt, Dieter Meschede

Optical spectroscopic sensors are powerful tools for analysing gas mixtures in industrial and scientific applications. Whilst highly sensitive spectrometers tend to have a large footprint, miniaturized optical devices usually lack sensitivity or wideband spectroscopic coverage. By employing a widely tunable, passively stable fiber Fabry-Perot cavity (FFPC),

K. D. Olumoyin, A. Q. M. Khaliq, K. M. Furati

Mutating variants of COVID-19 have been reported across many US states since 2021. In the fight against COVID-19, it has become imperative to study the heterogeneity in the time-varying transmission rates for each variant in the presence of pharmaceutical and non-pharmaceutical mitigation measures. We develop a Susceptible-Exposed-Infected-Recovered mathemat

Susana Cebrián

Dark matter particles populating our galactic halo could be directly detected by measuring their scattering off target nuclei or electrons in a suitable detector. As this interaction is expected to occur with very low probability and would generate very small energy deposits, the detection is challenging; the possible identification of distinctive signatures

G. Vietri, T. Misawa, E. Piconcelli, P. Franzetti

We report on the variability of a multi-component broad absorption line (BAL) system observed in the hyper-luminous quasar J1538+0855 at z=3.6. Observations from SDSS, VLT, LBT and Subaru telescopes taken at five different epochs, spanning 17 yr in the observed frame, are presented. We detect three (A, B, C) CIV variable troughs exhibiting extreme velocities

Maurizio Giannotti

The physics of axions and axion-like particles (ALPs) is enjoying an incredibly productive period, with many new experimental proposals, theoretical idea, and original astrophysical and cosmological arguments which help the search effort. The large number of experimental proposals is likely to lead to fundamental advances (perhaps, a discovery?) in the comin

Qiang Gao, Eslam Khalaf

Lattice dynamics play a crucial role in the physics of Moir\'e systems. In twisted bilayer graphene (TBG), it was shown that, in addition to the graphene phonons, there is another set of gapless excitations termed Moir\'e Phonons [Phys. Rev. B, 075416, 2019] reflecting the lattice dynamics at the Moire superlattice level. These modes were later suggested to

Wen-Han Kao, Natalia B. Perkins

We study the Kitaev spin ladder with random couplings by using the real-space renormalization group technique. This model is the minimum model in Kitaev systems that has conserved plaquette fluxes, and its quasi-one-dimensional geometry makes it possible to study the strong-disorder fixed points for both spin- and flux- excitation gaps. In the Ising limit, t

Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé

There are many ways to express similar things in text, which makes evaluating natural language generation (NLG) systems difficult. Compounding this difficulty is the need to assess varying quality criteria depending on the deployment setting. While the landscape of NLG evaluation has been well-mapped, practitioners' goals, assumptions, and constraints -- whi

Elizabeth J. Gonzalez, Kai Hoffmann, Diego R. García Lambas, Enrique Gaztañaga

Constraints on dark matter halo masses from weak gravitational lensing can be improved significantly by using additional information about the morphology of their density distribution, leading to tighter cosmological constraints derived from the halo mass function. This work is the first of two in which we investigate the accuracy of halo morphology and mass

H. P. Ojeda Collado, Nicolò Defenu, José Lorenzana

We generalize the dynamical phase diagram of a Bardeen-Cooper-Schrieffer condensate, considering attractive to repulsive, i.e., critical quenches (CQ) and a non-constant density of states (DOS). We show that different synchronized Higgs dynamical phases can be stabilized, associated with singularities in the density of states (DOS) and different quench proto

Michelle L. M. Collins, Justin I. Read

Feedback to the interstellar medium (ISM) from ionising radiation, stellar winds and supernovae is central to regulating star formation in galaxies. Due to their low mass ($M_{*} < 10^{9}$\,M$_\odot$), dwarf galaxies are particularly susceptible to such processes, making them ideal sites to study the detailed physics of feedback. In this perspective, we summ

Linda M. Carpenter, Taylor Murphy, Tim M. P. Tait

We study a renormalizable model of Dirac fermion dark matter (DM) that communicates with the Standard Model (SM) through a pair of mediators -- one scalar, one fermion -- in the representation $(\boldsymbol{6},\boldsymbol{1}, \tfrac{4}{3})$ of the SM gauge group $\text{SU}(3)_{\text{c}} \times \text{SU}(2)_{\text{L}} \times \text{U}(1)_Y$. While such assignm

Andrei P. Igoshev, Anastasia Frantsuzova, Konstantinos N. Gourgouliatos, Savina Tsichli

Initial distributions of pulsar periods and magnetic fields are essential components of multiple modern astrophysical models. Not enough work has been done to properly constrain these distributions using direct measurements. Here we aim to fill this gap by rigorously analysing properties of young neutron stars associated to supernova remnants. In order to pe

Jun Yong Khoo, Falko Pientka, Patrick A. Lee, Inti Sodemann Villadiego

We study the transverse electrical conductivity and the corresponding magnetic noise of a two-dimensional U(1) spin liquid state with a spinon Fermi surface. We show that in the quasi-static regime these responses have the same wave-vector dependence as that of a metal but are reduced by a dimensionless pre-factor controlled by the ratio of orbital diamagnet

Abhish Dev, Gordan Krnjaic, Pedro Machado, Harikrishnan Ramani

If ultralight $(\ll$ eV), bosonic dark matter couples to right handed neutrinos, active neutrino masses and mixing angles depend on the ambient dark matter density. When the neutrino Majorana mass, induced by the dark matter background, is small compared to the Dirac mass, neutrinos are "pseudo-Dirac" fermions that undergo oscillations between nearly degener

Konstantinos Tassis, Vasiliki Pavlidou

Molecular clouds in the central molecular zone (CMZ) have been observed to feature turbulent line widths that are significantly higher, and scale with cloud size more steeply, than in the rest of the Milky Way. In the same Galactic region, the stellar density is also much higher than in the rest of the Milky Way, and the vertical stellar velocity dispersion

Fabio Rigamonti, Massimo Dotti, Stefano Covino, Francesco Haardt

Dissecting the underlying structure of galaxies is of main importance in the framework of galaxy formation and evolution theories. While a classical bulge+disc decomposition of disc galaxies is usually taken as granted, this is only rarely solidly founded upon the full exploitation of the richness of data arising from spectroscopic studies with integral fiel

Pedro Cal, Jesse Thaler, Wouter J. Waalewijn

Power counting is a systematic strategy for organizing collider observables and their associated theoretical calculations. In this paper, we use power counting to characterize a class of jet substructure observables called energy flow polynomials (EFPs). EFPs provide an overcomplete linear basis for infrared-and-collinear safe jet observables, but it is know

David E. Kaplan, Andrea Mitridate, Tanner Trickle

Pulsar Timing Arrays (PTAs) are exceptionally sensitive detectors in the frequency band $\text{nHz} \lesssim f \lesssim \mu\text{Hz}$. Ultralight dark matter (ULDM), with mass in the range $10^{-23}\,\text{eV} \lesssim m_\phi \lesssim 10^{-20}\,\text{eV}$, is one class of DM models known to generate signals in this frequency window. While purely gravitationa

Rhine Samajdar, Yanting Teng, Mathias S. Scheurer

Twisted trilayer graphene is a particularly promising moir\'e superlattice system, due to its tunability, strong superconductivity, and complex electronic symmetry breaking. Motivated by these properties, we study lattice relaxation and the long-wavelength phonon modes of this system. We show that mirror-symmetric trilayer graphene hosts, aside from the conv

Stephen Bates, Michael I. Jordan, Michael Sklar, Jake A. Soloff

Consider the relationship between a regulator (the principal) and an experimenter (the agent) such as a pharmaceutical company. The pharmaceutical company wishes to sell a drug for profit, whereas the regulator wishes to allow only efficacious drugs to be marketed. The efficacy of the drug is not known to the regulator, so the pharmaceutical company must run

Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

We study the linear contextual bandit problem in the presence of adversarial corruption, where the reward at each round is corrupted by an adversary, and the corruption level (i.e., the sum of corruption magnitudes over the horizon) is $C\geq 0$. The best-known algorithms in this setting are limited in that they either are computationally inefficient or requ

Jess Banks, Jorge Garza-Vargas, Nikhil Srivastava

We develop a framework for proving rapid convergence of shifted QR algorithms which use Ritz values as shifts, in finite arithmetic. Our key contribution is a dichotomy result which addresses the known forward-instability issues surrounding the shifted QR iteration [Parlett and Le 1993]: we give a procedure which provably either computes a set of approximate

Pere Mujal, Rodrigo Martínez-Peña, Gian Luca Giorgi, Miguel C. Soriano

Quantum machine learning represents a promising avenue for data processing, also for purposes of sequential temporal data analysis, as recently proposed in quantum reservoir computing (QRC). The possibility to operate on several platforms and noise intermediate-scale quantum devices makes QRC a timely topic. A challenge that has not been addressed yet, howev

Pratik Kumar, Sajal K. Paul

In this paper, a new design has been proposed for the realization of high-frequency memcapacitor emulators built with three OTAs. This paper also proposes the application of memcapacitor as an amplitude modulator. Furthermore, applications of memcapacitor as a filter, Oscillator point attractor, and periodic doubler are also shown. The proposed circuits can

Ludwig A. Hoffmann, Livio Nicola Carenza, Luca Giomi

Recent experimental observations have suggested that topological defects can facilitate the creation of sharp features in developing embryos. Whereas these observations echo established knowledge about the interplay between geometry and topology in two-dimensional passive liquid crystals, the role of activity has mostly remained unexplored. In this article w

Jess Banks, Jorge Garza-Vargas, Nikhil Srivastava

We give a self-contained randomized algorithm based on shifted inverse iteration which provably computes the eigenvalues of an arbitrary matrix $M\in\mathbb{C}^{n\times n}$ up to backward error $\delta\|M\|$ in $O(n^4+n^3\log^2(n/\delta)+\log(n/\delta)^2\log\log(n/\delta))$ floating point operations using $O(\log^2(n/\delta))$ bits of precision. While the $O

Yuchao Gu, Xintao Wang, Liangbin Xie, Chao Dong

Although generative facial prior and geometric prior have recently demonstrated high-quality results for blind face restoration, producing fine-grained facial details faithful to inputs remains a challenging problem. Motivated by the classical dictionary-based methods and the recent vector quantization (VQ) technique, we propose a VQ-based face restoration m

T. Zalialiutdinov, D. Solovyev, D. Chubukov, S. Chekhovskoi

It is well-known that the 4-rotation in the 4-dimensional space-time is equivalent to the CPT-transformation (C is the charge conjugation, P is the space inversion and T is the time-reversal). The standard definition of the T-reversal includes the change of the sign of time variable and replacement of the initial state of the particle (system of particles) b

Collin Farquhar, Prem Sagar Pattanshetty Vasanth Kumar, Anu Jagannath, Jithin Jagannath

We examine the problem of transmission control, i.e., when to transmit, in distributed wireless communications networks through the lens of multi-agent reinforcement learning. Most other works using reinforcement learning to control or schedule transmissions use some centralized control mechanism, whereas our approach is fully distributed. Each transmitter n

Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler

The ACM Multimedia 2022 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Vocalisations and Stuttering Sub-Challenges, a classification on human non-verbal vocalisations and speech has to be made; the Activity Sub-Challenge aims at beyond-audio human ac

Hong Hu, Yue M. Lu

The generalization performance of kernel ridge regression (KRR) exhibits a multi-phased pattern that crucially depends on the scaling relationship between the sample size $n$ and the underlying dimension $d$. This phenomenon is due to the fact that KRR sequentially learns functions of increasing complexity as the sample size increases; when $d^{k-1}\ll n\ll

Marek Napiórkowski, Marcin Pruszczyk

We consider an ideal Bose gas enclosed in a $d$-dimensional slab of thickness $D$. Using the grand canonical ensemble we calculate the variance of the thermal Casimir force acting on the slab's walls. The variance evaluated per unit wall area is shown to decay like $ \Delta_{var}/D$ for large $D$. The amplitude $ \Delta_{var}$ is a non-universal function of

Anna Antal, Stanley Pritchard

We compute the involutive concordance invariants for the 10- and 11-crossing (1,1)-knots.

Frank Merle, Hatem Zaag

We consider the semilinear heat equation with a superlinear power nonlinearity in the Sobolev subcritical range. We construct a solution which blows up in finite time only at the origin, with a completely new blow-up profile, which is cross-shaped. Our method is general and extends to the construction of other solutions blowing up only at the origin, with a

Lars Kool, Patrick Charbonneau, Karen E. Daniels

We report experimental evidence of a Gardner-like transition from variable to persistent force contacts in a two-dimensional, bidisperse granular crystal by analyzing the variability of both particle positions and force networks formed under uniaxial compression. Starting from densities just above the freezing transition, and for variable amounts of addition

Francisco Maturana, K. V. Rashmi

Distributed storage systems must store large amounts of data over long periods of time. To avoid data loss due to device failures, an $[n,k]$ erasure code is used to encode $k$ data symbols into a codeword of $n$ symbols that are stored across different devices. However, device failure rates change throughout the life of the data, and tuning $n$ and $k$ acco

Tianhui Zhou, William E. Carson, Michael Hunter Klein, David Carlson

Observational studies are regarded as economic alternatives to randomized trials, often used in their stead to investigate and determine treatment efficacy. Due to lack of sample size, observational studies commonly combine data from multiple sources or different sites/centers. Despite the benefits of an increased sample size, a naive combination of multicen

Gábor Bíró, Mihály Pocsai, Imre Ferenc Barna, Joshua T. Moody

We investigate the usage of a Schlieren imaging setup to measure the geometrical dimensions of a plasma channel in atomic vapor. Near resonant probe light is used to image the plasma channel in a tenuous vapor and machine learning techniques are tested for extracting quantitative information from the images. By building a database of simulated signals with a

Breno Costa, Joao Bachiega, Leonardo Reboucas de Carvalho, Michel Rosa

Fog computing is a distributed paradigm that provides computational resources in the users' vicinity. Fog orchestration is a set of functionalities that coordinate the dynamic infrastructure and manage the services to guarantee the Service Level Agreements. Monitoring is an orchestration functionality of prime importance. It is the basis for resource managem

Alexander Zheglov

The notion of quasi-elliptic rings appeared as a result of an attempt to classify a wide class of commutative rings of operators found in the theory of integrable systems, such as rings of commuting differential, difference, differential-difference, etc. operators. They are contained in a certain non-commutative "universal" ring - a purely algebraic analogue

Josina O. do Nascimento, Valmir C. Barbosa

We build a four-dimensional linear model of object membership in the Beta Pictoris moving group (BPMG), using two nested applications of Principal Component Analysis (PCA) to high-quality data on about 1.5 million objects. These data contain the objects' galactic space velocities and also their Gaia $G$ magnitudes. Through PCA, they ultimately result in a fo

Frank de Meijer, Renata Sotirov, Angelika Wiegele, Shudian Zhao

The graph partition problem (GPP) aims at clustering the vertex set of a graph into a fixed number of disjoint subsets of given sizes such that the sum of weights of edges joining different sets is minimized. This paper investigates the quality of doubly nonnegative (DNN) relaxations, i.e., relaxations having matrix variables that are both positive semidefin

G. S. Osipenko

We consider a discrete dynamical system on a compact manifold M generated by a homeomorphism f. Let C = {M(i)} be a finite covering of M by closed cells. The symbolic image of a dynamical system is a directed graph G with vertices corresponding to cells in which vertices i and j are joined by an arc i to j if the image f(M(i)) intersects M(j). We show that t

Raul Quiroga-Barranco, Monyrattanak Seng

Let us consider, for $n \geq 3$, the Cartan domain $\mathrm{D}_n^{\mathrm{IV}}$ of type IV. On the weighted Bergman spaces $\mathcal{A}^2_\lambda(\mathrm{D}_n^{\mathrm{IV}})$ we study the problem of the existence of commutative $C^*$-algebras generated by Toeplitz operators with special symbols. We focus on the subgroup $\mathrm{SO}(n) \times \mathrm{SO}(2)$

Stephanie L. Olson, Malte F. Jansen, Dorian S. Abbot, Itay Halevy

The influence of atmospheric composition on the climates of present-day and early Earth has been studied extensively, but the role of ocean composition has received less attention. We use the ROCKE-3D ocean-atmosphere general circulation model to investigate the response of Earth's present-day and Archean climate system to low vs. high ocean salinity. We fin

Shyamgopal Karthik, Massimiliano Mancini, Zeynep Akata

The goal of open-world compositional zero-shot learning (OW-CZSL) is to recognize compositions of state and objects in images, given only a subset of them during training and no prior on the unseen compositions. In this setting, models operate on a huge output space, containing all possible state-object compositions. While previous works tackle the problem b

Daniel T. Chang

Dual embodied-symbolic concept representations are the foundation for deep learning and symbolic AI integration. We discuss the use of dual embodied-symbolic concept representations for molecular graph representation learning, specifically with exemplar-based contrastive self-supervised learning (SSL). The embodied representations are learned from molecular

Rohit K. Gupta, Supriya Kar, R. Nitish, Monika Verma

We show that the extremal Reissner-Nordstr\"{o}m type multi black holes in an emergent scenario are exact in General Relativity. It is shown that an axion in the bulk together with a geometric torsion ensure the required energy-momentum to source the $(3$$+$$1)$ geometry in the Einstein tensor. Analysis reveals a significant role of dark energy to the curved

Haider Al Kim, Kai Jie Chan

This work deals with error correction for non-volatile memories that are partially defective at some levels. Such memory cells can only store incomplete information since some of their levels cannot be utilized entirely due to, e.g., wearout. On top of that, this paper corrects random errors $t\geq 1$ that could happen among $u$ partially defective cells whi

Madhurima Chakraborty, Renzo Olivares, Manu Sridharan, Behnaz Hassanshahi

Building sound and precise static call graphs for real-world JavaScript applications poses an enormous challenge, due to many hard-to-analyze language features. Further, the relative importance of these features may vary depending on the call graph algorithm being used and the class of applications being analyzed. In this paper, we present a technique to aut

Qiuhui Chen, Yi Hong

Recently, weakly-supervised image segmentation using weak annotations like scribbles has gained great attention, since such annotations are much easier to obtain compared to time-consuming and label-intensive labeling at the pixel/voxel level. However, because scribbles lack structure information of region of interest (ROI), existing scribble-based methods s

Rui Chen, Wee Teck Gan

In this paper, we investigate the twisted GGP conjecture for certain tempered representations using the theta correspondence and establish some special cases, namely when the L-parameter of the unitary group is the sum of conjugate-dual characters of the appropriate sign.

W. Jeffrey Johnston, Justin M. Fine, Seng Bum Michael Yoo, R. Becket Ebitz

When choosing between options, we must solve an important binding problem. The values of the options must be associated with information about the action needed to select them. We hypothesize that the brain solves this binding problem through use of distinct population subspaces. To test this hypothesis, we examined the responses of single neurons in five re

Qing Gu, Qi Guo, Tianchi Zhang, Marius Cautun

The planar distributions of satellite galaxies around the Milky Way and Andromeda have been extensively studied as potential challenges to the standard cosmological model. Using the Sloan Digital Sky Survey and the Millennium simulation we extend such studies to the satellite galaxies of massive galaxy clusters. We find that both observations and simulations

Efrat Levy, Ben Nassi, Raz Swissa, Yuval Elovici

The ability to detect whether an object is a 2D or 3D object is extremely important in autonomous driving, since a detection error can have life-threatening consequences, endangering the safety of the driver, passengers, pedestrians, and others on the road. Methods proposed to distinguish between 2 and 3D objects (e.g., liveness detection methods) are not su

Weimin Lyu, Songzhu Zheng, Tengfei Ma, Chao Chen

Trojan attacks raise serious security concerns. In this paper, we investigate the underlying mechanism of Trojaned BERT models. We observe the attention focus drifting behavior of Trojaned models, i.e., when encountering an poisoned input, the trigger token hijacks the attention focus regardless of the context. We provide a thorough qualitative and quantitat

Bianca Gualandi, Luca Pareschi, Silvio Peroni

Purpose: This article describes the interviews we conducted in late 2021 with 19 researchers at the Department of Classical Philology and Italian Studies at the University of Bologna. The main purpose was to shed light on the definition of the word "data" in the humanities domain, as far as FAIR data management practices are concerned, and on what researcher