August 2022 arXiv papers — page 22

Amir Youssefi, Shingo Kono, Mahdi Chegnizadeh, Tobias J. Kippenberg

An enduring challenge in constructing mechanical oscillator-based hybrid quantum systems is to ensure engineered coupling to an auxiliary degree of freedom while maintaining good mechanical isolation from the environment, that is, low quantum decoherence, consisting of thermal decoherence and dephasing. Here, we overcome this challenge by introducing a super

Bennett Kleinberg, Toby Davies, Maximilian Mozes

The increased use of text data in social science research has benefited from easy-to-access data (e.g., Twitter). That trend comes at the cost of research requiring sensitive but hard-to-share data (e.g., interview data, police reports, electronic health records). We introduce a solution to that stalemate with the open-source text anonymisation software_Text

Ethan Pickering, Themistoklis P. Sapsis

Misleading or unnecessary data can have out-sized impacts on the health or accuracy of Machine Learning (ML) models. We present a Bayesian sequential selection method, akin to Bayesian experimental design, that identifies critically important information within a dataset, while ignoring data that is either misleading or brings unnecessary complexity to the s

Shril Mody, Janvi Thakkar, Devvrat Joshi, Siddharth Soni

In this paper, we present novel variations of an earlier approach called homogeneous clustering algorithm for reducing dataset size. The intuition behind the approaches proposed in this paper is to partition the dataset into homogeneous clusters and select some images which contribute significantly to the accuracy. Selected images are the proper subset of th

Qingyu Zhang, Xiaoyu Shen, Ernie Chang, Jidong Ge

Owing to the lack of corpora for low-resource languages, current works on dialogue generation have mainly focused on English. In this paper, we present mDIA, the first large-scale multilingual benchmark for dialogue generation across low- to high-resource languages. It covers real-life conversations in 46 languages across 19 language families. We present bas

Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf

We propose a recommendation system that suggests treatment strategies to a therapist during the psychotherapy session in real-time. Our system uses a turn-level rating mechanism that predicts the therapeutic outcome by computing a similarity score between the deep embedding of a scoring inventory, and the current sentence that the patient is speaking. The sy

Xiaozhe Hu, Seulip Lee, Lin Mu, Son-Young Yi

In this paper, we present a pressure-robust enriched Galerkin (EG) scheme for solving the Stokes equations, which is an enhanced version of the EG scheme for the Stokes problem proposed in [Son-Young Yi, Xiaozhe Hu, Sanghyun Lee, James H. Adler, An enriched Galerkin method for the Stokes equations, Computers and Mathematics with Applications, accepted, 2022]

Xiyuan Lu, Mingkang Wang, Feng Zhou, Mikkel Heuck

Twisted light with orbital angular momentum (OAM) has been extensively studied for applications in quantum and classical communications, microscopy, and optical micromanipulation. Ejecting the naturally high angular momentum whispering gallery modes (WGMs) of an optical microresonator through a grating-assisted mechanism, where the generated OAM number ($l$)

Jiaqi Li, Likai Chen, Weining Wang, Wei Biao Wu

We propose an inference method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. Our method aggregates moving sum (MOSUM) statistics cross-sectionally by an $\ell^2$-norm and maximizes them over time. We further introduce a novel Two-Way MOSUM, which utilizes spatial-temporal moving regions

Gergö Popping

A number of new $z>11$ galaxy candidates have recently been identified based on public James Webb Space Telescope (JWST) NIRCam observations. Spectroscopic confirmation of these candidates is necessary to robustly measure their redshift and put them in the context of our understanding of the buildup of galaxies in the early Universe. GLASS-z13 is one of thes

A. M. Jarmusch, A. Liu, C. Munley, D. Horta

OpenACC is a high-level directive-based parallel programming model that can manage the sophistication of heterogeneity in architectures and abstract it from the users. The portability of the model across CPUs and accelerators has gained the model a wide variety of users. This means it is also crucial to analyze the reliability of the compilers' implementatio

Usman Muhammad, Mourad Oussalah

Face presentation attack detection (PAD) plays an important role in defending face recognition systems against presentation attacks. The success of PAD largely relies on supervised learning that requires a huge number of labeled data, which is especially challenging for videos and often requires expert knowledge. To avoid the costly collection of labeled dat

Xuan Kien Phung

For linear non-uniform cellular automata (NUCA) over an arbitrary universe, we introduce and investigate their dual linear NUCA. Generalizing results for linear CA, we show that dynamical properties namely pre-injectivity, resp. injectivity, resp. stably injectivity, resp. invertibility of a linear NUCA is equivalent to surjectivity, resp. post-surjectivity,

Peter Kraft, Qian Li, Kostis Kaffes, Athinagoras Skiadopoulos

Developers increasingly use function-as-a-service (FaaS) platforms for data-centric applications that perform low-latency and transactional operations on data, such as for microservices or web serving. Unfortunately, existing FaaS platforms support these applications poorly because they physically and logically separate application logic, executed in cloud f

Jilali Seffadi, Ilham Redouani, Youness Zahidi, Ahmed Jellal

Our research focuses on the transmission gaps of charge carriers passing through phosphorene superlattice, which are made up of a series of barriers and wells generating $n$ identical cells. We determine the solutions of the energy spectrum and then transmission using Bloch's theorem and the transfer-matrix approach. The analysis will be done on the impact o

Deng JiaCheng, Dong Li, Yan Diqun, Wang Rangding

Deep neural networks are vulnerable to adversarial examples that mislead models with imperceptible perturbations. In audio, although adversarial examples have achieved incredible attack success rates on white-box settings and black-box settings, most existing adversarial attacks are constrained by the input length. A More practical scenario is that the adver

Xianbang Chen, Yikui Liu, Lei Wu

Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are raw. In other words, if

Mayukh Bagchi

The development of domain ontological models, though being a mature research arena backed by well-established methodologies, still suffer from two key shortcomings. Firstly, the issues concerning the semantic persistency of ontology concepts and their flexible reuse in domain development employing existing approaches. Secondly, due to the difficulty in under

R. V. Maluf, C. R. Muniz, A. C. L. Santos, Milko Estrada

This paper investigates a new class of regular black hole solutions in (2 + 1)-dimensions by introducing a generalization of the quasi-localized matter model proposed by Estrada and Tello-Ortiz. Initially, we try to physically interpret the matter source encoded in the energy-momentum tensor as originating from nonlinear electrodynamics. We show, however, th

Lauren L. Rose, Kariane Calta

Generalized splines on a graph $G$ with edge labels in a commutative ring $R$ are vertex labelings such that if two vertices share an edge in $G$, the difference between the vertex labels lies in the ideal generated by the edge label. When $R$ is an integral domain, the set of all such splines is a finitely generated $R$-module $R_G$ of rank $n$, the number

Sasikanth Kotti, Mayank Vatsa, Richa Singh

Deep Learning systems need large data for training. Datasets for training face verification systems are difficult to obtain and prone to privacy issues. Synthetic data generated by generative models such as GANs can be a good alternative. However, we show that data generated from GANs are prone to bias and fairness issues. Specifically, GANs trained on FFHQ

Mitch Majure

We study the image of a generalized Dedekind sum relating to the weight zero Eisenstein series $E_{\chi_1,\chi_2}$. We show that the image is a lattice of full rank inside a number field determined by the characters $\chi_1$ and $\chi_2$. We also give a generalization of Knopp's identity for the classical Dedekind sum.

Louis Zhao, Chen Ye Gan, Minglu Zhao

Complex networks are a great tool for simulating the outcomes of different strategies used within the iterated prisoners' dilemma game. However, because the strategies themselves rely on the connection between nodes, then initial network structure should have an impact on the progression of the game. By defining each interaction in terms of a prisoner's dile

Klim Kireev, Bogdan Kulynych, Carmela Troncoso

Many safety-critical applications of machine learning, such as fraud or abuse detection, use data in tabular domains. Adversarial examples can be particularly damaging for these applications. Yet, existing works on adversarial robustness primarily focus on machine-learning models in image and text domains. We argue that, due to the differences between tabula

Zhiyuan Wang, Kaden R. A. Hazzard

It has been proved that in gapped ground states of locally-interacting quantum systems, the effect of local perturbations decays exponentially with distance. However, in systems with power-law ($1/r^\alpha$) decaying interactions, no analogous statement has been shown, and there are serious mathematical obstacles to proving it with existing methods. In this

Zhihao Duan, Ming Lu, Zhan Ma, Fengqing Zhu

Recent research has shown a strong theoretical connection between variational autoencoders (VAEs) and the rate-distortion theory. Motivated by this, we consider the problem of lossy image compression from the perspective of generative modeling. Starting with ResNet VAEs, which are originally designed for data (image) distribution modeling, we redesign their

Rea Dalipi, Giovanni Felder

We give a fermionic formula for $R$-matrices of exterior powers of the vector representations of $U_q(\widehat{ \mathfrak{gl}}_N)$ and relate it to the dynamical Weyl group of Tarasov--Varchenko and Etingof--Varchenko, via a Howe ($\mathfrak{gl}_N,\mathfrak{gl}_M)$-duality. In the limit $N\to\infty$ we obtain $R$-matrices for Fock spaces. As a consequence of

Shreyas Kulkarni, Shreyas Singh, Dhananjay Balakrishnan, Siddharth Sharma

The detection of cracks is a crucial task in monitoring structural health and ensuring structural safety. The manual process of crack detection is time-consuming and subjective to the inspectors. Several researchers have tried tackling this problem using traditional Image Processing or learning-based techniques. However, their scope of work is limited to det

Najem N Sirhan, Manel Martinez-Ramon

The number of LTE users and their applications has increased significantly in the last decade, which increased the demand on the mobile network. LTE-Advanced comes with many features that can support this increasing demand. LTE-Advanced supports Heterogeneous Networks deployment, in which it consists of a mix of macro-cells, remote radio heads, and low power

Tapani Hyttinen, Jouko Väänänen

It is well-known that the first order Peano axioms PA have a continuum of non-isomorphic countable models. The question, how close to being isomorphic such countable models can be, seems to be less investigated. A measure of closeness to isomorphism of countable models is the length of back-and-forth sequences that can be established between them. We show th

Carlos Escobar, Juan Estrada, Chris Rogan

The Photon Detectors Topical Group has identified two areas where focused R&D over the next decade could have a large impact in High Energy Physics Experiments. These areas described here are characterized by the convergence of a compelling scientific need and recent technological advances. Key messages: IF02-1 The development of detectors with the capabilit

Taras Banakh

Let $\mathcal C$ be a class of topological semigroups. A semigroup $X$ is $injectively$ $\mathcal C$-$closed$ if $X$ is closed in each topological semigroup $Y\in\mathcal C$ containing $X$ as a subsemigroup. Let $\mathsf{T_{\!2}S}$ (resp. $\mathsf{T_{\!z}S}$) be the class of Hausdorff (and zero-dimensional) topological semigroups. We prove that a commutative

Mengxin Zheng, Qian Lou, Lei Jiang

Vision Transformers (ViTs) have demonstrated the state-of-the-art performance in various vision-related tasks. The success of ViTs motivates adversaries to perform backdoor attacks on ViTs. Although the vulnerability of traditional CNNs to backdoor attacks is well-known, backdoor attacks on ViTs are seldom-studied. Compared to CNNs capturing pixel-wise local

Jiasheng Li, Jun Yang

A model subspace configuration interaction method is developed to obtain chemically accurate electron correlations by diagonalising a very compact effective Hamiltonian of realistic molecule. The construction of the effective Hamiltonian is deterministic and implemented by iteratively building a sufficiently small model subspace comprising local clusters of

Shaocong Zhu, Zhenhai Fu, Xiaowen Gao, Cuihong Li

Nanomechanical resonator based on levitated particle exhibits unique advantages in the development of ultrasensitive electric field detector. We demonstrate a three-dimensional, high-sensitivity electric field measurement technology using the optically levitated nanoparticle with a known net charge. By changing the relative position between nanoparticle and

Marisa Fernández, Anna Fino, Alexei Kovalev, Vicente Muñoz

We construct new examples of non-formal simply connected compact Sasaki-Einstein 7-manifolds. We determine the minimal model of the total space of any fibre bundle over $CP^2$ with fibre $S^1\times S^2$ or $S^3/Z_p$ ($p>0$), and we apply this to conclude that the Aloff-Wallach spaces are formal. We also find examples of formal manifolds and non-formal manifo

Daniela Sicilia, Luca Malavolta, Lorenzo Pino, Gaetano Scandariato

Transmission spectroscopy is among the most fruitful techniques to infer the main opacity sources present in the upper atmosphere of a transiting planet and to constrain the composition of the thermosphere and of the unbound exosphere. Not having a public tool able to automatically extract a high-resolution transmission spectrum creates a problem of reproduc

Sarder Iftekhar Ahmed, Muhammad Ibrahim, Md. Nadim, Md. Mizanur Rahman

Agriculture is of one of the few remaining sectors that is yet to receive proper attention from the machine learning community. The importance of datasets in the machine learning discipline cannot be overemphasized. The lack of standard and publicly available datasets related to agriculture impedes practitioners of this discipline to harness the full benefit

Kilian Fraboulet, Jean-Paul Ebran

The energy density functional (EDF) method is currently the only microscopic theoretical approach able to tackle the entire nuclear chart. Nevertheless, it suffers from limitations resulting from its empirical character and deteriorating its reliability. This paper is part of a larger program that aims at formulating the EDF approach as an effective field th

G. K. Tamrakar, A. Banerjee

An infinite buffer batch service vacation queue has been studied where service rate of the batch is dependent on the size of the batch and vacation rate is dependent on the queue size at vacation initiation epoch. The arrivals follow the Markovian arrival process (MAP). For service rule, general bulk service (GBS) rule is considered. The service time and vac

Nicolas Pinzauti, Daniela Bubboloni

The power graph $\mathcal{P}(G)$ of a group $G$ is the graph whose vertex set is $G$, having an edge between two distinct vertices if one is the power of the other. The directed power graph $\vec{\mathcal{P}}(G)$ of a group $G$ is the digraph whose vertex set is $G$, having an arc from $x$ to $y$, with $x\ne y$, whenever $y$ is a power of $x$. We rewrite two

Ziheng Wu, Xinyi Zou, Wenmeng Zhou, Jun Huang

We develop an all-in-one computer vision toolbox named EasyCV to facilitate the use of various SOTA computer vision methods. Recently, we add YOLOX-PAI, an improved version of YOLOX, into EasyCV. We conduct ablation studies to investigate the influence of some detection methods on YOLOX. We also provide an easy use for PAI-Blade which is used to accelerate t

Hong Yang, Gongrui Nan, Mingbao Lin, Fei Chao

This paper focuses on the limitations of current over-parameterized shadow removal models. We present a novel lightweight deep neural network that processes shadow images in the LAB color space. The proposed network termed "LAB-Net", is motivated by the following three observations: First, the LAB color space can well separate the luminance information and c

Yu. S. Barash

This paper gives an overview of the unconventional dependence of internal phase differences on the external phase difference in superconductor-normal metal-superconductor (SINIS) and superconductor-superconductor-superconductor (SISIS) tunnel double junctions. The results are obtained within the Ginzburg-Landau (GL) approach that includes boundary conditions

G. R. Boroun

We present a modification of the DGLAP improved saturation model with respect to the nonlinear correction (NLC). The GLR-MQ improved saturation model is considered by employing the parametrization of proton structure function due to the Laplace transforms method, which preserves its behavior success in the low and high $Q^{2}$ regions. We show that the geome

G. R. Boroun

The correspondence between the gluon density behavior of the color dipole picture and the two-Pomeron approach at low $x$ deep inelastic scattering is considered. For photon virtualities of $Q^{2}{\gtrsim}10~\mathrm{GeV}^{2}$, the results for the parametrization and CDP models are defined by the CDP asymptotic limit and are compatible with the soft and hard-

Liyi Zhou, Xihan Xiong, Jens Ernstberger, Stefanos Chaliasos

Within just four years, the blockchain-based Decentralized Finance (DeFi) ecosystem has accumulated a peak total value locked (TVL) of more than 253 billion USD. This surge in DeFi's popularity has, unfortunately, been accompanied by many impactful incidents. According to our data, users, liquidity providers, speculators, and protocol operators suffered a to

Yousef Safari, Anja Kroon, Boris Vaisband

In recent years, with the rise of artificial intelligence and big data, there is an even greater demand for scaling out computing and memory capacity. Silicon interconnect fabric (Si-IF), a wafer-scale integration platform, promotes a paradigm shift in packaging features and enables ultra-large-scale systems, while significantly improving communication bandw

Marco Calzá, Lorenzo Sebastiani

We analyze a class of topological static spherically symmetric vacuum solutions in $f(Q)$-gravity. We considered an Ansatz ensuring that those solutions trivially satisfy the field equations of the theory when the non-metricity scalar is constant. In the specific, we provide and discuss local solutions in the form of black holes and traversable wormholes.

Emna Baccour, Aiman Erbad, Amr Mohamed, Mounir Hamdi

Although Deep Neural Networks (DNN) have become the backbone technology of several ubiquitous applications, their deployment in resource-constrained machines, e.g., Internet of Things (IoT) devices, is still challenging. To satisfy the resource requirements of such a paradigm, collaborative deep inference with IoT synergy was introduced. However, the distrib

D. A. Sasi Kiran, Kritika Anand, Chaitanya Kharyal, Gulshan Kumar

This paper describes a framework for the object-goal navigation task, which requires a robot to find and move to the closest instance of a target object class from a random starting position. The framework uses a history of robot trajectories to learn a Spatial Relational Graph (SRG) and Graph Convolutional Network (GCN)-based embeddings for the likelihood o

B. Helffer, A. Kachmar

Inspired by a recent paper$^*$ by C. Fefferman, J. Shapiro and M. Weinstein, we investigate quantum tunneling for a Hamiltonian with a symmetric double well and a uniform magnetic field. In the simultaneous limit of strong magnetic field and deep potential wells with disjoint supports, tunneling occurs and we derive accurate estimates of its magnitude. $^*\,

Sidun Liu, Peng Qiao, Yong Dou

Image deblurring task is an ill-posed one, where exists infinite feasible solutions for blurry image. Modern deep learning approaches usually discard the learning of blur kernels and directly employ end-to-end supervised learning. Popular deblurring datasets define the label as one of the feasible solutions. However, we argue that it's not reasonable to spec

Pedro Araújo, Matías Pavez-Signé, Nicolás Sanhueza-Matamala

Let $R(C_n)$ be the Ramsey number of the cycle on $n$ vertices. We prove that, for some $C > 0$, with high probability every $2$-colouring of the edges of $G(N,p)$ has a monochromatic copy of $C_n$, as long as $N\geq R(C_n) + C/p$ and $p \geq C/n$. This is sharp up to the value of $C$ and it improves results of Letzter and of Krivelevich, Kronenberg and Mond

Yi-Lin Tsai, Jeremy Irvin, Suhas Chundi, Andrew Y. Ng

Taiwan has the highest susceptibility to and fatalities from debris flows worldwide. The existing debris flow warning system in Taiwan, which uses a time-weighted measure of rainfall, leads to alerts when the measure exceeds a predefined threshold. However, this system generates many false alarms and misses a substantial fraction of the actual debris flows.

Ahana Ghoshal, Ujjwal Sen

We obtain a Gorini-Kossakowski-Sudarshan-Lindblad -like master equation for two or more quantum systems connected locally to a combination of Markovian and non-Markovian heat baths. The master equation was originally formulated for multiparty systems with either exclusively Markovian or non-Markovian environments. We extend it to encompass the case of multip

Colin J. Denzel, Andrew D. Bragg, David H. Richter

The Pi Chamber, located at Michigan Technological University, generates moist turbulent Rayleigh-B\'{e}nard flow in order to replicate steady-state cloud conditions. We take inspiration from this setup and consider a particle-laden, convectively-driven turbulent flow using direct numerical simulation (DNS). The aim of our study is to develop a simple stochas

P Jitendra Kumar Senapati, Pradeep Boggarapu

Strichartz inequality for the solutions of free Schr\"odinger equation associated with Dunkl Hermite operator $H_\kappa$ is generalized to any system of orthonormal functions with initial data. A relation between the kernels of Schr\"odinger propagators ($e^{-it H_\kappa}$ and $e^{it\Delta_\kappa}$) associated with the Dunkl Hermite and Dunkl Laplacian opera

Tao Feng, Weicong Li, Ran Tao

In this paper, we classify the $m$-ovoids of finite classical polar spaces that admit a transitive automorphism group acting irreducibly on the ambient vector space. In particular, we obtain several new infinite families of transitive $m$-ovoids.

Teng Lu, Xuan He, Peng Kang, Jiongyue Xing

In this paper, we consider how to partition the parity-check matrices (PCMs) to reduce the hardware complexity and computation delay for the row layered decoding of quasi-cyclic low-density parity-check (QC-LDPC) codes. First, we formulate the PCM partitioning as an optimization problem, which targets to minimize the maximum column weight of each layer while

Nikolay Mikhaylovskiy

In this short note we explore what is needed for the unsupervised training of graph language models based on link grammars. First, we introduce the ter-mination tags formalism required to build a language model based on a link grammar formalism of Sleator and Temperley [21] and discuss the influence of context on the unsupervised learning of link grammars. S

Christian Schmidt, Adrian Vdberg, Alix Petit

One of the biggest criticisms of the Set Shaping Theory is the lack of a practical application. This is due to the difficulty of its application. In fact, to apply this technique from an experimental point of view we must use a table that defines the correspondences between two sets. However, this approach is not usable in practice, because the table has A^N

Hongjian Xia, Yi Zhang, Dao Zhou, Minyou Chen

Power loss estimation is an indispensable procedure to conduct lifetime prediction for power semiconductor device. The previous studies successfully perform steady-state power loss estimation for different applications, but which may be limited for the electric vehicles (EVs) with high dynamics. Based on two EV standard driving cycle profiles, this paper giv

Evgenij Troitsky

For a restricted wreath product $G\wr \mathbb{Z}^k$, where $G$ is a finite abelian group, we determine (almost in all cases) whether this product has the $R_\infty$ property (i.e., each its automorphism has infinite Reidemeister number).

Jie Zhou, Qi Zhang, Qin Chen, Liang He

Event argument extraction (EAE) aims to extract arguments with given roles from texts, which have been widely studied in natural language processing. Most previous works have achieved good performance in specific EAE datasets with dedicated neural architectures. Whereas, these architectures are usually difficult to adapt to new datasets/scenarios with variou

Zhizhong Wang, Zhanjie Zhang, Lei Zhao, Zhiwen Zuo

Recent studies have shown remarkable success in universal style transfer which transfers arbitrary visual styles to content images. However, existing approaches suffer from the aesthetic-unrealistic problem that introduces disharmonious patterns and evident artifacts, making the results easy to spot from real paintings. To address this limitation, we propose

John Alexis B. Gemino, Alexander J. Balsomo, Geneveve M. Parreño-Lachica, Dave Ryll B. Libre

In this paper we provided a formula for the $n$th term of the $k$-generalized Fibonacci-like sequence, a generalization of the well-known Fibonacci sequence, having $k$ arbitrary initial terms, where the succeeding terms are obtained by adding its previous $k$ terms. The formula for the $n$th term of the $k$-generalized Fibonacci-like sequence was obtained b

Henning Bordihn, Géza Horváth, György Vaszil

The Twelfth International Workshop on Non-Classical Models of Automata and Applications (NCMA 2022) was held in Debrecen, Hungary, on August 26 and 27, 2022, organized by the University of Debrecen. The NCMA workshop series was established in 2009 as an annual event for researchers working on non-classical and classical models of automata, grammars or relate

Phillippe Samer, Dag Haugland

Given a graph $G=(V,E)$ and a set $C$ of unordered pairs of edges regarded as being in conflict, a stable spanning tree in $G$ is a set of edges $T$ inducing a spanning tree in $G$, such that for each $\left\lbrace e_i, e_j \right\rbrace \in C$, at most one of the edges $e_i$ and $e_j$ is in $T$. The existing work on Lagrangean algorithms to the NP-hard prob

Shangkun Weng, Wengang Yang

This paper is devoted to the structural stability of a transonic shock passing through a flat nozzle for two-dimensional steady compressible flows with an external force. We first establish the existence and uniqueness of one dimensional transonic shock solutions to the steady Euler system with an external force by prescribing suitable pressure at the exit o

Boyang You, Kerry Papps

Social employment, which is mostly carried by firms of different types, determines the prosperity and stability of a country. As time passing, the fluctuations of firm employment can reflect the process of creating or destroying jobs. Therefore, it is instructive to investigate the firm employment (size) dynamics. Drawing on the firm-level panel data extract

Alexander Merkurjev, Federico Scavia

We prove that, for all fields $F$ of characteristic different from $2$ and all $a,b,c\in F^\times$, the mod $2$ Massey product $\langle a,b,c,a \rangle$ vanishes as soon as it is defined. For every field $F_0$, we construct a field $F$ containing $F_0$ and $a,b,c,d\in F^\times$ such that $\langle a,b,c \rangle$ and $\langle b,c,d \rangle$ vanish but $\langle

Mateo Anarella, Marcos Salvai

Let L be the manifold of all (unparametrized) oriented lines of R^3. We study the controllability of the control system in L given by the condition that a curve in L describes at each instant, at the infinitesimal level, an helicoid with prescribed angular speed alpha. Actually, we pose the analogous more general problem by means of a control system on the m

Santanu Acharjee, Murad Özkoç, Faical Yacine Issaka

The purpose of this paper is to introduce a new structure `primal'. Primal is dual to grill. Like ideal, dual of filter, this new structure also generates a new topology named `primal topology'. We introduce a new operator using primal, which satisfies Kuratowski's closure axioms. Mainly, we prove that primal topology is finer than the topology of a primal t

Francisco Caruso, Vitor Oguri, Felipe Silveira, Amos Troper

New results recently obtained (\textit{Annals of Physics} (New York) a.n.~168943) established some non-relativistic ground state solutions for three-body molecules interacting through a Chern--Simons model. Within this model, it was argued that Chern--Simons potential should not help improve the fusion rates by replacing electrons with muons, in the case of

Nandiraju Gireesh, D. A. Sasi Kiran, Snehasis Banerjee, Mohan Sridharan

Object Goal Navigation requires a robot to find and navigate to an instance of a target object class in a previously unseen environment. Our framework incrementally builds a semantic map of the environment over time, and then repeatedly selects a long-term goal ('where to go') based on the semantic map to locate the target object instance. Long-term goal sel

Ran Ji, Shuo Chen, Chongwen Huang, Wei E. I. Sha

In this letter, we consider transceivers with spatially-constrained antenna apertures of rectangular symmetry, and aim to improve of spatial degrees of freedom (DoF) and channel capacity leveraging evanescent waves for information transmission in near-field scenarios based on the Fourier plane-wave series expansion. The treatment is limited to an isotropic s

Ziyang Wang, Huoyu Liu, Wei Wei, Yue Hu

Sequential recommendation (SR) aims to predict the subsequent behaviors of users by understanding their successive historical behaviors. Recently, some methods for SR are devoted to alleviating the data sparsity problem (i.e., limited supervised signals for training), which take account of contrastive learning to incorporate self-supervised signals into SR.

Song Chen, Shengze Cai, Tehuan Chen, Chao Xu

In this paper, we propose a novel nonlinear observer based on neural networks, called neural observer, for observation tasks of linear time-invariant (LTI) systems and uncertain nonlinear systems. In particular, the neural observer designed for uncertain systems is inspired by the active disturbance rejection control, which can measure the uncertainty in rea

Karol Chlasta, Paweł Sochaczewski, Izabela Grabowska, Agata Jastrzębowska

We present the design, implementation and evaluation of a new cloud-based social chatbot called MyMigrationBot, that is deployed to Facebook. The system asks and answers questions related to user's personality traits and person-job competency fit to give feedback, and potentially support migrant populations. The chatbot's response database is based on reputa

F. T. Brandt, J. Frenkel, D. G. C. McKeon

We deduce, in a general background gauge, the counter-term Lagrangian for pure quantum gravity to one-loop order. As an application, we evaluate the leading quantum correction to the classical gravitational potential, generated by the vacuum polarization. We find that, in specific background gauges, this yields the complete result for the one-loop quantum co

Yamin Arefeen, Junshen Xu, Molin Zhang, Zijing Dong

Purpose: Training auto-encoders on simulated signal evolution and inserting the decoder into the forward model improves reconstructions through more compact, Bloch-equation-based representations of signal in comparison to linear subspaces. Methods: Building on model-based nonlinear and linear subspace techniques that enable reconstruction of signal dynamics,

Samuel F. Potter, Maria K. Cameron, Ramani Duraiswami

We present algorithms for solving high-frequency acoustic scattering problems in complex domains. The eikonal and transport partial differential equations from the WKB/geometric optic approximation of the Helmholtz equation are solved recursively to generate boundary conditions for a tree of eikonal/transport equation pairs, describing the phase and amplitud

Thomas A. Ciarfuglia, Ionut M. Motoi, Leonardo Saraceni, Mulham Fawakherji

Detection, segmentation and tracking of fruits and vegetables are three fundamental tasks for precision agriculture, enabling robotic harvesting and yield estimation applications. However, modern algorithms are data hungry and it is not always possible to gather enough data to apply the best performing supervised approaches. Since data collection is an expen

David S. Axelrod, Brian P. Harper, John C. Paolillo

While most social media companies have attempted to address the challenge of COVID-19 misinformation, the success of those policies is difficult to assess, especially when focusing on individual platforms. This study explores the relationship between Twitter and YouTube in spreading COVID-19 vaccine-related misinformation through a mixed-methods approach to

Jing-jing Liu, Zheng-wei Li, Bin Liang, Jian-chun Cheng

Efficiently receiving underwater sound remotely from air is a long-standing challenge in acoustics hindered by the large impedance mismatch at the water-air interface. Here we introduce and experimentally demonstrate a technique for remote and efficient water-to-air eavesdropping through phase-engineered impedance matching metasurfaces. By judiciously engine

Taekyun Kim, Dae San Kim

In recent years, some degenerate versions of quite a few special numbers and polynomials are introduced and investigated by means of various methods. The aim of this paper is to study some results on degenerate harmonic numbers, degenerate hyperharmonic numbers, degenerate Fubi polynomials and degenerate r-Fubini polynomials from a general identity which is

Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux

Learning to safely navigate in unknown environments is an important task for autonomous drones used in surveillance and rescue operations. In recent years, a number of learning-based Simultaneous Localisation and Mapping (SLAM) systems relying on deep neural networks (DNNs) have been proposed for applications where conventional feature descriptors do not per

Diya Anand, Ioannis Mavromatis, Pietro Carnelli, Aftab Khan

Data-enabled cities are recently accelerated and enhanced with automated learning for improved Smart Cities applications. In the context of an Internet of Things (IoT) ecosystem, the data communication is frequently costly, inefficient, not scalable and lacks security. Federated Learning (FL) plays a pivotal role in providing privacy-preserving and communica

Xin Zhang, Yong Jiang, Xiaobin Wang, Xuming Hu

Successful Machine Learning based Named Entity Recognition models could fail on texts from some special domains, for instance, Chinese addresses and e-commerce titles, where requires adequate background knowledge. Such texts are also difficult for human annotators. In fact, we can obtain some potentially helpful information from correlated texts, which have

Jiangtao Zhao, Ivan A. Vartanyants, Fucai Zhang

Bragg coherent diffraction imaging (BCDI) is a unique and powerful method for tracking three-dimensional strain fields non-destructively. While BCDI has been successfully applied to many scientific research fields and receives high demands, the reconstructed results for highly strained crystals are still subject to big uncertainties. Here, the progress in im

Emel Altas, Bayram Tekin

We provide two novel ways to compute the surface gravity ($\kappa$) and the Hawking temperature $(T_{H})$ of a stationary black hole: in the first method $T_{H}$ is given as the three-volume integral of the Gauss-Bonnet invariant (or the Kretschmann scalar for Ricci-flat metrics) in the total region outside the event horizon; in the second method it is given

Tristan L. Smith, Vivian Poulin, Théo Simon

The Hubble tension can be addressed by modifying the sound horizon ($r_s$) before recombination, triggering interest in $r_s$-free early-universe estimates of the Hubble constant, $H_0$. Constraints on $H_0$ from an $r_s$-free analysis of the full shape BOSS galaxy power spectra within LCDM were recently reported and used to comment on the viability of physi

Hannah Bos, Dylan Muir

Spiking Neural Networks (SNNs) provide an efficient computational mechanism for temporal signal processing, especially when coupled with low-power SNN inference ASICs. SNNs have been historically difficult to configure, lacking a general method for finding solutions for arbitrary tasks. In recent years, gradient-descent optimization methods have been applied

Etienne Wijler

In this paper, we develop a restricted eigenvalue condition for unit-root non-stationary data and derive its validity under the assumption of independent Gaussian innovations that may be contemporaneously correlated. The method of proof relies on matrix concentration inequalities and offers sufficient flexibility to enable extensions of our results to altern

Suraka Bhattacharjee, Koushik Mandal, Supurna Sinha

We derive a quantum Langevin equation for a quantum spin in the presence of a magnetic field and study its dynamics in the Markovian limit using the Ohmic bath model. We extend our analysis to the Drude bath with a finite memory. We study the time evolution of the expectation values of the magnetic moments. The spin auto-correlation functions exhibit a dampe

Wei Xiong, Mingfeng Wang, Guo-Qiang Zhang, Jiaojiao Chen

Strong long-distance spin-magnon coupling is essential for solid-state quantum information processing and single qubit manipulation. Here, we propose an approach to realize strong spin-magnon coupling in a hybrid optomechanical cavity-spin-magnon system, where the optomechanical system, consisting of two cavities coupled to a common high-frequency mechanical

Shukai Han, Mi Zhang, Dejun Jiang, Jin Xiong

RDMA (Remote Direct Memory Access) is widely exploited in building key-value stores to achieve ultra low latency. In RDMA-based key-value stores, the indexing time takes a large fraction (up to 74%) of the overall operation latency as RDMA enables fast data accesses. However, the single index structure used in existing RDMA-based key-value stores, either has

Bowen Fu, Sek Kun Leong, Xiaocong Lian, Xiangyang Ji

Vision-based robotic assembly is a crucial yet challenging task as the interaction with multiple objects requires high levels of precision. In this paper, we propose an integrated 6D robotic system to perceive, grasp, manipulate and assemble blocks with tight tolerances. Aiming to provide an off-the-shelf RGB-only solution, our system is built upon a monocul

Vagner R. de Bessa, Anderson L. P. Porto, Pavel A. Zalesskii

We introduce a class $\A$ of finitely generated residually finite accessible groups with some natural restriction on one-ended vertex groups in their JSJ-decompositions. We prove that the profinite completion of groups in $\A$ almost detects its JSJ-decomposition and compute the genus of free products of groups in $\A$.