August 2022 arXiv papers — page 123

Wentao Kang, Guijun Zhang, Xiao Fu

Named Entity Recognition (NER) is an important task in natural language processing. However, traditional supervised NER requires large-scale annotated datasets. Distantly supervision is proposed to alleviate the massive demand for datasets, but datasets constructed in this way are extremely noisy and have a serious unlabeled entity problem. The cross entropy

Song Jiang, Fabrice Scheurer, Qiang Sun, Pascal Ruffieux

Atomically precise graphene nanoribbons (GNRs) have emerged as promising candidates for nanoelectronic applications due to their widely tunable energy band gaps resulting from lateral quantum confinement and edge effects. Here we report on the electronic transport characterization of an edge-modified GNR suspended between the tip of a scanning tunneling micr

Ivan Dneprov, Maxim Grigoriev

We elaborate on the presymplectic BV-AKSZ approach to local gauge theories and apply it to conformal gravity. More specifically, we identify a compatible presymplectic structure on the minimal model of the total BRST complex of this theory and show that together with the BRST differential it determines a full-scale BV formulation for a specific frame-like ac

Yilei Zeng, Jiali Duan, Yang Li, Emilio Ferrara

Human-centered AI considers human experiences with AI performance. While abundant research has been helping AI achieve superhuman performance either by fully automatic or weak supervision learning, fewer endeavors are experimenting with how AI can tailor to humans' preferred skill level given fine-grained input. In this work, we guide the curriculum reinforc

Yuxiao Huang, Yan Ma

A key challenge in Machine Learning is class imbalance, where the sample size of some classes (majority classes) are much higher than that of the other classes (minority classes). If we were to train a classifier directly on imbalanced data, it is more likely for the classifier to predict a new sample as one of the majority classes. In the extreme case, the

Elias Andrade, Ramon Carrillo-Bastos, Mahmoud M. Asmar, Gerardo G. Naumis

In graphene, a Kekul\'e-Y bond texture modifies the electronic band structure generating two concentric Dirac cones with different Fermi velocities lying in the {\Gamma}-point in reciprocal space. The energy dispersion results in different group velocities for each isospin component at a given energy. This energy spectrum combined with the negative refractio

C. Reichhardt, C. J. O. Reichhardt

We consider the driven dynamics of Wigner crystals interacting with random disorder. Using numerical simulations, we find a rich variety of transport phenomena as a function of charge density, drive, and pinning strength. For weak pinning, the system forms a defect free crystal that depins elastically. When the pinning is stronger, a pinned glass phase appea

Haruhisa Enomoto, Shunya Saito

We study the Grothendieck monoid (a monoid version of the Grothendieck group) of an extriangulated category, and give some results which are new even for abelian categories. First, we classify Serre subcategories and dense 2-out-of-3 subcategories using the Grothendieck monoid. Second, in good situations, we show that the Grothendieck monoid of the localizat

Marissa Walker, Vijay Varma, Geoffrey Lovelace, Mark A. Scheel

Numerical relativity (NR) simulations of binary black hole (BBH) systems provide the most accurate gravitational wave predictions, but at a high computational cost -- especially when the black holes have nearly extremal spins (i.e. spins near the theoretical upper limit) or very unequal masses. Recently, the technique of Reduced Order Modeling (ROM) has enab

Hossein Mirzaee, Hamed Samarghandi, Keith Willoughby

Due to increasing air pollution, which is a consequence of the environmental effects of production in various industries, green supply chain management (GSCM) has attracted the attention of both scholars and practitioners. Green supplier selection is one of the most important problems in GSCM, which satisfies a firm's environmental goals as well as its econo

Matteo Barigozzi, Giuseppe Cavaliere, Graziano Moramarco

We propose a factor network autoregressive (FNAR) model for time series with complex network structures. The coefficients of the model reflect many different types of connections between economic agents ("multilayer network"), which are summarized into a smaller number of network matrices ("network factors") through a novel tensor-based principal component a

Wali Ullah Khan, Zain Ali, Eva Lagunas, Symeon Chatzinotas

LEO satellite communication has drawn particular attention recently due to its high data rate services and low round-trip latency. It is low-cost to launch and can provide global coverage. However, the spectrum scarcity might be one of the critical challenges in the growth of LEO satellites, impacting severe restrictions on the development of ground-space in

Naritaka Oshita

We find a significant destructive interference among Kerr overtones in the early ringdown induced by an extreme mass-ratio merger of a massive black hole and a compact object, and that the ringdown spectrum apparently follows the Fermi-Dirac distribution. We numerically compute the spectral amplitude of gravitational waves induced by a particle plunging into

Yi-Wei Chen, Chi Wang, Amin Saied, Rui Zhuang

Deploying machine learning models requires high model quality and needs to comply with application constraints. That motivates hyperparameter optimization (HPO) to tune model configurations under deployment constraints. The constraints often require additional computation cost to evaluate, and training ineligible configurations can waste a large amount of tu

Raiha Browning, Judith Rousseau, Kerrie Mengersen

Hawkes processes are a self-exciting stochastic process used to describe phenomena whereby past events increase the probability of the occurrence of future events. This work presents a flexible approach for modelling a variant of these, namely discrete-time Hawkes processes. Most standard models of Hawkes processes rely on a parametric form for the function

Franck Cassez, Joanne Fuller, Horacio Mijail Anton Quiles

We present a methodology to develop verified smart contracts. We write smart contracts, their specifications and implementations in the verification-friendly language Dafny. In our methodology the ability to write specifications, implementations and to reason about correctness is a primary concern. We propose a simple, concise yet powerful solution to reason

Samuel Baugh, Karen McKinnon

Regression-based optimal fingerprinting techniques for climate change detection and attribution require the estimation of the forced signal as well as the internal variability covariance matrix in order to distinguish between their influences in the observational record. While previously developed approaches have taken into account the uncertainty linked to

Mark S. Bandstra, Daniel Hellfeld, Jaewon Lee, Brian J. Quiter

The ability to formulate maps of minimum detectable activities (MDAs) that describe the sensitivity of an ad hoc measurement that used one or more freely moving radiation detector systems would be significantly beneficial for the conduct and understanding of many radiological search activities. In a real-time scenario with a free-moving detector system, an M

Arthur Bucker, Luis Figueredo, Sami Haddadin, Ashish Kapoor

Natural language is one of the most intuitive ways to express human intent. However, translating instructions and commands towards robotic motion generation and deployment in the real world is far from being an easy task. The challenge of combining a robot's inherent low-level geometric and kinodynamic constraints with a human's high-level semantic instructi

Ethan Witwer, James Holland, Nicholas Hopper

Website fingerprinting is an attack that uses size and timing characteristics of encrypted downloads to identify targeted websites. Since this can defeat the privacy goals of anonymity networks such as Tor, many algorithms to defend against this attack in Tor have been proposed in the literature. These algorithms typically consist of some combination of the

Sheldon Dantas, Rubén Medina, Andrés Quilis, Óscar Roldán

In this paper, we provide an infinite metric space $M$ such that the set $\mbox{SNA}(M)$ of strongly norm-attaining Lipschitz functions does not contain a subspace which is isometric to $c_0$. This answers a question posed by Antonio Avil\'es, Gonzalo Mart\'inez Cervantes, Abraham Rueda Zoca, and Pedro Tradacete. On the other hand, we prove that $\mbox{SNA}(

Feng-Wu Chen, Zheng-Han Huang, Yu-Shu G. Wu

Valleytronics in 2D materials - primarily graphene and transition metal dichalcogenides is rooted in the existence of valley flavor but extends far out to the rich dimension of local physics, as reviewed, extensively studied and demonstrated in this work, in terms of a local, Ginzburg-Landau order parameter type field - valley field. A theoretical framework

Tan Zhi-Xuan, Nishad Gothoskar, Falk Pollok, Dan Gutfreund

To facilitate the development of new models to bridge the gap between machine and human social intelligence, the recently proposed Baby Intuitions Benchmark (arXiv:2102.11938) provides a suite of tasks designed to evaluate commonsense reasoning about agents' goals and actions that even young infants exhibit. Here we present a principled Bayesian solution to

Joshua Zahl

We prove a conjecture of D. Oberlin on the dimension of unions of lines in $\mathbb{R}^n$. If $d \geq 1$ is an integer, $0 \leq \beta \leq 1$, and $L$ is a set of lines in $\mathbb{R}^n$ with Hausdorff dimension at least $2(d-1) + \beta$, then the union of the lines in $L$ has Hausdorff dimension at least $d + \beta$. Our proof combines a refined version of

Yang Nan, Peng Tang, Guyue Zhang, Caihong Zeng

Tissue segmentation is the mainstay of pathological examination, whereas the manual delineation is unduly burdensome. To assist this time-consuming and subjective manual step, researchers have devised methods to automatically segment structures in pathological images. Recently, automated machine and deep learning based methods dominate tissue segmentation re

Jianwei Urbain Yang

We prove $\mathcal{H}^{\alpha_1}\times\mathcal{H}^{\alpha_2}\to L^q_tL^r_x$ null form estimates for solutions to homogeneous wave equations with $(q,r)$ on the endline of the condition concerning geometry of the cone, except the critical index. This extends the previous endpoint result of Tao, Math. Z. 238, no. 2, 215-268, (2001) in symmetric norms to mixed

Shiyi Wang, Guang Yang

Medical image classification and segmentation based on deep learning (DL) are emergency research topics for diagnosing variant viruses of the current COVID-19 situation. In COVID-19 computed tomography (CT) images of the lungs, ground glass turbidity is the most common finding that requires specialist diagnosis. Based on this situation, some researchers prop

Sarah E. Spielman, Alicia Handian, Nina P. Inman, Thomas J. Carroll

We simulate the dynamics of Rydberg atoms resonantly exchanging energy via two-, three-, and four-body dipole-dipole interactions in a one-dimensional array. Using simplified models of a realistic experimental system, we study the initial state survival probability, mean level spacing, spread of entanglement, and properties of the energy eigenstates. By expl

Aloni Cohen, Sarah Scheffler, Mayank Varia

If a court knows that a respondent knows the password to a device, can the court compel the respondent to enter that password into the device? In this work, we propose a new approach to the foregone conclusion doctrine from Fisher v US that governs the answer to this question. The Holy Grail of this line of work would be a framework for reasoning about wheth

Anton Bernshteyn

This is a draft of an article to appear in the October 2022 issue of the Notices of the AMS. In this survey article we explore a fascinating area called descriptive combinatorics and its recently discovered connections to distributed algorithms -- a fundamental part of computer science that is becoming increasingly important in the modern era of decentralize

David H. Wolpert

The past two decades have seen a revolution in statistical physics, generalizing it to apply to systems of arbitrary size, evolving while arbitrarily far from equilibrium. Many of these new results are based on analyzing the dynamics of the entropy of a system that is evolving according to a Markov process. These results comprise a sub-field called ``stochas

Bingde Liu, John Cartlidge

We approach the problem of designing an automated trading strategy that can consistently profit by adapting to changing market conditions. This challenge can be framed as a Nonstationary Continuum-Armed Bandit (NCAB) problem. To solve the NCAB problem, we propose PRBO, a novel trading algorithm that uses Bayesian optimization and a ``bandit-over-bandit'' fra

Marshall Rawson, Michael Rawson

Concurrent programming is used in all large and complex computer systems. However, concurrency errors and system failures (ex: crashes and deadlocks) are common. We find that Petri nets can be used to model concurrent systems and find and remove errors ahead of time. We introduce a novel generalization of Petri nets with nondeterministic transition nodes to

Jayson R. Vavrek, C. Corey Hines, Mark S. Bandstra, Daniel Hellfeld

We demonstrate a method for using arrays of point sources that emulate -- when measured from a standoff of at least several meters -- distributed gamma-ray sources, and present results using this method from outdoor aerial measurements of several planar arrays each comprising up to $100$ ${\sim}7$ mCi Cu-64 sealed sources. The method relies on the Poisson de

Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu

Hyperparameter optimization (HPO) is a well-studied research field. However, the effects and interactions of the components in an HPO pipeline are not yet well investigated. Then, we ask ourselves: can the landscape of HPO be biased by the pipeline used to evaluate individual configurations? To address this question, we proposed to analyze the effect of the

Cormac O'Sullivan

A conjectured relation between Ramanujan's asymptotic approximations to the exponential function and the exponential integral is established. The proof involves Stirling numbers, second-order Eulerian numbers, modifications of both of these, and Stirling's approximation to the gamma function. Our work provides new information about the coefficients in Stirli

Panagiotis Tolias, Marco De Angeli, Dario Ripamonti, Svetlana Ratynskaia

Dust-wall high speed impacts, triggered by the termination of runaway electrons on plasma facing components, constitute a source of erosion. Normal high velocity mechanical impacts of tungsten dust on bulk tungsten plates are reproduced in a controlled manner by light gas gun shooting systems. Post-mortem surface analysis revealed that three erosion regimes

Neha Hulkund, Nicolo Fusi, Jennifer Wortman Vaughan, David Alvarez-Melis

We propose a method to identify and characterize distribution shifts in classification datasets based on optimal transport. It allows the user to identify the extent to which each class is affected by the shift, and retrieves corresponding pairs of samples to provide insights on its nature. We illustrate its use on synthetic and natural shift examples. While

S. Mazdak Abulnaga, Sean I. Young, Katherine Hobgood, Eileen Pan

Blood oxygen level dependent (BOLD) MRI with maternal hyperoxia can assess oxygen transport within the placenta and has emerged as a promising tool to study placental function. Measuring signal changes over time requires segmenting the placenta in each volume of the time series. Due to the large number of volumes in the BOLD time series, existing studies rel

Zhipeng Du, Miaojing Shi, Jiankang Deng, Stefanos Zafeiriou

Perspective distortions and crowd variations make crowd counting a challenging task in computer vision. To tackle it, many previous works have used multi-scale architecture in deep neural networks (DNNs). Multi-scale branches can be either directly merged (e.g. by concatenation) or merged through the guidance of proxies (e.g. attentions) in the DNNs. Despite

Pedro Ripper, Gustavo Amaral, Guilherme Temporão

Quantum Computing has been presenting major developments in the last few years, unveiling systems with a increasing number of qubits. However, unreliable quantum processes in universal quantum computers still represent one of the the greatest challenges to be overcome. Such obstacle has its source on noisy operations and interactions with the environment whi

Julian Kates-Harbeck, Martin A. Nowak

In social systems subject to indirect reciprocity, a positive reputation is key for increasing one's likelihood of future positive interactions. The flow of gossip can amplify the impact of a person's actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem. To quantify this notion, we cal

Mohamed Jebalia, Abderrazek Karoui

In this work, we construct a stable and fairly fast estimator for solving non-parametric multidimensional regression problems. The proposed estimator is based on the use of multivariate Jacobi polynomials that generate a basis for a reduced size of $d-$variate finite dimensional polynomial space. An ANOVA decomposition trick has been used for building this l

Lan Luo, Jingshen Wang, Emily C. Hector

Modern longitudinal data, for example from wearable devices, measures biological signals on a fixed set of participants at a diverging number of time points. Traditional statistical methods are not equipped to handle the computational burden of repeatedly analyzing the cumulatively growing dataset each time new data is collected. We propose a new estimation

S. Ganguly

The Muon Campus at Fermilab provides world class accelerator infrastructure supporting the next generation intensity frontier experiments. The anti-proton source from the Tevatron era was converted to the present day Muon Campus at the end of the collider program in 2011. Currently, the Muon Campus delivers highly polarized muon beams to the Muon g-2 experim

Matteo Polettini, Izaak Neri

For continuous-time Markov chains we prove that, depending on the notion of effective affinity $F$, the probability of an edge current to ever become negative is either $1$ if $F< 0$ else $\sim \exp - F$. The result generalizes a ``noria'' formula to multicyclic networks. We give operational insights on the effective affinity and compare several estimators,

Dongwook Lim, Andreas J. Koch-Hansen, Sang-Hyun Chun, Seungsoo Hong

Globular clusters (GCs) play an important role in the formation and evolution of the Milky Way. New candidates are continuously found, particularly in the high-extinction low-latitude regions of the bulge, although their existence and properties have yet to be verified. In order to investigate the new GC candidates, we performed high-resolution NIR spectrosc

Zachary Grey, Olga Doronina, Andrew Glaws

Airfoil shape design is a classical problem in engineering and manufacturing. In this work, we combine principled physics-based considerations for the shape design problem with modern computational techniques using a data-driven approach. Modern and traditional analyses of 2D and 3D aerodynamic shapes reveal a flow-based sensitivity to specific deformations

Zhiyu Lin, Rohan Agarwal, Mark Riedl

Recent neural generation systems have demonstrated the potential for procedurally generating game content, images, stories, and more. However, most neural generation algorithms are "uncontrolled" in the sense that the user has little say in creative decisions beyond the initial prompt specification. Co-creative, mixed-initiative systems require user-centric

Zilin Si, Zirui Zhu, Arpit Agarwal, Stuart Anderson

Robot simulation has been an essential tool for data-driven manipulation tasks. However, most existing simulation frameworks lack either efficient and accurate models of physical interactions with tactile sensors or realistic tactile simulation. This makes the sim-to-real transfer for tactile-based manipulation tasks still challenging. In this work, we integ

Nicolaas Kaashoek, Robert Morris

CheckSync provides applications with high availability via runtime-integrated checkpointing. This allows CheckSync to take checkpoints of a process running in a memory-managed language (Go, for now), which can be resumed on another machine after a failure. CheckSync uses the runtime to checkpoint only the process' live memory, doing without requiring signifi

Joshua Hovanes, Yadi Zhong, Ujjwal Guin

Data recovery has long been a focus of the electronics industry for decades by security experts, focusing on hard disk recovery, a type of non-volatile memory. Unfortunately, none of the existing research, neither from academia, industry, or government, have ever considered data recovery from volatile memories. The data is lost when it is powered off, by def

Philippe Lewalle, K. Birgitta Whaley

Open-system quantum dynamics described by non-Hermitian effective Hamiltonians have become a subject of considerable interest. Studies of non-Hermitian physics have revealed general principles, including relationships between the topology of the complex eigenvalue space and the breakdown of adiabatic control strategies. We study here the control of a single

Minoo Jafarlou, Omid Mahdi Ebadati E., Hassan Naderi

The requirement to trace and process moving objects in the contemporary era gradually increases since numerous applications quickly demand precise moving object locations. The Map-matching method is employed as a preprocessing technique, which matches a moving object point on a corresponding road. However, most of the GPS trajectory datasets include stay-poi

Jindi Wu, Zeyi Tao, Qun Li

Many recent machine learning tasks resort to quantum computing to improve classification accuracy and training efficiency by taking advantage of quantum mechanics, known as quantum machine learning (QML). The variational quantum circuit (VQC) is frequently utilized to build a quantum neural network (QNN), which is a counterpart to the conventional neural net

Jing An, Christopher Henderson, Lenya Ryzhik

We uncover a seemingly previously unnoticed algebraic structure of a large class of reaction-diffusion equations and use it, in particular, to study the long time behavior of the solutions and their convergence to traveling waves in the pulled and pushed regimes, as well as at the pushmi-pullyu boundary. One such new object introduced in this paper is the sh

Wenxuan Wu, Li Fuxin, Qi Shan

We introduce PointConvFormer, a novel building block for point cloud based deep network architectures. Inspired by generalization theory, PointConvFormer combines ideas from point convolution, where filter weights are only based on relative position, and Transformers which utilize feature-based attention. In PointConvFormer, attention computed from feature d

Fan Yang, Qizhang Feng, Kaixiong Zhou, Jiahao Chen

Counterfactual, serving as one emerging type of model explanation, has attracted tons of attentions recently from both industry and academia. Different from the conventional feature-based explanations (e.g., attributions), counterfactuals are a series of hypothetical samples which can flip model decisions with minimal perturbations on queries. Given valid co

Steven J. Murdoch, Aydin Abadi

Two-factor authentication (2FA) schemes that rely on a combination of knowledge factors (e.g., PIN) and device possession have gained popularity. Some of these schemes remain secure even against strong adversaries that (a) observe the traffic between a client and server, and (b) have physical access to the client's device, or its PIN, or breach the server. H

Abílio Lemos, Victor Neumann, Sávio Ribas

In this paper, we explore the existence of $m$-terms arithmetic progressions in $\mathbb{F}_{q^n}$ with a given common difference whose terms are all primitive elements, and at least one of them is normal. We obtain asymptotic results for $m \ge 4$ and concrete results for $m \in \{2,3\}$, where the complete list of exceptions when the common difference belo

Pejman Shamsipour, Tedd Kourkounakis, Amin Aghaee, Rouzbeh Meshkinnejad

Stochastic and conditional simulation methods have been effective towards producing realistic realizations and simulations of spatial numerical models that share equal probability of occurrence. Application of these methods are valuable throughout the domain of earth science for their ability to simulate sampled study data. Such stochastic methods have also

Matthew Kwan, Ashwin Sah, Lisa Sauermann, Mehtaab Sawhney

An $n$-vertex graph is called $C$-Ramsey if it has no clique or independent set of size $C\log_2 n$ (i.e., if it has near-optimal Ramsey behavior). In this paper, we study edge-statistics in Ramsey graphs, in particular obtaining very precise control of the distribution of the number of edges in a random vertex subset of a $C$-Ramsey graph. This brings toget

Sonia Martin, Simona Onori, Ram Rajagopal

Battery energy storage systems (BESSs) provide many benefits to the electricity grid, including stability, backup power, and flexibility in introducing more clean energy sources. As BESS penetration grows, knowledge of the uncertainty in the battery's state of charge (SOC) estimate is crucial for planning optimal BESS power injection trajectories. This paper

I. V. Lukin, A. G. Sotnikov

We develop the continuous matrix-product states approach for description of inhomogeneous one-dimensional quantum systems with long-range interactions. The method is applied to the exactly-solvable Calogero-Moser model. We show the high accuracy of reproducing the ground-state properties of the many-body system and discuss potential errors that can originate

Sergey A. Khaibrakhmanov, Alexander E. Dudorov

We investigate the dynamics of the accretion disks of young stars with fossil large-scale magnetic field. The author's magnetohydrodynamic (MHD) model of the accretion disks is generalized to consider the dynamical influence of the magnetic field on gas rotation speed and vertical structure of the disks. With the help of the developed MHD model, the structur

Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li

Probability calibration for deep models is highly desirable in safety-critical applications such as medical imaging. It makes output probabilities of deep networks interpretable, by aligning prediction probability with the actual accuracy in test data. In image segmentation, well-calibrated probabilities allow radiologists to identify regions where model-pre

Chanon Thongprayoon, Lorenzo Livi, Naoki Masuda

Temporal network data are increasingly available in various domains, and often represent highly complex systems with intricate structural and temporal evolutions. Due to the difficulty of processing such complex data, it may be useful to coarse grain temporal network data into a numeric trajectory embedded in a low-dimensional space. We refer to such a proce

Lilas Alrahis, Johann Knechtel, Florian Klemme, Hussam Amrouch

Process variations and device aging impose profound challenges for circuit designers. Without a precise understanding of the impact of variations on the delay of circuit paths, guardbands, which keep timing violations at bay, cannot be correctly estimated. This problem is exacerbated for advanced technology nodes, where transistor dimensions reach atomic lev

Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu

Spatial optimization problems (SOPs) are characterized by spatial relationships governing the decision variables, objectives, and/or constraint functions. In this article, we focus on a specific type of SOP called spatial partitioning, which is a combinatorial problem due to the presence of discrete spatial units. Exact optimization methods do not scale with

Shuo Liu, Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang

Discrete time crystal (DTC) has recently attracted increasing attention, but most DTC models and their properties are only revealed after disorder average. In this Letter, we propose a simple disorder-free periodically driven model that exhibits nontrivial DTC order stabilized by Stark many-body localization (MBL). We demonstrate the existence of DTC phase b

Michael Xu, Abinash Kumar, James M. LeBeau

Here, we report a case study implementation of reinforcement learning (RL) to automate operations in the scanning transmission electron microscopy (STEM) workflow. To do so, we design a virtual, prototypical RL environment to test and develop a network to autonomously align the electron beam without prior knowledge. Using this simulator, we evaluate the impa

Tiemo Pedergnana, Nicolas Noiray

Systems governed by a multivariate Langevin equation featuring an exact potential exhibit straightforward dynamics but are often difficult to recognize because, after a general coordinate change, the gradient flow becomes obscured by the Jacobian matrix of the mapping. In this work, a detailed analysis of the transformation properties of Langevin equations u

Claudio D. Mello, Bryan U. Moreira, Paulo J. O. Evald, Paulo L. Drews

Images acquired during underwater activities suffer from environmental properties of the water, such as turbidity and light attenuation. These phenomena cause color distortion, blurring, and contrast reduction. In addition, irregular ambient light distribution causes color channel unbalance and regions with high-intensity pixels. Recent works related to unde

Julian Kates-Harbeck, Michael M. Desai

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals' affected neighbors, such a spreading process becomes a "complex contagion". This non-linearity does not typically appear with physically spreading infections, but instead can emerge wh

Matteo Messa, Miroslava Dessauges-Zavadsky, Johan Richard, Angela Adamo

We study the population of star-forming clumps in A521-sys1, a $\rm z=1.04$ system gravitationally lensed by the foreground ($\rm z=0.25$) cluster Abell 0521. The galaxy presents one complete counter--image with a mean magnification of $\rm \mu\sim4$ and a wide arc containing two partial images of A521-sys1 with magnifications reaching $\rm \mu>20$, allowing

Anita Dürr

In a recent breakthrough paper, Chi et al. (STOC'22) introduce an $\tilde{O}(n^{\frac{3 + \omega}{2}})$ time algorithm to compute Monotone Min-Plus Product between two square matrices of dimensions $n \times n$ and entries bounded by $O(n)$. This greatly improves upon the previous $\tilde O(n^{\frac{12 + \omega}{5}})$ time algorithm and as a consequence impr

Jiahui Zhang, Fangneng Zhan, Yingchen Yu, Rongliang Wu

Recently, single image super-resolution (SR) under large scaling factors has witnessed impressive progress by introducing pre-trained generative adversarial networks (GANs) as priors. However, most GAN-Priors based SR methods are constrained by an attribute disentanglement problem in inverted latent codes which directly leads to mismatches of visual attribut

Torsten Böker, Yasin Abul-Huda, Martin Altenburg, Catarina Alves de Oliveira

The Near-Infrared Spectrograph (NIRSpec) is one of the four focal plane instruments on the James Webb Space Telescope which was launched on Dec. 25, 2021. We present an overview of the as-run NIRSpec commissioning campaign, with particular emphasis on the sequence of activities that led to the verification of all hardware components of NIRSpec. We also discu

Olga Kulikova

This paper describes some generalizations of the results presented in the book "Geometry of defining Relations in Groups" , of A.Yu.Ol'shanskii to the case of non-cyclic torsion-free hyperbolic groups. In particular, it is proved that for every non-cyclic torsion-free hyperbolic group, there exists a non-Abelian torsion-free quotient group in which all prope

Xingyu Lyu, Mengya Zhang, Xiaokuan Zhang, Jianyu Niu

Recently, Decentralized Finance (DeFi) platforms on Ethereum are booming, and numerous traders are trying to capitalize on the opportunity for maximizing their benefits by launching front-running attacks and extracting Miner Extractable Values (MEVs) based on information in the public mempool. To protect end users from being harmed and hide transactions from

Surudhi Asokraj, Tommaso Bianchi, Alessandro Brighente, Mauro Conti

Dynamic wireless power transfer provides means for charging Electric Vehicles (EVs) while driving, avoiding stopping for charging and hence fostering their widespread adoption. Researchers devoted much effort over the last decade to provide a reliable infrastructure for potential users to improve comfort and time management. Due to the severe security and pe

Farzaneh Esmaili, Mahdi Pourmirzaei, Shahin Ramazi, Seyedehsamaneh Shojaeilangari

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that occurs in most proteins and plays a significant role in many biological processes. Disorders in the phosphoryl

Adam Khakhar, Xi Chen

Liquidity Providers on Automated Market Makers generate millions of USD in transaction fees daily. However, the net value of a Liquidity Position is vulnerable to price changes in the underlying assets in the pool. The dominant measure of loss in a Liquidity Position is Impermanent Loss. Impermanent Loss for Constant Function Market Makers has been widely st

Satyavrat Wagle, Seyyedali Hosseinalipour, Naji Khosravan, Mung Chiang

Federated learning (FL) has been recognized as one of the most promising solutions for distributed machine learning (ML). In most of the current literature, FL has been studied for supervised ML tasks, in which edge devices collect labeled data. Nevertheless, in many applications, it is impractical to assume existence of labeled data across devices. To this

Sayan Banerjee, Amarjit Budhiraja

This article presents a review of some old and new results on the long time behavior of reflected diffusions. First, we present a summary of prior results on construction, ergodicity and geometric ergodicity of reflected diffusions in the positive orthant $\mathbb{R}^d_+$, $d \in \mathbb{N}$. The geometric ergodicity results, although very general, usually g

Max Silva-Feaver, Zeeshan Ahmed, Kam Arnold, Josef C. Frisch

A number of modern millimeter, sub-millimeter, and far-infrared detectors are read out using superconducting microwave (1-10GHz) resonators. The main detector technologies are Transition Edge Sensors, read out using Microwave SQUID Multiplexers ($\mu$mux) and Microwave Kinetic Inductance Detectors. In these readout schemes, sky signal is encoded as resonance

Fan Zhang

An approach for quantitatively evaluating overshooting oscillations is designed to characterize the performance of shock-capturing schemes. Specifically, following our previous work focused on cases with only discontinuities, now we account for the concurrent presences of discontinuities and smooth waves, each with a complete set of supported modes on a give

Mohamed Akrout, Hayet Amdouni, Amal Feriani, Monia Kourda

The evolution of behavior of dermatology patients has seen significantly accelerated change over the past decade, driven by surging availability and adoption of digital tools and platforms. Through our longitudinal analysis of this behavior within Tunisia over a 35-year time frame, we identify behavioral patterns across economic and cultural dimensions and h

Faris Almalik, Mohammad Yaqub, Karthik Nandakumar

Vision Transformers (ViT) are competing to replace Convolutional Neural Networks (CNN) for various computer vision tasks in medical imaging such as classification and segmentation. While the vulnerability of CNNs to adversarial attacks is a well-known problem, recent works have shown that ViTs are also susceptible to such attacks and suffer significant perfo

Esther Galby, Daniel Marx, Philipp Schepper, Roohani Sharma

The leafage of a chordal graph G is the minimum integer l such that G can be realized as an intersection graph of subtrees of a tree with l leaves. We consider structural parameterization by the leafage of classical domination and cut problems on chordal graphs. Fomin, Golovach, and Raymond [ESA 2018, Algorithmica 2020] proved, among other things, that Domin

Martina Petráková

This paper generalizes a recent existence result for infinite-volume marked Gibbs point processes. We try to use the existence theorem for two models from stochastic geometry. First, we show the existence of Gibbs facet processes in $\mathbb{R}^d$ with repulsive interactions. We also prove that the finite-volume Gibbs facet processes with attractive interact

Jordi Vila-Pérez, Matteo Giacomini, Antonio Huerta

Purpose: This study aims to assess the robustness and accuracy of the face-centred finite volume (FCFV) method for the simulation of compressible laminar flows in different regimes, using numerical benchmarks. Design/methodology/approach: The work presents a detailed comparison with reference solutions published in the literature -- when available -- and num

Michael Garstka, Mark Cannon, Paul Goulart

This paper describes the design of a safeguarding scheme for Anderson acceleration to improve its practical performance and stability when used for first-order optimisation methods. We show how the combination of a non-expansiveness condition, conditioning constraints, and memory restarts integrate well with solver algorithms that can be represented as fixed

Xuchen Wang, Mohammad Sajjad Mirmoosa, Viktar S. Asadchy, Carsten Rockstuhl

Photonic time crystals are artificial materials whose electromagnetic properties are uniform in space but periodically vary in time. The synthesis of such materials and experimental observation of their physics remain very challenging due to the stringent requirement for uniform modulation of material properties in volumetric samples. In this work, we extend

I. Gallardo Cava, V. Bujarrabal, J. Alcolea, M. Gómez-Garrido

There is a class of binary post-AGB stars (binary system including a post-AGB star) that are surrounded by Keplerian disks and outflows resulting from gas escaping from the disk. To date, there are seven sources that have been studied in detail through interferometric millimeter-wave maps of CO lines (ALMA/NOEMA). For the cases of the Red Rectangle, IW Carin

Qinhua Jenny Sun, Khuong Vo, Kitty Lui, Michael Nunez

Human decision making behavior is observed with choice-response time data during psychological experiments. Drift-diffusion models of this data consist of a Wiener first-passage time (WFPT) distribution and are described by cognitive parameters: drift rate, boundary separation, and starting point. These estimated parameters are of interest to neuroscientists

Dávid Guszejnov, Aman N. Raju, Stella S. R. Offner, Michael Y. Grudić

Most observed stars are part of a multiple star system, but the formation of such systems and the role of environment and various physical processes is still poorly understood. We present a suite of radiation-magnetohydrodynamic simulations of star-forming molecular clouds from the STARFORGE project that include stellar feedback with varied initial surface d

Subhankar Ghosh, Prasun Roy, Saumik Bhattacharya, Umapada Pal

Image colorization is a well-known problem in computer vision. However, due to the ill-posed nature of the task, image colorization is inherently challenging. Though several attempts have been made by researchers to make the colorization pipeline automatic, these processes often produce unrealistic results due to a lack of conditioning. In this work, we atte

Shira Faigenbaum-Golovin, Or Shimshi

Over the years, various algorithms were developed, attempting to imitate the Human Visual System (HVS), and evaluate the perceptual image quality. However, for certain image distortions, the functionality of the HVS continues to be an enigma, and echoing its behavior remains a challenge (especially for ill-defined distortions). In this paper, we learn to com

Niloofar Fadavi

Having fixed capacities, homogeneous products and price sensitive customer purchase decision are primary distinguishing characteristics of numerous revenue management systems. Even with two or three rivals, competition is still highly fierce. This paper studies sub-game perfect Nash equilibrium of a price competition in an oligopoly market with perishable as