August 2022 arXiv papers — page 113

Larry Han, Andrea Arfe, Lorenzo Trippa

The use of simulation-based sensitivity analyses is fundamental to evaluate and compare candidate designs for future clinical trials. In this context, sensitivity analyses are especially useful to assess the dependence of important design operating characteristics (OCs) with respect to various unknown parameters (UPs). Typical examples of OCs include the lik

David H. Wolpert

In this essay I will consider a sequence of questions. The first questions concern the biological function of intelligence in general, and cognitive prostheses of human intelligence in particular. These will lead into questions concerning human language, perhaps the most important cognitive prosthesis humanity has ever developed. While it is traditional to r

Tim W. Reid, Ilse C. F. Ipsen, Jon Cockayne, Chris J. Oates

We analyse the calibration of BayesCG under the Krylov prior, a probabilistic numeric extension of the Conjugate Gradient (CG) method for solving systems of linear equations with symmetric positive definite coefficient matrix. Calibration refers to the statistical quality of the posterior covariances produced by a solver. Since BayesCG is not calibrated in t

Daniele Bartoli, Lukas Kölsch, Giacomo Micheli

Differential cryptanalysis famously uses statistical biases in the propagation of differences in a block cipher to attack the cipher. In this paper, we investigate the existence of more general statistical biases in the differences. To this end, we discuss the $c$-differential uniformity of S-boxes, which is a concept that was recently introduced in Ellingse

Lu Meng, Bo Wang, Shi-Lin Zhu

Very recently, the LHCb Collaboration reported the first observation of the hidden charm pentaquark with strangeness, $P_{\psi s}^\Lambda(4338)^0$. Considering this state is very close to the $\Xi_c^0\bar{D}^0$ and $\Xi_c^+D^-$ thresholds, we explore the possible bias of the Breit-Wigner parameterization, with emphasis on the effect of its coupling to the do

Vlad Yaskin

Busemann's intersection inequality gives an upper bound for the volume of the intersection body of a star body in terms of the volume of the body itself. Koldobsky, Paouris, and Zymonopoulou asked if there is a similar result for $k$-intersection bodies. We solve this problem for star bodies that are close to the Euclidean ball in the Banach-Mazur distance.

Mohammad Pirani, Saber Jafarpour

In a Nature article, Scheffer et al. presented a novel data-driven framework to predict critical transitions in complex systems. These transitions, which may stem from failures, degradation, or adversarial actions, have been attributed to bifurcations in the nonlinear dynamics. Their approach was built upon the phenomenon of critical slowing down, i.e., slow

Taiki Kawamuro, Claudio Ricci, Masatoshi Imanishi, Richard F. Mushotzky

To understand the origin of nuclear ($\lesssim$ 100 pc) millimeter-wave (mm-wave) continuum emission in active galactic nuclei (AGNs), we systematically analyzed sub-arcsec resolution Band-6 (211-275 GHz) ALMA data of 98 nearby AGNs ($z <$ 0.05) from the 70-month Swift/BAT catalog. The sample, almost unbiased for obscured systems, provides the largest number

Wei Luo, Tongzhi Niu, Lixin Tang, Wenyong Yu

In surface defect detection, due to the extreme imbalance in the number of positive and negative samples, positive-samples-based anomaly detection methods have received more and more attention. Specifically, reconstruction-based methods are the most popular. However, existing methods are either difficult to repair abnormal foregrounds or reconstruct clear ba

Jin-Jie Yang, Shou-Fu Tian, Zhi-Qiang Li

We investigate the long-time asymptotic behavior for the Cauchy problem of the modified Camassa-Holm (mCH) equation with nonzero boundary conditions in different regions \begin{align*} &m_{t}+\left((u^2-u_x^2)m\right)_{x}=0,~~ m=u-u_{xx}, ~~ (x,t)\in\mathbb{R}\times\mathbb{R}^{+},\\ &u(x,0)=u_{0}(x),~~\lim_{x\to\pm\infty} u_{0}(x)=1,~~u_{0}(x)-1\in H^{4,1}(\

Chenwei Ran, Wei Shen, Jianbo Gao, Yuhan Li

Entity linking (EL) is the process of linking entity mentions appearing in text with their corresponding entities in a knowledge base. EL features of entities (e.g., prior probability, relatedness score, and entity embedding) are usually estimated based on Wikipedia. However, for newly emerging entities (EEs) which have just been discovered in news, they may

Khang Nhut Lam, Feras Al Tarouti, Jugal Kalita

This paper examines approaches to generate lexical resources for endangered languages. Our algorithms construct bilingual dictionaries and multilingual thesauruses using public Wordnets and a machine translator (MT). Since our work relies on only one bilingual dictionary between an endangered language and an "intermediate helper" language, it is applicable t

Beibei Zhu, Lun Ji, Aiqing Zhu, Yifa Tang

We propose efficient numerical methods for nonseparable non-canonical Hamiltonian systems which are explicit, K-symplectic in the extended phase space with long time energy conservation properties. They are based on extending the original phase space to several copies of the phase space and imposing a mechanical restraint on the copies of the phase space. Ex

Xiaofeng Xue

In this paper we are concerned with a family of $N$-urn branching processes, where some particles are put into $N$ urns initially and then each particle gives birth to several new particles in some urn when dies. This model includes the $N$-urn Ehrenfest model and the $N$-urn branching random walk as special cases. We show that the scaling limit of the proce

Gaurang Karwande, Amarachi Mbakawe, Joy T. Wu, Leo A. Celi

Despite the progress in utilizing deep learning to automate chest radiograph interpretation and disease diagnosis tasks, change between sequential Chest X-rays (CXRs) has received limited attention. Monitoring the progression of pathologies that are visualized through chest imaging poses several challenges in anatomical motion estimation and image registrati

Rui Zu, Bo Wang, Jingyang He, Jian-Jun Wang

Optical second harmonic generation is a second-order nonlinear process that combines two photons of a given frequency into a third photon at twice the frequency. Due to the symmetry constraints, it is widely used as a sensitive probe to detect broken inversion symmetry and local polar order. Analytical modeling of the electric-dipole SHG response is essentia

Hao Feng, Yi Zhang, Srikathyayani Srikanteswara, Marcin Spoczynski

Named Data Networking (NDN) offers promising advantages in deploying next-generation service applications over distributed computing networks. We consider the problem of dynamic orchestration over a NDN-based computing network, in which nodes can be equipped with communication, computation, and data producing resources. Given a set of services with function-

Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan

The ongoing advancements in network architecture design have led to remarkable achievements in deep learning across various challenging computer vision tasks. Meanwhile, the development of neural architecture search (NAS) has provided promising approaches to automating the design of network architectures for lower prediction error. Recently, the emerging app

Khang Nhut Lam, Feras Al Tarouti, Jugal Kalita

Manually constructing a Wordnet is a difficult task, needing years of experts' time. As a first step to automatically construct full Wordnets, we propose approaches to generate Wordnet synsets for languages both resource-rich and resource-poor, using publicly available Wordnets, a machine translator and/or a single bilingual dictionary. Our algorithms transl

Jonathan Zong, Josh Pollock, Dylan Wootton, Arvind Satyanarayan

We present Animated Vega-Lite, a set of extensions to Vega-Lite that model animated visualizations as time-varying data queries. In contrast to alternate approaches for specifying animated visualizations, which prize a highly expressive design space, Animated Vega-Lite prioritizes unifying animation with the language's existing abstractions for static and in

Thomas Schlegl, Heiko Stino, Michael Niederleithner, Andreas Pollreisz

The automatic detection and localization of anatomical features in retinal imaging data are relevant for many aspects. In this work, we follow a data-centric approach to optimize classifier training for optic nerve head detection and localization in optical coherence tomography en face images of the retina. We examine the effect of domain knowledge driven sp

John Bulava, Andrew D. Hanlon, Ben Hörz, Colin Morningstar

Elastic nucleon-pion scattering amplitudes are computed using lattice QCD on a single ensemble of gauge field configurations with $N_{\rm f} = 2+1$ dynamical quark flavors and $m_{\pi} = 200~{\rm MeV}$. The $s$-wave scattering lengths with both total isospins $I=1/2$ and $I=3/2$ are inferred from the finite-volume spectrum below the inelastic threshold toget

Nathan Donagi

This paper proves a linear algebra result that has to do with the geometry of "widgets". For us a widget is a collection of n pairs of points in a vector space. (The pairs represent the different possible spin states of a particle.) We investigate linear relations among such collections. A corollary of our theorem was conjectured in arXiv:2208.02478v1 where

Ashok Kumar Verma

Radio science data collected from NASA's Deep Space Networks (DSNs) are made available in various formats through NASA's Planetary Data System (PDS). The majority of these data are packed in complex formats, making them inaccessible to users without specialized knowledge. In this paper, we present a Python-based tool that can preprocess the closed-loop archi

Yanjun Li, Jie Peng, Haibin Kan, Lijing Zheng

Recently, much progress has been made to construct minimal linear codes due to their preference in secret sharing schemes and secure two-party computation. In this paper, we put forward a new method to construct minimal linear codes by using vectorial Boolean functions. Firstly, we give a necessary and sufficient condition for a generic class of linear codes

Khang Nhut Lam, Jugal Kalita

Bilingual dictionaries are expensive resources and not many are available when one of the languages is resource-poor. In this paper, we propose algorithms for creation of new reverse bilingual dictionaries from existing bilingual dictionaries in which English is one of the two languages. Our algorithms exploit the similarity between word-concept pairs using

Zhi Liu

Feature extraction is critical for TLS traffic analysis using machine learning techniques, which it is also very difficult and time-consuming requiring huge engineering efforts. We designed and implemented DeepTLS, a system which extracts full spectrum of features from pcaps across meta, statistical, SPLT, byte distribution, TLS header and certificates. The

Muammer Y. Yaman, Sergei V. Kalinin, Kathryn N. Guye, David Ginger

We demonstrate the application of machine learning for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational autoencoder (dual-VAE). In this approach, the information is shared between the latent spaces of two VAEs acting on the particle shape data and spectral data, respectively, but enf

Leszek Szczecinski, Harsh Sukheja

The linear ordering problem (LOP), which consists in ordering M objects from their pairwise comparisons, is commonly applied in many areas of research. While efforts have been made to devise efficient LOP algorithms, verification of whether the data are rankable, that is, if the linear ordering problem (LOP) solutions have a meaningful interpretation, receiv

Xiaoxiang Chai, Gaoming Wang

We prove a comparison theorem for certain types of polyhedra in a 3-manifold with its scalar curvature bounded below by $-6$. The result confirms in some cases the Gromov dihedral rigidity conjecture in hyperbolic $3$-space.

Wen Huang, Meng Wei, Kyle A. Gallivan, Paul Van Dooren

This paper considers the optimization problem in the form of $\min_{X \in \mathcal{F}_v} f(x) + \lambda \|X\|_1,$ where $f$ is smooth, $\mathcal{F}_v = \{X \in \mathbb{R}^{n \times q} : X^T X = I_q, v \in \mathrm{span}(X)\}$, and $v$ is a given positive vector. The clustering models including but not limited to the models used by $k$-means, community detecti

Koichi Oyanagi, Saburo Takahashi, Takashi Kikkawa, Eiji Saitoh

We have theoretically investigated the spin Seebeck effect (SSE) in a normal metal (NM)/paramagnetic insulator (PI) bilayer system. Through a linear response approach, we calculated the thermal spin pumping from PI to NM and backflow spin current from NM to PI, where the spin-flip scattering via the interfacial exchange coupling between conduction-electron s

Wade Hindes, Reiyah Jacobs, Peter Ye

We construct many irreducible polynomials within semigroups generated by sets of the form $S=\{x^2+c_1,\dots,x^2+c_s\}$ under composition.

Chris Hamilton, Elizabeth A. Tolman, Lev Arzamasskiy, Vinícius N. Duarte

The secular evolution of disk galaxies is largely driven by resonances between the orbits of 'particles' (stars or dark matter) and the rotation of non-axisymmetric features (spiral arms or a bar). Such resonances may also explain kinematic and photometric features observed in the Milky Way and external galaxies. In simplified cases, these resonant interacti

Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee

Conversational recommender systems have demonstrated great success. They can accurately capture a user's current detailed preference -- through a multi-round interaction cycle -- to effectively guide users to a more personalized recommendation. Alas, conversational recommender systems can be plagued by the adverse effects of bias, much like traditional recom

Le Chen, Jingyu Huang

In this paper, we study the stochastic heat equation (SHE) on $\mathbb{R}^d$ subject to a centered Gaussian noise that is white in time and colored in space. We establish the existence and uniqueness of the random field solution in the presence of locally Lipschitz drift and diffusion coefficients, which can have certain superlinear growth. This is a nontriv

Shinsuke Yoshida, Difei Zheng

In this paper, we propose a new calculation method for the twist-3 gluon Sivers effect within the collinear factorization approach. The method called pole calculation has been used to derive the cross section formula for the single transverse-spin asymmetry(SSA) as a standard method. We point out that we encounter a problem when we try to apply the pole calc

William McLean

The Mittag-Leffler function is computed via a quadrature approximation of a contour integral representation. We compare results for parabolic and hyperbolic contours, and give special attention to evaluation on the real line. The main point of difference with respect to similar approaches from the literature is the way that poles in the integrand are handled

Hideo Kozono, Yutaka Terasawa, Yuta Wakasugi

We study the asymptotic behavior of solutions to the steady Navier-Stokes equations outside of an infinite cylinder in $\mathbb{R}^3$. We assume that the flow is periodic in $x_3$-direction and has no swirl. This problem is closely related with two-dimensional exterior problem. Under a condition on the generalized finite Dirichlet integral, we give a pointwi

Kshitiz Bansal, Keshav Rungta, Dinesh Bharadia

Perception systems for autonomous driving have seen significant advancements in their performance over last few years. However, these systems struggle to show robustness in extreme weather conditions because sensors like lidars and cameras, which are the primary sensors in a sensor suite, see a decline in performance under these conditions. In order to solve

Vudtiwat Ngampruetikorn, David J. Schwab

Avoiding overfitting is a central challenge in machine learning, yet many large neural networks readily achieve zero training loss. This puzzling contradiction necessitates new approaches to the study of overfitting. Here we quantify overfitting via residual information, defined as the bits in fitted models that encode noise in training data. Information eff

H. Koibuchi, F. Kato, S. El Hog, G. Diguet

In this paper, we study the stability of skyrmions (SKYs) caused by the geometric confinement (GC) effect observed in nano-domains in recent experiments, where SKYs appear only inside the boundary and is stable at the low magnetic field region. However, the mechanism of the GC effect is unclear for skyrmions. We numerically find that this effect is not obser

William McLean, Kassem Mustapha

We consider the time discretization of a linear parabolic problem by the discontinuous Galerkin (DG) method using piecewise polynomials of degree at most $r-1$ in $t$, for $r\ge1$ and with maximum step size~$k$. It is well known that the spatial $L_2$-norm of the DG error is of optimal order $k^r$ globally in time, and is, for $r\ge2$, superconvergent of ord

R. M. Moita, J. P. B. C. de Melo, T. Frederico, W. de Paula

The pion structure in Minkowski space is explored using the Nakanishi integral representation. A general framework is developed for the pion Bethe-Salpeter amplitude based on the Kallen-Lehmann representation of the dressed quarks with an ansatz for the pseudo-scalar $\pi-q\bar q$ vertex fulfilling the axial Ward-Takahashi identity. The Nakanishi weight func

Nicolai Kraus, Fredrik Nordvall Forsberg, Chuangjie Xu

In a constructive setting, no concrete formulation of ordinal numbers can simultaneously have all the properties one might be interested in; for example, being able to calculate limits of sequences is constructively incompatible with deciding extensional equality. Using homotopy type theory as the foundational setting, we develop an abstract framework for or

Lucas Rosenblatt, R. Teal Witter

Making fair decisions is crucial to ethically implementing machine learning algorithms in social settings. In this work, we consider the celebrated definition of counterfactual fairness [Kusner et al., NeurIPS, 2017]. We begin by showing that an algorithm which satisfies counterfactual fairness also satisfies demographic parity, a far simpler fairness constr

Ryan Chown, Laura C. Parker, Christine D. Wilson, Toby Brown

We study the cold gas and dust properties for a sample of red star forming galaxies called "red misfits." We collect single-dish CO observations and HI observations from representative samples of low-redshift galaxies, as well as our own JCMT CO observations of red misfits. We also obtain SCUBA-2 850 um observations for a subset of these galaxies. With these

Ada Amendola, Antonio Fortunato, Fernando Fraternali, Ornella Mattei

Truss structures composed of members that work exclusively in tension or in compression appear in several problems of science and engineering, e.g., in the study of the resisting mechanisms of masonry structures, as well as in the design of spider web-inspired web structures. This work generalizes previous results on the existence of cable webs that are able

L. Martínez, H. Pinedo, A. Villamizar

Given a partial action of a topological group $G$ on a space $X$, we determine properties $\mathcal P$ which can be extended from $X$ to its globalization. We treat the cases when $\mathcal P$ is any of the following: Hausdorff, regular, metrizable, second countable and having invariant metric. Further, for a normal subgroup $H$ we introduce and study a part

Maxim Kramar, Haosheng Lin

This study presents a justification of the use of Stokes-V Cryo-NIRSP/DKIST observations for the 3D Reconstruction of the Coronal Magnetic Field. A magnetohydrodynamic (MHD) model of the solar corona during solar minimum generated by Predictive Science Inc. was used to synthesize spectropolarimetric measurements of the Fe XIII 1075 nm coronal emission line a

John B. Rundle, Andrea Donnellan, Geoffrey Fox, Lisa Grant Ludwig

Yes. Interval statistics have been used to conclude that major earthquakes are random events in time and cannot be anticipated or predicted. Machine learning is a powerful new technique that enhances our ability to understand the information content of earthquake catalogs. We show that catalogs contain significant information on current hazard and future pre

G. Lusztig

We study the intersection of the totally positive part of a split semisimple group over the real numbers with a totally positive parabolic subgroup.

Giacomo Benedetti, Luca Verderame, Alessio Merlo

The demand for quick and reliable DevOps operations pushed distributors of repository platforms to implement workflows. Workflows allow automating code management operations directly on the repository hosting the software. However, this feature also introduces security issues that directly affect the repository, its content, and all the software supply chain

Mario Krenn, Jonas Landgraf, Thomas Foesel, Florian Marquardt

In recent years, the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more

Laura Fee Nern, Harsh Raj, Maurice Georgi, Yash Sharma

As large-scale training regimes have gained popularity, the use of pretrained models for downstream tasks has become common practice in machine learning. While pretraining has been shown to enhance the performance of models in practice, the transfer of robustness properties from pretraining to downstream tasks remains poorly understood. In this study, we dem

Norman Christ, Xu Feng, Luchang Jin, Cheng Tu

We extend the application of lattice QCD to the two-photon-mediated, order $\alpha^2$ rare decay $\pi^0\rightarrow e^+ e^-$. By combining Minkowski- and Euclidean-space methods we are able to calculate the complex amplitude describing this decay directly from the underlying theories (QCD and QED) which predict this decay. The leading connected and disconnect

U. C. Perera, A. V. Afanasjev

The detailed investigation of microscopic mechanisms leading to the formation of bubble structures in the nuclei has been performed in the framework of covariant density functional theory. The main emphasis of this study is on the role of single-particle degrees of freedom and Coulomb interaction. In general, the formation of bubbles lowers the Coulomb energ

Ryan Abbott, Michael S. Albergo, Aleksandar Botev, Denis Boyda

Machine learning methods based on normalizing flows have been shown to address important challenges, such as critical slowing-down and topological freezing, in the sampling of gauge field configurations in simple lattice field theories. A critical question is whether this success will translate to studies of QCD. This Proceedings presents a status update on

Jeremy P. Bos, Stephen Grulke, Jeff Beck

We derive limits for wave optics simulations of plane wave propagation in non-Kolmogorov turbulence using the split-step method and thin phase screens. These limits are used to inform two simulation campaigns where the relationship between volume turbulence strength and normalized intensity variance for various non-Kolmogorov power-laws. We find that simulat

Davide Lombardo

In this semi-expository article we solve the diophantine equation $m^5+(4 \cdot 5^4 b^4)mn^4 - n^5=1$ for all integers $b \neq 0$. This gives an example of a family of quintic Thue equations that can be solved completely by using nothing more than Skolem's $p$-adic method. We also give a general introduction to Skolem's method from a modern perspective.

Sariel Har-Peled, Elfarouk Harb

Consider a set $P$ of $n$ points picked uniformly and independently from $[0,1]^d$ for a constant dimension $d$ -- such a point set is extremely well behaved in many aspects. For example, for a fixed $r \in [0,1]$, we prove a new concentration result on the number of pairs of points of $P$ at a distance at most $r$ -- we show that this number lies in an inte

Prateek Mantri, Hariharan Subramonyam, Audrey L. Michal, Cindy Xiong

Scientific knowledge develops through cumulative discoveries that build on, contradict, contextualize, or correct prior findings. Scientists and journalists often communicate these incremental findings to lay people through visualizations and text (e.g., the positive and negative effects of caffeine intake). Consequently, readers need to integrate diverse an

Tibor Dome, Anastasia Fialkov, Philip Mocz, Björn Malte Schäfer

The fuzzy dark matter (FDM) scenario has received increased attention in recent years due to the small-scale challenges of the vanilla Lambda cold dark matter ($\Lambda$CDM) cosmological model and the lack of any experimental evidence for any candidate particle. In this study, we use cosmological $N$-body simulations to investigate high-redshift dark matter

Lingzhi Zhang, Shenghao Zhou, Simon Stent, Jianbo Shi

Egocentric videos offer fine-grained information for high-fidelity modeling of human behaviors. Hands and interacting objects are one crucial aspect of understanding a viewer's behaviors and intentions. We provide a labeled dataset consisting of 11,243 egocentric images with per-pixel segmentation labels of hands and objects being interacted with during a di

Amged Alquliah, Mohamed ElKabbash, JinLuo Cheng, Wei Li

We present a design approach for realizing on-chip wavelength division demultiplexing (WDD) schemes by integrating all-dielectric metasurfaces of TiO2 nanorod arrays into a SiN waveguide. The designed metasurface locally modifies the effective refractive index of the SiN waveguide, creating an effective WDD that selectively passes a certain band of wavelengt

Xiatian Zhang, Noura Al Moubayed, Hubert P. H. Shum

Surgical workflow anticipation can give predictions on what steps to conduct or what instruments to use next, which is an essential part of the computer-assisted intervention system for surgery, e.g. workflow reasoning in robotic surgery. However, current approaches are limited to their insufficient expressive power for relationships between instruments. Hen

Supawit Chockchowwat, Wenjie Liu, Yongjoo Park

Existing learned indexes (e.g., RMI, ALEX, PGM) optimize the internal regressor of each node, not the overall structure such as index height, the size of each layer, etc. In this paper, we share our recent findings that we can achieve significantly faster lookup speed by optimizing the structure as well as internal regressors. Specifically, our approach (cal

Mohammad Hashemi, Steffi Roy, Fatemeh Ganji, Domenic Forte

The complexity of modern integrated circuits (ICs) necessitates collaboration between multiple distrusting parties, including thirdparty intellectual property (3PIP) vendors, design houses, CAD/EDA tool vendors, and foundries, which jeopardizes confidentiality and integrity of each party's IP. IP protection standards and the existing techniques proposed by r

Pokou Nagacy, Justin Feuto, Berenger Akon Kpata

We establish some new properties of the Dunkl-Wiener amalgam spaces defined on the real line. These results allow us to obtain the boundedness of Dunkl-type fractional integral and fractional maximal operators in the Dunkl-Fofana spaces.

B. A. Nizamov, M. S. Pshirkov

High-energy radiation of young pulsar wind nebulae (PWNe) is known to be variable. This is most prominently exemplified by the Crab nebula which can undergo both rapid brightenings and dimmings. Two pulsars in the Large Magellanic Cloud, PSR J0540-6919 and PSR J0537-6910 are evolutionally very close to Crab, so one may expect the same kind of variability fro

Feixiang Zhou, Xinyu Yang, Fang Chen, Long Chen

Automated social behaviour analysis of mice has become an increasingly popular research area in behavioural neuroscience. Recently, pose information (i.e., locations of keypoints or skeleton) has been used to interpret social behaviours of mice. Nevertheless, effective encoding and decoding of social interaction information underlying the keypoints of mice h

Leonid V. Kovalev

The standard arithmetic measures of center, the mean and median, have natural topological counterparts which have been widely used in continuum theory. In the context of metric spaces it is natural to consider the Lipschitz continuous versions of the mean and median. We show that they are related to familiar concepts of the geometry of metric spaces: the bou

Dusko Pavlovic

This is a draft of the textbook/monograph that presents computability theory using string diagrams. The introductory chapters have been taught as graduate and undergraduate courses and evolved through 8 years of lecture notes. The later chapters contain new ideas and results about categorical computability and some first steps into computable category theory

Sandeep Kumar Acharya, Jiten Dhandha, Jens Chluba

The excess radio background seen at $\simeq 0.1-10\,{\rm GHz}$ has stimulated much scientific debate in the past years. Recently, it was pointed out that the soft photon emission from accreting primordial black holes may be able to explain this signal. We show that the expected ultraviolet photon emission from these accreting black holes would ionize the uni

Francetic Igor

Selection on moral hazard represents the tendency to select a specific health insurance coverage depending on the heterogeneity in utilisation ''slopes''. I use data from the Swiss Household Panel and from publicly available regulatory data to explore the extent of selection on slopes in the Swiss managed competition system. I estimate responses in terms of

Chang-An Li

We study the topological properties of the generalized two-dimensional (2D) Su-Schrieffer-Heeger (SSH) models. We show that a pair of Dirac points appear in the Brillouin zone (BZ), consisting a semimetallic phase. Interestingly, the locations of these Dirac points are not pinned to any high-symmetry points of the BZ but tunable by model parameters. Moreover

Tatiana Vybostokova, Michal Svanda

The induction of electric currents in electric power distribution networks is a well-known effect of Earth-directed eruptive events. Inspired by recent studies showing that the rate of power-grid anomalies may increase after exposure to strong geomagnetically induced currents in mid-latitude countries in the middle of Europe, we decided to investigate such e

Siyan Li, Ashwin Paranjape, Christopher D. Manning

Current spoken dialogue systems initiate their turns after a long period of silence (700-1000ms), which leads to little real-time feedback, sluggish responses, and an overall stilted conversational flow. Humans typically respond within 200ms and successfully predicting initiation points in advance would allow spoken dialogue agents to do the same. In this wo

Sally Dong, Haotian Jiang, Yin Tat Lee, Swati Padmanabhan

Many fundamental problems in machine learning can be formulated by the convex program \[ \min_{\theta\in R^d}\ \sum_{i=1}^{n}f_{i}(\theta), \] where each $f_i$ is a convex, Lipschitz function supported on a subset of $d_i$ coordinates of $\theta$. One common approach to this problem, exemplified by stochastic gradient descent, involves sampling one $f_i$ ter

Lisa Hellerstein, Devorah Kletenik, Naifeng Liu, R. Teal Witter

We consider the Stochastic Boolean Function Evaluation (SBFE) problem where the task is to efficiently evaluate a known Boolean function $f$ on an unknown bit string $x$ of length $n$. We determine $f(x)$ by sequentially testing the variables of $x$, each of which is associated with a cost of testing and an independent probability of being true. If a strateg

Pengyu Liu, Jie Jian

Social networks play an important role in analyzing the impact of individual-level interactions on societal or economic outcomes. We model interactive decision making for a community of individuals with different traits, represented by a social network with trait-attributed nodes. We develop a deterministic process generating a sequence of choices for each i

Yawen Wu, Dewen Zeng, Zhepeng Wang, Yiyu Shi

Supervised deep learning needs a large amount of labeled data to achieve high performance. However, in medical imaging analysis, each site may only have a limited amount of data and labels, which makes learning ineffective. Federated learning (FL) can learn a shared model from decentralized data. But traditional FL requires fully-labeled data for training, w

Srimanta Mitra, Aquil Ahmad, Sajib Biswas, Amal Kumar Das

Random forest (RF) regression model is used to predict the lattice constant, magnetic moment and formation energies of full Heusler alloys, half Heusler alloys, inverse Heusler alloys and quaternary Heusler alloys based on existing as well as indigenously prepared databases. Prior analysis was carried out to check the distribution of the data points of the r

Kariane Calta, Cor Kraaikamp, Thomas A. Schmidt

We give two results for deducing dynamical properties of piecewise M\"obius interval maps from their related planar extensions. First, eventual expansivity and the existence of an ergodic invariant probability measure equivalent to Lebesgue measure both follow from mild finiteness conditions on the planar extension along with a new property ``bounded non-ful

Marzieh Arasteh, Narges Yarahmadi Gharaei, Mehrdad Ardebilipour

Cellular communication is a widely used technology in the world where the coverage area is divided into multiple cells. Interference is one of the most important challenges in cellular networks which causes problems by reducing the quality of the service. Cell-Free (CF) massive multiple-input multiple-output (MIMO) is a novel technolgy in which a large numbe

Xi Jia, Joseph Bartlett, Tianyang Zhang, Wenqi Lu

Due to their extreme long-range modeling capability, vision transformer-based networks have become increasingly popular in deformable image registration. We believe, however, that the receptive field of a 5-layer convolutional U-Net is sufficient to capture accurate deformations without needing long-range dependencies. The purpose of this study is therefore

Mohammad Hashemi, Steffi Roy, Domenic Forte, Fatemeh Ganji

Recent work has highlighted the risks of intellectual property (IP) piracy of deep learning (DL) models from the side-channel leakage of DL hardware accelerators. In response, to provide side-channel leakage resiliency to DL hardware accelerators, several approaches have been proposed, mainly borrowed from the methodologies devised for cryptographic implemen

Eugene A. Feinberg, Pavlo O. Kasyanov, Johannes O. Royset

For expectation functions on metric spaces, we provide sufficient conditions for epi-convergence under varying probability measures and integrands, and examine applications in the area of sieve estimators, mollifier smoothing, PDE-constrained optimization, and stochastic optimization with expectation constraints. As a stepping stone to epi-convergence of ind

Martin Nisser, Yashaswini Makaram, Lucian Covarrubias, Amadou Bah

In this paper, we present Mixels, programmable magnetic pixels that can be rapidly fabricated using an electromagnetic printhead mounted on an off-the-shelve 3-axis CNC machine. The ability to program magnetic material pixel-wise with varying magnetic force enables Mixels to create new tangible, tactile, and haptic interfaces. To facilitate the creation of i

Nicolas Nagel

The Union Closed Sets Conjecture states that in every finite, nontrivial set family closed under taking unions there is an element contained in at least half of all the sets of the family. We investigate two new directions with respect to the conjecture. Firstly, we investigate the frequencies of all elements among a union closed family and pose a question g

Sudip Mukherjee, Abhik Basu

We present the general theory of Ising transitions in isotropic elastic media with vanishing thermal expansion. By constructing a minimal model with appropriate spin-lattice couplings, we show that in two dimensions near a continuous transition the elasticity is anomalous in unusual ways: the system either significantly stiffens with a hitherto unknown uniqu

Varun Kulkarni, Suhas Tamvada, Nikhil Shirdade, Navid Saneie

The splat formed after drop impact on supercooled solid surfaces sticks to it. On the contrary, a sublimating supercooled surface such as dry ice inhibits pinning and therefore efficiently rebounds drops made of a variety of liquids. While rebound is expected at lower impact velocities on dry ice, at higher impact velocities the drop fragments leaving behind

Patrícia Carvalho, Cristian Landri, Ravi Mistry, Aleksandr Pinzul

Motivated in part by the bi-gravity approach to massive gravity, we introduce and study the multimetric Finsler geometry. For the case of an arbitrary number of dimensions, we study some general properties of the geometry in terms of its Riemannian ingredients, while in the 2-dimensional case, we derive all the Cartan equations as well as explicitly find the

Martin Nisser, Yashaswini Makaram, Faraz Faruqi, Ryo Suzuki

This paper introduces a method to generate highly selective encodings that can be magnetically "programmed" onto physical modules to enable them to self-assemble in chosen configurations. We generate these encodings based on Hadamard matrices, and show how to design the faces of modules to be maximally attractive to their intended mate, while remaining maxim

Walid R. Ghanem, Vahid Jamali, Malte Schellmann, Hanwen Cao

This paper investigates the resource allocation algorithm design for wireless systems assisted by large intelligent reflecting surfaces (IRSs) with coexisting enhanced mobile broadband (eMBB) and ultra reliable low-latency communication (URLLC) users. We consider a two-time scale resource allocation scheme, whereby the base station's precoders are optimized

Mohamed ElKabbash

Radiative cooling emerged as a possible sustainable solution to the energy hungry vapor compression-based cooling. However, realizing subfreezing temperatures through radiative cooling remains challenging in environments with high humidity and often requires extreme heat management, e.g., by placing the thermal emitter in ultrahigh vacuum conditions. This wo

Adar Kahana, Symeon Papadimitropoulos, Eli Turkel, Dmitry Batenkov

Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit, preventing distinction of sources separated by less than the emitted wavelength. In this work we propose a method based on physically-informed neural-networks for solving the sourc

Mansooreh Karami, Ahmadreza Mosallanezhad, Paras Sheth, Huan Liu

Online Social Networks (OSNs) facilitate access to a variety of data allowing researchers to analyze users' behavior and develop user behavioral analysis models. These models rely heavily on the observed data which is usually biased due to the participation inequality. This inequality consists of three groups of online users: the lurkers - users that solely

Stian Rørheim

Rock properties are environment- and condition-dependent which render field-laboratory comparisons ambiguous for a number of known and unknown reasons that constitute the upscaling problem. Unknowns are first transformed into knowns in a controlled environment (laboratory) and second in a volatile environment (field). Causality-bound dispersion and attenuati

Zhenghuan Gao, Xi-Nan Ma, Dekai Zhang

In this paper, we consider the homogeneous complex k-Hessian equation in an exterior domain $\mathbb{C}^n\setminus\Omega$. We prove the existence and uniqueness of the $C^{1,1}$ solution by constructing approximating solutions. The key point for us is to establish the uniform gradient estimate and the second order estimate.