August 2022 arXiv papers — page 106

Jing Du, Zesheng Ye, Lina Yao, Bin Guo

Recent sequential recommendation models rely increasingly on consecutive short-term user-item interaction sequences to model user interests. These approaches have, however, raised concerns about both short- and long-term interests. (1) {\it short-term}: interaction sequences may not result from a monolithic interest, but rather from several intertwined inter

Yuri A. Kordyukov

The paper is devoted to the trace formula for the magnetic Laplacian associated with a magnetic system on a compact manifold. This formula is a natural generalization of the semiclassical Gutzwiller trace formula and reduces to it in the case when the magnetic field form is exact. It differs somewhat from the Guillemin-Uribe trace formula studied in the auth

Lucas Mourot, Ludovic Hoyet, François Le Clerc, Pierre Hellier

Human motion synthesis and editing are essential to many applications like film post-production. However, they often introduce artefacts in motions, which can be detrimental to the perceived realism. In particular, footskating is a frequent and disturbing artefact requiring foot contacts knowledge to be cleaned up. Current approaches to obtain foot contact l

Victor P. Goncalves, Diego R. Gratieri, Alex S. C. Quadros

The number of events observed in neutrino telescopes depends on the neutrino fluxes in the Earth, their absorption while crossing the Earth and their interaction in the detector. In this paper, we investigate the impact of the QCD dynamics at high energies on the energy dependence of the average inelasticity and angular dependence of the absorption probabili

Saikat Chakraborty, Daniele Gregoris, B. Mishra

We address the question of the uniqueness of spatially flat $\Lambda$CDM-like evolution for FLRW cosmologies in General Relativity, i.e. whether any model other than the spatially flat $\Lambda$CDM can give rise to the same type of scale factor evolution. Firstly, we elaborate on what we exactly imply by a $\Lambda$CDM-like evolution or kinematic/cosmographi

Peter A. Sloan, Kristina R. Rusimova

Understanding the ultra-fast transport properties of hot charge carriers is of significant importance both fundamentally and technically in applications like solar cells and transistors. However, direct measurement of charge transport at the relevant nanometre length scales is challenging with only a few experimental methods demonstrated to date. Here we rep

Mamadou N'Diaye, David Mary, Frantz Martinache, Roxanne Ligi

Kernel phase is a method to interpret stellar point source images by considering their formation as the analytical result of an interferometric process. Using Fourier formalism, this method allows for observing planetary companions around nearby stars at separations down to half a telescope resolution element, typically 20\,mas for a 8\,m class telescope in

Roberto Merco, Francesco Ferrante, Ricardo G. Sanfelice, Pierluigi Pisu

Output feedback control design for linear time-invariant systems in the presence of sporadic measurements and exogenous perturbations is addressed. To cope with the sporadic availability of measurements of the output, a hybrid dynamic output feedback controller equipped with a holding device whose state is reset when a new measurement is available is designe

Umar Masud, Ethan Cohen, Ihab Bendidi, Guillaume Bollot

Progress in automated microscopy and quantitative image analysis has promoted high-content screening (HCS) as an efficient drug discovery and research tool. While HCS offers to quantify complex cellular phenotypes from images at high throughput, this process can be obstructed by image aberrations such as out-of-focus image blur, fluorophore saturation, debri

Vitaly Feldman, Audra McMillan, Kunal Talwar

The shuffle model of differential privacy has gained significant interest as an intermediate trust model between the standard local and central models [EFMRTT19; CSUZZ19]. A key result in this model is that randomly shuffling locally randomized data amplifies differential privacy guarantees. Such amplification implies substantially stronger privacy guarantee

M. Zubair, Quratulien Muneer, Saira Waheed

The primary objective of this article is to study the energy condition bounds for spherical and hyperbolic wormholes in well-known $f(R,T)$ theory of gravity. For this purpose, we formulate the field equations for spherically and pseudospherically geometries using anisotropic matter and linear form of generic function $f(R,T)$. By imposing different conditio

Frédéric Bihan, Tristan Humbert, Sébastien Tavenas

We prove that the number of connected components of a smooth hypersurface in the positive orthant of $\mathbb{R}^n$ defined by a real polynomial with $d + k + 1$ monomials, where $d$ is the dimension of the affine span of the exponent vectors, is smaller than or equal to $8(d+1)^{k-1} 2^{k-1 \choose 2}$, improving the previously known bounds. We refine this

Ruichu Cai, Weilin Chen, Zeqin Yang, Shu Wan

Estimating long-term causal effects based on short-term surrogates is a significant but challenging problem in many real-world applications, e.g., marketing and medicine. Despite its success in certain domains, most existing methods estimate causal effects in an idealistic and simplistic way - ignoring the causal structure among short-term outcomes and treat

Yiheng Lu, Maoguo Gong, Wei Zhao, Kaiyuan Feng

Pruning techniques are used comprehensively to compress convolutional neural networks (CNNs) on image classification. However, the majority of pruning methods require a well pre-trained model to provide useful supporting parameters, such as C1-norm, BatchNorm value and gradient information, which may lead to inconsistency of filter evaluation if the paramete

Vít Fojtík, Petra Laketa, Pavlo Mozharovskyi, Stanislav Nagy

The Tukey (or halfspace) depth extends nonparametric methods toward multivariate data. The multivariate analogues of the quantiles are the central regions of the Tukey depth, defined as sets of points in the $d$-dimensional space whose Tukey depth exceeds given thresholds $k$. We address the problem of fast and exact computation of those central regions. Fir

Yu-Jie Hao, Ming-Yuan Zhu, Xiao-Ming Ma, Chengcheng Zhang

We report successful growth of millimeter-sized high quality single crystals of V$_3$S$_4$, a candidate topological semimetal belonging to a low-symmetry space group and consisting of only low atomic number elements. Using density functional theory calculations and angle-resolved photoemission spectroscopy, we show that the nonmagnetic phase of monoclinic V$

Linbo Liang, Guoxing Xia, Alexander Pukhov, John Patrick Farmer

Beam-driven plasma wakefield accelerators typically use the external injection scheme to ensure controllable beam quality at injection. However, the externally injected witness bunch may exhibit a non-Gaussian transverse density distribution. Using particle-in-cell simulations, we show that the common beam quality factors, such as the normalized RMS emittanc

Andrea Calignano, Michele Correggi

We study a dilute gas of interacting fermions at temperature $T=0$ and chemical potential $\mu \in \mathbb{R}$. The particles are trapped by an external potential, and they interact via a microscopic attractive two-body potential with a two-body bound state. We prove the emergence of the macroscopic Gross-Pitaevskii theory as first-order contribution to the

Jui-Kun Chiu, Tzu-Yun Lin, Wei-Shen Hsu, Shun-Chi Wu

Biometric authentication relies on an individual's physiological or behavioral traits to verify their identity before granting access permission to a system or device without remembering anything. Although electrocardiograms (ECGs) have been considered a biometric trait, an ECG biometric recognition system that operates in verification mode is rarely conside

Arijit Chakrabarty, Gennady Samorodnitsky

We describe the cluster of large deviations events that arise when one such large deviations event occurs. We work in the framework of an infinite moving average process with a noise that has finite exponential moments.

Amel Dechemi, Vikarn Bhakri, Ipsita Sahin, Arjun Modi

Action recognition is an important component to improve autonomy of physical rehabilitation devices, such as wearable robotic exoskeletons. Existing human action recognition algorithms focus on adult applications rather than pediatric ones. In this paper, we introduce BabyNet, a light-weight (in terms of trainable parameters) network structure to recognize i

Yoko Oya, Hirofumi Kibukawa, Shota Miyake, Satoshi Yamamoto

Radio observations of low-mass star formation in molecular spectral lines have rapidly progressed since the advent of Atacama Large Millimeter/submillimeter Array (ALMA). A gas distribution and its kinematics within a few 100s au scale around a Class 0-I protostar are spatially resolved, and the region where a protostellar disk is being formed is now reveale

Zixun Lan, Binjie Hong, Ye Ma, Fei Ma

Graph similarity measurement, which computes the distance/similarity between two graphs, arises in various graph-related tasks. Recent learning-based methods lack interpretability, as they directly transform interaction information between two graphs into one hidden vector and then map it to similarity. To cope with this problem, this study proposes a more i

Weijia Shao, Sahin Albayrak

In this paper, we propose and analyze algorithms for zeroth-order optimization of non-convex composite objectives, focusing on reducing the complexity dependence on dimensionality. This is achieved by exploiting the low dimensional structure of the decision set using the stochastic mirror descent method with an entropy alike function, which performs gradient

S. A. Tyul'bashev, G. E. Tyul'basheva, M. A. Kitaeva

Since the discovery of pulsars, dozens of surveys have already been conducted with their searches. In the course of surveys in the sky, areas from thousands to tens of thousands of square degrees are explored. Despite repeated observations of the same areas, new pulsars are constantly being discovered. We present Pushchino Multibeam Pulsar Search (PUMPS), ha

Carles Bonet, Mike R. Jeffrey, Pau Martín, Josep M. Olm

When an oscillator switches abruptly between different frequencies, there is some ambiguity in deciding how the system should be modelled at the switch. Here we describe two seemingly natural models of a switch in a simple periodically-forced harmonic oscillator, which disagree starkly in their predictions of its long time behaviour. Attempting to resolve th

Haojie Ren

We study dynamical systems generated by skew products: $$T: [0,1)\times\mathbb{R}\to [0,1)\times\mathbb{R} \quad\quad T(x,y)=(bx\mod1,\gamma y+\phi(x))$$ where integer $b\ge2$, $0<\gamma<1$ and $\phi$ is a real analytic $\mathbb{Z}$-periodic function. We prove the following dichotomy for the SRB measure $\omega$ for $T$: Either the support of $\omega$ is a g

Mikel Falxa, Stanislav Babak, Maude Le Jeune

Markov Chain Monte Carlo approach is frequently used within Bayesian framework to sample the target posterior distribution. Its efficiency strongly depends on the proposal used to build the chain. The best jump proposal is the one that closely resembles the unknown target distribution, therefore we suggest an adaptive proposal based on Kernel Density Estimat

Ionel-Dumitrel Ghiba, Mircea Birsan, Patrizio Neff

In this paper we derive the linear elastic Cosserat shell model incorporating effects up to order $O(h^5)$ in the shell thickness $h$ as a particular case of the recently introduced geometrically nonlinear elastic Cosserat shell model. The existence and uniqueness of the solution is proven in suitable admissible sets. To this end, inequalities of Korn-type f

Alexandra Malyugina, Nantheera Anantrasirichai, David Bull

Although image denoising algorithms have attracted significant research attention, surprisingly few have been proposed for, or evaluated on, noise from imagery acquired under real low-light conditions. Moreover, noise characteristics are often assumed to be spatially invariant, leading to edges and textures being distorted after denoising. Here, we introduce

Tao Zhang, Houyi Yu

Given a positive integer $n$ and a nonnegative integer $k$ with $k\leq n$, we denote by $\mathcal{A}(n,k)$ the class of all $n$-by-$n$ $(0,1)$-matrices with constant row and column sums $k$. In this paper, we show that the Bruhat order and the secondary Bruhat order coincide on $\mathcal{A}(n,k)$ if and only if either $0\leq n\leq 5$ or $k\in\{0,1,2,n-2,n-1,

Scuderi S., Giuliani A., Pareschi G., Tosti G.

The ASTRI Mini-Array (MA) is an INAF project to build and operate a facility to study astronomical sources emitting at very high-energy in the TeV spectral band. The ASTRI MA consists of a group of nine innovative Imaging Atmospheric Cherenkov telescopes. The telescopes will be installed at the Teide Astronomical Observatory of the Instituto de Astrofisica d

Marie-No\''elle Célérier

This article is the second in a series devoted to the study of spacetimes sourced by a stationary cylinder of fluid rigidly rotating around its symmetry axis and exhibiting an anisotropic pressure by using new exact interior solutions of General Relativity. The configurations have been specialized to three different cases where the pressure is on turn direct

Renzhi Su, Elaine M. Sadler, James R. Allison, Elizabeth K. Mahony

We present the results of a search for associated 21 cm HI absorption at redshift 0.42 < z < 1.00 in radio-loud galaxies from three Galaxy And Mass Assembly (GAMA) survey fields. These observations were carried out as part of a pilot survey for the ASKAP First Large Absorption Survey in HI (FLASH). From a sample of 326 radio sources with 855.5 MHz peak flux

Manuel Fokam, Michael Beukman

Data availability and quality are major challenges in natural language processing for low-resourced languages. In particular, there is significantly less data available than for higher-resourced languages. This data is also often of low quality, rife with errors, invalid text or incorrect annotations. Many prior works focus on dealing with these problems, ei

Ahmed M. Gad, Nesma M. Darwish

In longitudinal data a response variable is measured over time, or under different conditions, for a cohort of individuals. In many situations all intended measurements are not available which results in missing values. If the missing value is never followed by an observed measurement, this leads to dropout pattern. The missing values could be in the respons

Qi Yang, Xing-Yu Zhang, Hai-Jun Liao, Hong-Hao Tu

We investigate the physics of projected d-wave pairing states using their fermionic projected entangled pair state (fPEPS) representation. First, we approximate a d-wave Bardeen-Cooper-Schrieffer state using the Gaussian fPEPS. Next, we translate the resulting state into fPEPS tensors and implement the Gutzwiller projection which removes double occupancy by

Weixuan Wang, Wei Peng, Chong Hsuan Huang, Haoran Wang

In this paper, we describe a data enhancement method for developing Emily, an emotion-affective open-domain chatbot. The proposed method is based on explicitly modeling positively transitioned (PT) sentiment data from multi-turn dialogues. We construct a dialogue corpus with PT sentiment data and will release it for public use. By fine-tuning a pretrained di

Resve A. Saleh, A. K. Md. Ehsanes Saleh

This paper analyzes a popular loss function used in machine learning called the log-cosh loss function. A number of papers have been published using this loss function but, to date, no statistical analysis has been presented in the literature. In this paper, we present the distribution function from which the log-cosh loss arises. We compare it to a similar

Saumya Bhatnagar, Tarun Rambha, Gitakrishnan Ramadurai

With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit

Mi Jiang, Mona Berciu, George A. Sawatzky

Motivated by the recent X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS) experiments, we use a detailed impurity model to explore the nature of the parent compound and hole doped states of (La, Nd, Pr)NiO$_2$ by including the crystal field splitting, the Ni-$3d$ multiplet structure, and the hybridization between Ni-$3d$, O-$

Leonhard Frerick, Christian Vollmann, Michael Vu

The classical local Neumann problem is well studied and solutions of this problem lie, in general, in a Sobolev space. In this work, we focus on nonlocal Neumann problems with measurable, nonnegative kernels, whose solutions require less regularity assumptions. For kernels of this kind we formulate and study the weak formulation of the nonlocal Neumann probl

Qihua Zhang, Junning Liu, Yuzhuo Dai, Yiyan Qi

Recommender System (RS) is an important online application that affects billions of users every day. The mainstream RS ranking framework is composed of two parts: a Multi-Task Learning model (MTL) that predicts various user feedback, i.e., clicks, likes, sharings, and a Multi-Task Fusion model (MTF) that combines the multi-task outputs into one final ranking

Wei-Jer Chang, Yeping Hu, Chenran Li, Wei Zhan

Simulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where traffic participants follow certain human-encoded rules that fail to generate complex human behaviors. Therefore, the reactive simulation concept is proposed to bridge the human beh

Yuuki Nishiyama, Kosuke Hatai, Kota Tsubouchi, Kaoru Sezaki

Excessive or inadequate exposure to ultraviolet light (UV) is harmful to health and causes osteoporosis, colon cancer, and skin cancer. The UV Index, a standard scale of UV light, tends to increase in sunny places and sharply decrease in the shade. A method for distinguishing shady and sunny places would help us to prevent and cure diseases caused by UV. How

Choonghan Kim, Gary Geunbae Lee

Data-to-text (D2T) generation is the task of generating texts from structured inputs. We observed that when the same target sentence was repeated twice, Transformer (T5) based model generates an output made up of asymmetric sentences from structured inputs. In other words, these sentences were different in length and quality. We call this phenomenon "Asymmet

Hiroto Ishida

We consider solutions $u^\varepsilon$ of Poisson problems with the Dirichlet condition on domains $\Omega_\varepsilon$ with holes concentrated at subsets of a domain $\Omega$ non-periodically. We show $u^\varepsilon$ converges to a solution of a Poisson problem with a simple function potential. This is a generalized result of a sample model given by Cioranes

Zhilin Fu, Sangwon Hwang, Jihwan Moon, Haibao Ren

In this work, we study codebook designs for full-dimension multiple-input multiple-output (FD-MIMO) systems with a multi-panel array (MPA). We propose novel codebooks which allow precise beam structures for MPA FD-MIMO systems by investigating the physical properties and alignments of the panels. We specifically exploit the characteristic that a group of ant

Rajni Bala, Sooryansh Asthana, V. Ravishankar

Near-term quantum communication protocols suffer inevitably from channel noises, whose alleviation has been mostly attempted with resources such as multiparty entanglement or sophisticated experimental techniques. Generation of multiparty higher dimensional entanglement is not easy. This calls for exploring realistic solutions which are implementable with cu

Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi, Giampiero Salvi

We propose a multi-layer variational autoencoder method, we call HR-VQVAE, that learns hierarchical discrete representations of the data. By utilizing a novel objective function, each layer in HR-VQVAE learns a discrete representation of the residual from previous layers through a vector quantized encoder. Furthermore, the representations at each layer are h

Heng Cong, Mingzhu Sun, Duoying Zhou, Xin Zhao

Zebrafish is an excellent model organism, which has been widely used in the fields of biological experiments, drug screening, and swarm intelligence. In recent years, there are a large number of techniques for tracking of zebrafish involved in the study of behaviors, which makes it attack much attention of scientists from many fields. Multi-target tracking o

J. Blümlein, A. Maier, P. Marquard, G. Schäfer

Binary sources of gravitational waves in the early inspiral phase are accurately described by a post-Newtonian expansion in small velocity and weak interaction. We compute the conservative dynamics to fifth and partial sixth order using a non-relativistic effective field theory. We give predictions for central observables and determine the required coefficie

Sunandan Gangopadhyay, Rituparna Mandal, Amitabha Lahiri

The exact renormalization group flow equations for gravity lead to quantum corrections of Newton's constant and cosmological constant. Using this we investigate the Bianchi-I cosmological model at late times. In particular, we obtain the scale factors in different directions, and observe that they eventually evolve into Friedmann-Lema\^itre-Robertson-Walker

Hy Lam

In 1985, T. Sunada constructed a vast collection of non-isometric Laplace-isospectral pairs $(M_1,g_1)$, resp. $(M_2,g_2)$ of Riemannian manifolds. He further proves that the Ruelle zeta functions $Z_g(s):= \prod_{\gamma}(1 - e^{-sL(\gamma)})^{-1}$ of $(M_1,g_1)$, resp. $(M_2,g_2)$ coincide, where $\{\gamma\}$ runs over the primitive closed geodesics of $(M,

Daniel D. Kelson, Louis E. Abramson

Multiple investigations support describing galaxy growth as a stochastic process with correlations over a range of timescales governed by a parameter, $H$, empirically and theoretically constrained to be near unity. Here, we show that the distribution of UV-slopes, $\beta$, derived from an ensemble of theoretical $H=1$ star formation histories (SFHs) is cons

Mohammad Haghir Ebrahimabadi

Given a dataset of images containing different objects with different features such as shape, size, rotation, and x-y position; and a Variational Autoencoder (VAE); creating a disentangled encoding of these features in the hidden space vector of the VAE was the task of interest in this paper. The dSprite dataset provided the desired features for the required

Shehroz S. Khan, Ali Abedi, Tracey Colella

Background: Student engagement (SE) in virtual learning can have a major impact on meeting learning objectives and program dropout risks. Developing Artificial Intelligence (AI) models for automatic SE measurement requires annotated datasets. However, existing SE datasets suffer from inconsistent definitions and annotation protocols mostly unaligned with the

Ionuţ-Alexandru Albu, Stelian Spînu

Automatic identification of emotions expressed in Twitter data has a wide range of applications. We create a well-balanced dataset by adding a neutral class to a benchmark dataset consisting of four emotions: fear, sadness, joy, and anger. On this extended dataset, we investigate the use of Support Vector Machine (SVM) and Bidirectional Encoder Representatio

Hiroyuki Hirashita, I-Da Chiang

We investigate physical reasons for high dust temperatures ($T_\mathrm{dust}\gtrsim 40$ K) observed in some high-redshift ($z>5$) galaxies using analytic models. We consider two models that can be treated analytically: the radiative transfer (RT) model, {where a broad distribution of values for $T_\mathrm{dust}$ is considered}, and the one-tempearture (one-$

Beomsoo Ko, Hwanjin Kim, Junil Choi

To compensate the loss from outdated channel state information in wideband massive multiple-input multipleoutput (MIMO) systems, channel prediction can be performed by leveraging the temporal correlation of wireless channels. Machine learning (ML)-based channel predictors for massive MIMO systems were designed recently; however, the time overhead to collect

Akira Iyo, Hiroshi Fujihisa, Yoshito Gotoh, Shigeyuki Ishida

Enriching the material variation often contributes to the progress of materials science. We have discovered for the first time antiperovskite arsenide SrPd$_{3}$As and revealed a hidden structural and superconducting phase in Sr(Pd$_{1-x}$Pt$_{x}$)$_{3}$As. The Pd-rich samples (0 $\leq$ x $\leq$ 0.2) had the same non-centrosymmetric (NCS) tetragonal structur

Eduard Feireisl, Young Sam Kwon

We consider the motion of a viscous compressible and heat conducting fluid confined in the gap between two rotating cylinders (Taylor-Couette flow). The temperature of the cylinders is fixed but not necessarily constant. We show that the problem admits a time--periodic solution as soon as the ratio of the angular velocities of the two cylinders is a rational

Yuta Suzuki, Shohei Watabe, Shiro Kawabata, Shumpei Masuda

Kerr parametric oscillators (KPOs) have attracted increasing attention in terms of their application to quantum information processing and quantum simulations. The state preparation and measurement of KPOs are typical requirements when they are used as qubits. The methods previously proposed for state preparations of KPOs utilize modulation of a pump field o

Hyesang Cho, Beomsoo Ko, Bruno Clerckx, Junil Choi

Numerous studies claim that terahertz (THz) communication will be an essential piece of sixth-generation wireless communication systems. Its promising potential also comes with major challenges, in particular the reduced coverage due to harsh propagation loss, hardware constraints, and blockage vulnerability. To increase the coverage of THz communication, we

Wei Li, Yunpeng Ma, Tianyi Feng, Sergei V. Kalinin

Understanding the mechanisms and spatial correlations of crystallographic symmetry breaking in ferroelectric materials is essential to tuning their functional properties. While optical second harmonic generation (SHG) has long been utilized in ferroelectric studies, its capability for probing complex polar materials has yet to be fully realized. Here, we dev

Haowen Ren, Xin Yu Zheng, Sanyum Channa, Guanzhong Wu

Spin-Hall nano-oscillators (SHNOs) are promising spintronic devices to realize current controlled GHz frequency signals in nanoscale devices for neuromorphic computing and creating Ising systems. However, traditional SHNOs -- devices based on transition metals -- have high auto-oscillation threshold currents as well as low quality factors and output powers.

Kensuke Yoshizawa

This paper is concerned with the variational problem for the elastic energy defined on symmetric graphs under the unilateral constraint. Assuming that the obstacle function satisfies the symmetric cone condition, we prove (i) uniqueness of minimizers, (ii) loss of regularity of minimizers, and give (iii) complete classification of existence and non-existence

Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu

DBSCAN is widely used in many scientific and engineering fields because of its simplicity and practicality. However, due to its high sensitivity parameters, the accuracy of the clustering result depends heavily on practical experience. In this paper, we first propose a novel Deep Reinforcement Learning guided automatic DBSCAN parameters search framework, nam

Yu Liu, Panyue Zhou

Let $(\mathcal B,\mathbb{E},\mathfrak{s})$ be an extriangulated category and $\mathcal S$ be an extension closed subcategory of $\mathcal B$. In this article, we prove that the Gabriel-Zisman localization $\mathcal B/\mathcal S$ can be realized as an ideal quotient inside $\mathcal B$ when $\mathcal S$ satisfies some mild conditions. The ideal quotient is an

Rishabh Datta, Danny R. Russell, Iek Tang, Thomas Clayson

We investigate 3D bow shocks in a highly collisional magnetized aluminum plasma, generated during the ablation phase of an exploding wire array on the MAGPIE facility (1.4 MA, 240 ns). Ablation of plasma from the wire array generates radially diverging, supersonic ($M_S \sim 7$), super-Alfv\'enic ($M_A > 1$) magnetized flows with frozen-in magnetic flux ($R_

Bharath Ramakrishnan, Ruijia Deng, Hassan Ali

Estimation of the Heart rate from the facial video has a number of applications in the medical and fitness industries. Additionally, it has become useful in the field of gaming as well. Several approaches have been proposed to seamlessly obtain the Heart rate from the facial video, but these approaches have had issues in dealing with motion and illumination

Hang Yan, Yu Sun, Xiaonan Li, Xipeng Qiu

Named entity recognition (NER) is the task to detect and classify the entity spans in the text. When entity spans overlap between each other, this problem is named as nested NER. Span-based methods have been widely used to tackle the nested NER. Most of these methods will get a score $n \times n$ matrix, where $n$ means the length of sentence, and each entry

Agustín L. Nagy, William J. Zuluaga Botero

In this paper we introduce the variety of I-modal ririgs. We characterize the congruence lattice of its members by means of I-filters and we provide a description on I-filter generation. We also provide an axiomatic presentation for the variety generated by chains of the subvariety of contractive I-modal ririgs. Finally, we introduce a Hilbert-style calculus

Madisen Holbrook, Yuxuan Chen, Hyunsue Kim, Lisa Frammolino

The ability to engineer atomically thin nanoscale lateral heterojunctions (HJs) is critical to lay the foundation for future two-dimensional (2D) device technology. However, the traditional approach to creating a heterojunction by direct growth of a heterostructure of two different materials constrains the available band offsets, and it is still unclear if l

Farhad Aghili

This paper presents a robust 6-DOF relative navigation by combining the iterative closet point (ICP) registration algorithm and a noise-adaptive Kalman filter (AKF) in a closed-loop configuration together with measurements from a laser scanner and an inertial measurement unit (IMU). In this approach, the fine-alignment phase of the registration is integrated

Weimin Lyu, Songzhu Zheng, Tengfei Ma, Haibin Ling

Trojan attacks pose a severe threat to AI systems. Recent works on Transformer models received explosive popularity and the self-attentions are now indisputable. This raises a central question: Can we reveal the Trojans through attention mechanisms in BERTs and ViTs? In this paper, we investigate the attention hijacking pattern in Trojan AIs, \ie, the trigge

Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng

Deep-learning-based clinical decision support using structured electronic health records (EHR) has been an active research area for predicting risks of mortality and diseases. Meanwhile, large amounts of narrative clinical notes provide complementary information, but are often not integrated into predictive models. In this paper, we provide a novel multimoda

Xin Huang, Xiaoyu Tian, Junru Gu, Qiao Sun

Predicting future behaviors of road agents is a key task in autonomous driving. While existing models have demonstrated great success in predicting marginal agent future behaviors, it remains a challenge to efficiently predict consistent joint behaviors of multiple agents. Recently, the occupancy flow fields representation was proposed to represent joint fut

Yifei Wang, Shiyang Chen, Guobin Chen, Ethan Shurberg

This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowing ARGs to encode rich structural information widely observed in real applications. Existing graph neural networks offer limited ability to capture complex interactions within local

Motohiko Ezawa, Shun Yasunaga, Akio Higo, Tetuya Iizuka

We propose to use a buckled plate as a qubit, where a double-well potential is mechanically produced by pushing the plate from both the sides. The right and left positions of the plate are assigned to be quantum states $|0\rangle $ and $|1\rangle $. Quantum effects emerge when the displacement is of the order of picometers, although the size of a buckled pla

Roberto B. Corcino, Cristina B. Corcino

In this paper, the divisibility property of the type 2 $(p, q)$-analogue of the $r$-Whitney numbers of the second kind is established. More precisely, a congruence relation modulo $pq$ for this $(p,q)$-analogue is derived.

Cassandra Granade, Nathan Wiebe

In recent years there has been substantial development in algorithms for quantum phase estimation. In this work we provide a new approach to online Bayesian phase estimation that achieves Heisenberg limited scaling that requires exponentially less classical processing time with the desired error tolerance than existing Bayesian methods. This practically mean

Weiwei Cao, Yuzhu Cao

Accurate and automated segmentation of multi-structure (i.e., kidneys, renal tu-mors, arteries, and veins) from 3D CTA is one of the most important tasks for surgery-based renal cancer treatment (e.g., laparoscopic partial nephrectomy). This paper briefly presents the main technique details of the multi-structure seg-mentation method in MICCAI 2022 KIPA chal

Younghoon Kim, Tao Wang, Danyi Xiong, Xinlei Wang

Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to the growing appreciation of the roles of the host immunity system in tumor biology. However, the one-to-many c

Kingman Cheung, C. J. Ouseph

Neutrino-electron scattering experiments can explore the potential presence of a light gauge boson $A'$ which arises from an additional $U(1)_{B-L}$ group, or a dark photon $A'$ which arises from a dark sector and has kinetic mixing with the SM hypercharge gauge field. We generically call it a dark photon. In this study, we investigate the effect of the dark

Xinghui Zhou, Xin Jin, Jianwen Lv, Heng Huang

Image aesthetic quality assessment is popular during the last decade. Besides numerical assessment, nature language assessment (aesthetic captioning) has been proposed to describe the generally aesthetic impression of an image. In this paper, we propose aesthetic attribute assessment, which is the aesthetic attributes captioning, i.e., to assess the aestheti

Oliver Clarke, Akihiro Higashitani, Fatemeh Mohammadi

The Gelfand-Tsetlin and the Feigin-Fourier-Littelmann-Vinberg polytopes for the Grassmannians are defined, from the perspective of representation theory, to parametrize certain bases for highest weight irreducible modules. These polytopes are Newton-Okounkov bodies for the Grassmannian and, in particular, the GT-polytope is an example of a string polytope. T

Pranay K. Damuka, R. Aggarwal, M. Kaur

Analysis of the charged multiplicity in proton-proton inelastic interactions at the LHC energies in the setting of Dual Parton Model is presented. Data from the CMS experiment and the data simulated at different energies in various pseudo-rapidity windows using the event generator PYTHIA8are analysed and compared with the calculations from the model. Each in

Qile Chen, Felix Janda, Yongbin Ruan

In this paper, we develop the theory of punctured R-maps as a crucial component of logarithmic gauged linear sigma models (log GLSM). A punctured R-map is a punctured map in the sense of ACGS, further twisted by the sheaf of differentials on the domain curve. They admit two different but closely related perfect obstruction theories - a canonical one and a re

Zhilong Chen, Xiaochong Lan, Jinghua Piao, Yunke Zhang

In recent years, China has witnessed the proliferation and success of the online food delivery industry, an emerging type of the gig economy. Online food deliverers who deliver the food from restaurants to customers play a critical role in enabling this industry. Mediated by algorithms and coupled with interactions with multiple stakeholders, this emerging k

Xin Jin, Shu Zhao, Le Zhang, Xin Zhao

In recent years, image generation has made great strides in improving the quality of images, producing high-fidelity ones. Also, quite recently, there are architecture designs, which enable GAN to unsupervisedly learn the semantic attributes represented in different layers. However, there is still a lack of research on generating face images more consistent

Kai Jia, Martin Rinard, Yichen Yang

We present a new class of strategic games, mixed capability games, as a foundation for studying how different player capabilities impact the dynamics and outcomes of strategic games. We analyze the impact of different player capabilities via a capability transfer function that characterizes the payoff of each player at equilibrium given capabilities for all

Shuoguang Wang, Shiyong Li, Ahmad Hoorfar, Ke Miao

In the area of near-field millimeter-wave imaging, the generalized sparse array synthesis (SAS) method is in great demand. The traditional methods usually employ the greedy algorithms, which may have the convergence problem. This paper proposes a convex optimization model for the multiple-input multiple-output (MIMO) array design based on the compressive sen

Yongcheng Zong, Changhong Jing, Qiankun Zuo

The application of machine learning algorithms to the diagnosis and analysis of Alzheimer's disease (AD) from multimodal neuroimaging data is a current research hotspot. It remains a formidable challenge to learn brain region information and discover disease mechanisms from various magnetic resonance images (MRI). In this paper, we propose a simple but highl

HyoungSung Kim, Hyun-Sik Kim, Yong-Suk Park

Ethereum and its standardized token interface have formed decentralized finance (DeFi), an open financial system based on blockchain smart contracts. The DeFi ecosystem has become richer with the introduction of DeFi composability projects, such as Lido finance and Curve finance. DeFi composability denotes the concatenation of DeFi services in which each DeF

Yelai Feng, Huaixi Wang, Yining Zhu, Xiandong Liu

The shortest paths problem is a fundamental challenge in graph theory, with a broad range of potential applications. The algorithms based on matrix multiplication exhibits excellent parallelism and scalability, but is constrained by high memory consumption and algorithmic complexity. Traditional shortest paths algorithms are limited by priority queues, such

Prasad Sonar, Hiroaki Katsuragi

We experimentally investigate the effect of vertical vibrations on the brittle behavior of fine cohesive powders consisting of glass beads of 5 microns in diameter. This is an attempt to understand the sole role of vibrations in fluidizing Geldart's group C powders, which is known for posing difficulty while fluidization. We find that the cohesive powder col

Heng Kong, Shuqiang Wang

Mild cognitive impairment(MCI) is a precursor of Alzheimer's disease(AD), and the detection of MCI is of great clinical significance. Analyzing the structural brain networks of patients is vital for the recognition of MCI. However, the current studies on structural brain networks are totally dependent on specific toolboxes, which is time-consuming and subjec

He-Yi Li, Ren-You Zhang, Wen-Gan Ma, Yi Jiang

We present the NLO electroweak radiative corrections to the ee\gamma production in \gamma\gamma collision, which is an ideal channel for calibrating the beam luminosity of a Photon Linear Collider. We analyze the dependence of the total cross section on the beam colliding energy, and then investigate the kinematic distributions of final particles at various

Fan Hu, Dongqi Wang, Huazhen Huang, Yishen Hu

Drug discovery is vitally important for protecting human against disease. Target-based screening is one of the most popular methods to develop new drugs in the past several decades. This method efficiently screens candidate drugs inhibiting target protein in vitro, but it often fails due to inadequate activity of the selected drugs in vivo. Accurate computat