October 2022 arXiv papers — page 133

Chunhui Zhang, Yixiong Chen, Li Liu, Qiong Liu

The self-supervised ultrasound (US) video model pretraining can use a small amount of labeled data to achieve one of the most promising results on US diagnosis. However, it does not take full advantage of multi-level knowledge for learning deep neural networks (DNNs), and thus is difficult to learn transferable feature representations. This work proposes a h

Albert Yu, Raymond J. Mooney

Demonstrations and natural language instructions are two common ways to specify and teach robots novel tasks. However, for many complex tasks, a demonstration or language instruction alone contains ambiguities, preventing tasks from being specified clearly. In such cases, a combination of both a demonstration and an instruction more concisely and effectively

Matthew Deakin

The flexibility of multi-terminal AC-DC-AC converters connected in distribution networks can be increased by changing the sizes of the individual AC-DC converter stages and connecting the AC side of those converters to electromechanical switches (multiplexers) to allow reconfiguration within the network. The combinations of real powers that can be transferre

Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang

Semantic communication is an important participant in the next generation of wireless communications. Enabled by this novel paradigm, the conventional Internet-of-Things (IoT) is evolving toward the semantic IoT (SIoT) to achieve significant system performance improvements. However, traditional wireless communication security techniques for bit transmission

Zhuoxuan Jiang, Lingfeng Qiao, Di Yin, Shanshan Feng

Recent language generative models are mostly trained on large-scale datasets, while in some real scenarios, the training datasets are often expensive to obtain and would be small-scale. In this paper we investigate the challenging task of less-data constrained generation, especially when the generated news headlines are short yet expected by readers to keep

Kshitij Sirohi, Sajad Marvi, Daniel Büscher, Wolfram Burgard

Modern autonomous systems often rely on LiDAR scanners, in particular for autonomous driving scenarios. In this context, reliable scene understanding is indispensable. Current learning-based methods typically try to achieve maximum performance for this task, while neglecting a proper estimation of the associated uncertainties. In this work, we introduce a no

Yonatan Yehezkeally, Daniella Bar-Lev, Sagi Marcovich, Eitan Yaakobi

This paper introduces a new family of reconstruction codes which is motivated by applications in DNA data storage and sequencing. In such applications, DNA strands are sequenced by reading some subset of their substrings. While previous works considered two extreme cases in which all substrings of pre-defined lengths are read or substrings are read with no o

Shalabh Bhatnagar, Vivek S. Borkar, Soumyajit Guin

We revisit the standard formulation of tabular actor-critic algorithm as a two time-scale stochastic approximation with value function computed on a faster time-scale and policy computed on a slower time-scale. This emulates policy iteration. We observe that reversal of the time scales will in fact emulate value iteration and is a legitimate algorithm. We pr

Simona Korenjak-Černe, Nataša Kejžar

The study of mortality patterns is a popular research topic in many areas. We are particularly interested in mortality patterns among main causes of death associated with age-gender combinations. We use symbolic data analysis (SDA) and include three dimensions: age, gender, and patterns across main causes of death. In this study, we present an alternative me

Ru Peng, Yawen Zeng, Junbo Zhao

Past works on multimodal machine translation (MMT) elevate bilingual setup by incorporating additional aligned vision information. However, an image-must requirement of the multimodal dataset largely hinders MMT's development -- namely that it demands an aligned form of [image, source text, target text]. This limitation is generally troublesome during the in

Veysel Çelik

The hybrid halide perovskite CH$_3$NH$_3$PbI$_3$ is easy to manufacture and inexpensive. Despite these, its efficiency as a solar cell is comparable to today's efficient solar cells. For these reasons, it is attracting a lot of attention today. However, the effects of the CH$_3$NH$_3^+$ (MA) molecule in the perovskite structure on the electronic and structur

Swaroop Mishra, Anjana Arunkumar, Chitta Baral

With the increasing importance of safety requirements associated with the use of black box models, evaluation of selective answering capability of models has been critical. Area under the curve (AUC) is used as a metric for this purpose. We find limitations in AUC; e.g., a model having higher AUC is not always better in performing selective answering. We pro

Pablo G. Ortega, David R. Entem, Francisco Fernandez

Hidden-charm pentaquark-like $P_{\psi s}^\Lambda(4459)^0$ and $P_{\psi s}^\Lambda(4338)$ resonances are studied in a constituent quark model as molecular meson-baryon structures. Such states are found in the $J^P(I)=\frac{1}{2}^-(0)$ channel with masses and widths compatible with the experimental measurements in a coupled-channels calculation with all the pa

Xiao-Yun Wang, Jiyuan Zhang

Generally, multi-particle spring system is an important and widely used physical model. However, with the increase of the number of particles, the difficulty of solving the kinematic trajectory of the particles becomes more and more difficult. The key to solving this problem lies in whether it is possible to construct a dynamic model of the multi-particle sp

Giulio G. Giusteri, Raimondo Penta

In the design and analysis of composite materials based on periodic arrangements of sub-units it is of paramount importance to control the emergent material symmetry in relation to the elastic response. The target material symmetry plays also an important role in additive manufacturing. In numerous applications it would be useful to obtain effectively isotro

Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart

We describe a new transit detection algorithm designed to detect single transit events in discontinuous Perkins INfrared Exosatellite Survey (PINES) observations of L and T dwarfs. We use this algorithm to search for transits in 131 PINES light curves and identify two transit candidates: 2MASS J18212815+1414010 (2MASS J1821+1414) and 2MASS J08350622+1953050

J. Tian, J. Hong, Y. Li, M. D. Ding

Context. Radiative losses are an indispensable part in the numerical simulation of flares. Detailed calculations could be computationally expensive, especially in the chromosphere. There have been some approximate recipes for chromospheric radiative losses in flares, yet their feasibility in flare simulations needs further evaluation. Aims. We aim to evaluat

Frederick A. Gent, Mordecai-Mark Mac Low, Maarit J. Korpi-Lagg, Nishant K. Singh

Magnetic fields grow quickly, even at early cosmological times, suggesting the action of a small-scale dynamo (SSD) in the interstellar medium (ISM) of galaxies. Many studies have focused on idealized, isotropic, homogeneous, turbulent driving of the SSD. Here we analyze more realistic simulations of supernova-driven turbulence to understand how it drives an

Jan Wiersig

Higher-order exceptional points in the spectrum of non-Hermitian Hamiltonians describing open quantum or wave systems have a variety of potential applications in particular in optics and photonics. However, the experimental realization is notoriously difficult. Recently, Q. Zhong et al. [Phys. Rev. Lett. 125, 203602 (2020)] have introduced a robust construct

Ziyang Song, Bo Yang

In this paper, we study the problem of 3D object segmentation from raw point clouds. Unlike all existing methods which usually require a large amount of human annotations for full supervision, we propose the first unsupervised method, called OGC, to simultaneously identify multiple 3D objects in a single forward pass, without needing any type of human annota

Fang Ma, Chen Zhang, Lei Ren, Jingang Wang

Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gradually reached the performance level of fine-tuning as the model scale increases, there is still a large performance gap between prompt tuning and fine-tuning for models of modera

Dr Brendan Walker-Munro, Dr Zena Assaad

As human science pushes the boundaries towards the development of artificial intelligence (AI), the sweep of progress has caused scholars and policymakers alike to question the legality of applying or utilising AI in various human endeavours. For example, debate has raged in international scholarship about the legitimacy of applying AI to weapon systems to f

Dan Wang

Let $(X, \omega, J)$ be a toric variety of dimension $2n$ determined by a Delzant polytope. In this paper, we first construct the polarizations $\shP_{k}$ by the Hamiltonian $T^{k}$-action on $X$ (see Theorem 3.11). We will show that $\shP_{k}$ is a singular mixed polarization for $1\le k < n$, and $\shP_{n}$ is a singular real polarization which coincides w

Taras Skrypnyk

We show that the Lipkin-Meshkov-Glick $2N$-fermion model is a particular case of one-spin Gaudin-type model in an external magnetic field corresponding to a limiting case of non-skew-symmetric elliptic $r$-matrix and to an external magnetic field directed along one axis. We propose an exactly-solvable generalization of the Lipkin-Meshkov-Glick fermion model

Roxana Zahedi Nasab, Mohammad Reza Eftekhariyan Ghamsari, Ahmadreza Argha, Callum Macphillamy

Spatially resolved transcriptomics (SRT) has evolved rapidly through various technologies, enabling scientists to investigate both morphological contexts and gene expression profiling at single-cell resolution in parallel. SRT data are complex and multi-modal, comprising gene expression matrices, spatial information, and often high-resolution histology image

Priyanka Majumder, Anna-Maria von Pippich

Let $\Gamma$ be a cofinite Fuchsian subgroup. The canonical Green's function associated with $\Gamma$ arises in Arakelov theory when establishing asymptotics for Arakelov invariants of the modular curve associated with some congruence subgroup of level $N$ with a positive integer $N$. More precisely, in the known cases, canonical Green's functions at certain

Nicolas Gisin

I argue against the many-world interpretation (MWI) of quantum theory by emphasizing that when everything is entangled with everything else, in one big monstrous piece, there is no room left for creativity. Since the MWI was invented, it proves itself wrong (appeared first in French in [N. Gisin, L'\'epid\'emie du multivers, in Le plus grand des hasards, p.

Ryder Dale Walton

The purpose of this work is to contribute toward the larger goal of creating a Quantum Natural Language Processing (QNLP) translator program. This work contributes original diagrammatic representations of the Japanese language based on prior work that accomplished on the English language based on category theory. The germane differences between the English a

Lachlan Ewen MacDonald, Jack Valmadre, Hemanth Saratchandran, Simon Lucey

We introduce a general theoretical framework, designed for the study of gradient optimisation of deep neural networks, that encompasses ubiquitous architecture choices including batch normalisation, weight normalisation and skip connections. Our framework determines the curvature and regularity properties of multilayer loss landscapes in terms of their const

Dori Bejleri, Jun-Yong Park, Matthew Satriano

For proper stacks, unlike schemes, there is a distinction between rational and integral points. Moreover, rational points have extra automorphism groups. We show that these distinctions exactly account for the lower order main terms appearing in precise counts of elliptic curves over function fields, answering a question of Venkatesh in this case. More gener

Yu Wei Tan, Nicholas Chua, Clarence Koh, Anand Bhojan

Signed Distance Fields (SDFs) for surface representation are commonly generated offline and subsequently loaded into interactive applications like games. Since they are not updated every frame, they only provide a rigid surface representation. While there are methods to generate them quickly on GPU, the efficiency of these approaches is limited at high resol

Shiwei Wang, Chao Ding, Yangjing Zhang, Xinyuan Zhao

Strong variational sufficiency is a newly proposed property, which turns out to be of great use in the convergence analysis of multiplier methods. However, what this property implies for non-polyhedral problems remains a puzzle. In this paper, we prove the equivalence between the strong variational sufficiency and the strong second order sufficient condition

Momchil Hardalov, Anton Chernyavskiy, Ivan Koychev, Dmitry Ilvovsky

While there has been substantial progress in developing systems to automate fact-checking, they still lack credibility in the eyes of the users. Thus, an interesting approach has emerged: to perform automatic fact-checking by verifying whether an input claim has been previously fact-checked by professional fact-checkers and to return back an article that exp

Akkarapakam Suneesh Jacob, Bhaskar Dasgupta

Dimensional synthesis refers to design of the dimensions of manipulators by optimising different kinds of performance indices. The motivation of this study is to perform dimensional synthesis for a wide set of spatial manipulators by optimising the manipulability of each manipulator around a pre-defined task point in the workspace and to finally give a presc

Sneha Thomas, Kevin S. Silmore, Ananth Govind Rajan

Nanopores in two-dimensional (2D) materials, including graphene, can be used for a variety of applications, such as gas separations, water desalination, and DNA sequencing. So far, however, all plausible isomeric shapes of graphene nanopores have not been enumerated. Instead, a probabilistic approach has been followed to predict nanopore shapes in 2D materia

Prakash A. Dabhi, Karishman B. Solanki

Let $0<p\leq 1$, $\omega$ be a weight on $\mathbb Z$, and let $\mathcal A$ be a unital Banach algebra. If $f$ is a continuous function from the unit circle $\mathbb T$ to $\mathcal A$ such that $\sum_{n\in \mathbb Z} \|\widehat f(n)\|^p \omega(n)^p<\infty$ and $f(z)$ is left invertible for all $z \in \mathbb T$, then there is a weight $\nu$ on $\mathbb Z$ an

So Yeon Min, Hao Zhu, Ruslan Salakhutdinov, Yonatan Bisk

Embodied dialogue instruction following requires an agent to complete a complex sequence of tasks from a natural language exchange. The recent introduction of benchmarks (Padmakumar et al., 2022) raises the question of how best to train and evaluate models for this multi-turn, multi-agent, long-horizon task. This paper contributes to that conversation, by ar

Qiuchen Zhang, Hong kyu Lee, Jing Ma, Jian Lou

Graph Neural Networks (GNNs) have achieved great success in learning with graph-structured data. Privacy concerns have also been raised for the trained models which could expose the sensitive information of graphs including both node features and the structure information. In this paper, we aim to achieve node-level differential privacy (DP) for training GNN

Osman B. Guney, Suayb S. Arslan

In this study, we propose a simple method for fault-tolerant Strassen-like matrix multiplications. The proposed method is based on using two distinct Strassen-like algorithms instead of replicating a given one. We have realized that using two different algorithms, new check relations arise resulting in more local computations. These local computations are fo

Kevin Huang, Shuzhong Zhang

In this paper, we propose a general extra-gradient scheme for solving monotone variational inequalities (VI), referred to here as Approximation-based Regularized Extra-gradient method (ARE). The first step of ARE solves a VI subproblem with an approximation operator satisfying a $p^{th}$-order Lipschitz bound with respect to the original mapping, further cou

Debargha Banerjee, Loïc Merel

For $N$ integer $\ge1$, K. Murty and D. Ramakrishnan defined the $N$-th Heisenberg curve, as the compactified quotient $X'_N$ of the upper half-plane by a certain non-congruence subgroup of the modular group. They ask whether the Manin-Drinfeld principle holds, namely if the divisors supported on the cusps of those curves are torsion in the Jacobian. We give

Dylan Langharst, Eli Putterman

The inequality of Berwald is a reverse-H\"older like inequality for the $p$th average, $p\in (-1,\infty),$ of a non-negative, concave function over a convex body in $\mathbb{R}^n.$ We prove Berwald's inequality for averages of functions with respect to measures that have some concavity conditions, e.g. $s$-concave measures, $s\in \mathbb{R}.$ We also obtain

L. Cardona-Torres, I. Aretxaga, A. Montaña, J. A. Zavala

We present a demographic analysis of the physical and morphological properties of $450/850~\mu\rm m$-selected galaxies from the deep observations of the SCUBA-2 Cosmology Legacy Survey in the Extended Groth Strip that are detected below the classical submillimeter-galaxy regime ($S_{850 \mu\rm m}\lesssim 6~\rm mJy$/beam) and compare them with a sample of opt

Zachary Miller, Kevin Johnson

Purpose: To investigate motion compensated, self-supervised, model based deep learning (MBDL) as a method to reconstruct free breathing, 3D Pulmonary ultrashort echo time (UTE) acquisitions. Theory and Methods: A self-supervised eXtra Dimension MBDL architecture (XD-MBDL) was developed that combined respiratory states to reconstruct a single high-quality 3D

Xiaoyu Huang, Zhongyu Li, Yanzhen Xiang, Yiming Ni

We present a reinforcement learning (RL) framework that enables quadrupedal robots to perform soccer goalkeeping tasks in the real world. Soccer goalkeeping using quadrupeds is a challenging problem, that combines highly dynamic locomotion with precise and fast non-prehensile object (ball) manipulation. The robot needs to react to and intercept a potentially

Abduljaleel Al-Rubaye, Gita Sukthankar

Software quality is an important problem for technology companies, since it substantially impacts the efficiency, usefulness, and maintainability of the final product; hence, code review is a must-do activity for software developers. During the code review process, senior engineers monitor other developers' work to spot possible problems and enforce coding s

Zhiguang Zhao

In the present article, we extend the fragment of inductive formulas for the hybrid language L(@) in [8] including a McKinsey-like formula, and show that every formula in the extended class has a first-order correspondent, by modifying the algorithm hybrid-ALBA in [8]. We also identify a subclass of this extended inductive fragment, namely the extended skele

Kavisha Vidanapathirana, Peyman Moghadam, Sridha Sridharan, Clinton Fookes

In large-scale metric localization, an incorrect result during retrieval will lead to an incorrect pose estimate or loop closure. Re-ranking methods propose to take into account all the top retrieval candidates and re-order them to increase the likelihood of the top candidate being correct. However, state-of-the-art re-ranking methods are inefficient when re

Kyle R. Lennon, Gareth H. McKinley, James W. Swan

The formulation of rheological constitutive equations -- models that relate internal stresses and deformations in complex fluids -- is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disc

Yongbin Ruan, Cheng Shu

We study the geometry of singular $\text{SL}_n$-Hitchin fibres over the elliptic locus. We show that orbifold singularities appear in the $\text{PGL}_n$-moduli space $M^{ell}(\text{PGL}_n)$ exactly when the $\text{SL}_n$ side $M^{ell}(\text{SL}_n)$ has a reducible Hitchin fibre. Our main theorem shows that the Fourier-Mukai transform of a skyscraper sheaf su

Zeeshan Khan, Parth Shettiwar, Mukul Khanna, Shanmuganathan Raman

Due to hardware constraints, standard off-the-shelf digital cameras suffers from low dynamic range (LDR) and low frame per second (FPS) outputs. Previous works in high dynamic range (HDR) video reconstruction uses sequence of alternating exposure LDR frames as input, and align the neighbouring frames using optical flow based networks. However, these methods

Dario G. Soatto

I study the role of minimum wage as an anchor for judgements of the fairness of wages by both human subjects and artificial intelligence (AI). Through surveys of human subjects enrolled in the crowdsourcing platform Prolific.co and queries submitted to the OpenAI's language model GPT-3, I test whether the numerical response for what wage is deemed fair for a

Paul Janson, Wenxuan Zhang, Rahaf Aljundi, Mohamed Elhoseiny

With the success of pretraining techniques in representation learning, a number of continual learning methods based on pretrained models have been proposed. Some of these methods design continual learning mechanisms on the pre-trained representations and only allow minimum updates or even no updates of the backbone models during the training of continual lea

Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li

Knowledge Distillation (KD) aims at transferring the knowledge of a well-performed neural network (the {\it teacher}) to a weaker one (the {\it student}). A peculiar phenomenon is that a more accurate model doesn't necessarily teach better, and temperature adjustment can neither alleviate the mismatched capacity. To explain this, we decompose the efficacy of

Taeyong Kim, Soyeon Park, Vasudevan Iyer, Qi Jiang

Organic-inorganic hybrid perovskites (OIHPs) exhibiting exceptional photovoltaic and optoelectronic properties are of fundamental and practical interest, owing to their tunability and low manufacturing cost. For practical applications, however, challenges such as material instability and the photocurrent hysteresis occurring in perovskite solar cells under l

Vladimir Dzhunushaliev, Vladimir Folomeev, Burkhard Kleihaus, Jutta Kunz

We present rapidly rotating neutron stars featuring wormholes in their centers. They arise in general relativity in the presence of a ghost scalar field. The nuclear matter is described by a polytropic equation of state, yielding realistic masses and radii for the neutron stars. The wormholes possess small circumferential radii of size up to 3 km. With incre

Kenta Noguchi

We completely characterize triangulations of the projective plane that have a spanning bipartite quadrangulation subgraph. This is an affirmative answer to a question by K\"undgen and Ramamurthi (J Combin Theory Ser B 85, 307--337, 2002) for the projective planar case.

Vei Wang, Gang Tang, Ya-Chao Liu, Yun-Ye Liang

To overcome current serious energy and environmental issues, photocatalytic water splitting holds great promise because it requires only solar energy as an energy input to produce hydrogen. Two-dimensional (2D) semiconductors and heterostructures possess several inherent advantages which are more suitable for boosting solar energy than their bulk counterpart

Weihua Li, Hongwei Zheng

Despite the growing importance of teams in producing innovative and high-impact science and technology, it remains unclear how expertise diversity among team members relates to the originality and impact of the work they produce. Here, we develop a new method to quantify the expertise distance of researchers based on their prior career histories and apply it

Simin Chen, Mirazul Haque, Cong Liu, Wei Yang

Today, an increasing number of Adaptive Deep Neural Networks (AdNNs) are being used on resource-constrained embedded devices. We observe that, similar to traditional software, redundant computation exists in AdNNs, resulting in considerable performance degradation. The performance degradation is dependent on the input and is referred to as input-dependent pe

Vipin Kumar, Nishant Goyal, Abhishek Prasad, Suresh Babu

Pollen grains represent the male gametes of seed plants and their viability is critical for efficient sexual reproduction in the plant life cycle. Pollen analysis is used in diverse research thematics to address a range of botanical, ecological and geological questions. More recently it has been recognized that pollen may also be a vector for transgene escap

Jeremy Taylor

Geometric Langlands predicts an isomorphism between Whittaker coefficients of Eisenstein series and functions on the moduli space of $\check{N}$-local systems. We prove this formula by interpreting Whittaker coefficients of Eisenstein series as factorization homology and then invoking Beilinson and Drinfeld's formula for chiral homology of a chiral envelopin

Yongliang Sun, Yaohua Zhang

We provide a technique to glue simple-minded collections along a recollement of Hom-finite Krull-Schmidt triangulated categories over a field. This gluing technique for simple-minded collections is shown to be compatible with those for gluing bounded $t$-structures, silting objects, and co-$t$-structures in the literature. Furthermore, it also enjoys the pro

Mark Whitmeyer

We study what changes to an agent's decision problem increase her value for information. We prove that information becomes more valuable if and only if the agent's reduced-form payoff in her belief becomes more convex. When the transformation corresponds to the addition of an action, the requisite increase in convexity occurs if and only if a simple geometri

Maryam Paparimoghadamborazjani, Amin Kazemi

Undoubtedly, social media are brainstormed by a tremendous volume of stories, feedback, reviews, and reactions expressed in various languages and idioms, even though some are factually incorrect. These motifs make assessing such data challenging, time-consuming, and vulnerable to misinterpretation. This paper describes a classification model for movie review

Dingwen Li, Bing Xue, Christopher King, Bradley Fritz

Major postoperative complications are devastating to surgical patients. Some of these complications are potentially preventable via early predictions based on intraoperative data. However, intraoperative data comprise long and fine-grained multivariate time series, prohibiting the effective learning of accurate models. The large gaps associated with clinical

Courtney L. Crawford, Patrick Tisserand, Geoffrey C. Clayton, Jamie Soon

Stellar spectral classification has been highly useful in the study of stars. While there is a currently accepted spectral classification system for carbon stars, the subset of Hydrogen-deficient Carbon (HdC) stars has not been well described by such a system, due predominantly to their rarity and their variability. Here we present the first system for the c

Fu-Quan Dou, Fang-Mei Yang

Quantum battery (QB) is the miniature energy storage and release device and plays a crucial role in future quantum technology. Here, an implementation scheme of a QB is proposed on a superconducting circuit which is composed by $N$ coupled transmon qubits and a one-dimensional transmission line resonator. We derive the Hamiltonian of the QB system and invest

Adriano Valdés Gómez, Francisco J. Sevilla

We analyze \emph{fractional Brownian motion} and \emph{scaled Brownian motion} on the two-dimensional sphere $\mathbb{S}^{2}$. We find that the intrinsic long time correlations that characterize fractional Brownian motion collude with the specific dynamics (\emph{navigation strategies}) carried out on the surface giving rise to rich transport properties. We

Junfu Guo, Changhao Li, Xi Xia, Ruizhen Hu

When conducting autonomous scanning for the online reconstruction of unknown indoor environments, robots have to be competent at exploring scene structure and reconstructing objects with high quality. Our key observation is that different tasks demand specialized scanning properties of robots: rapid moving speed and far vision for global exploration and slow

Kazuki Yokomizo, Shuichi Murakami

The non-Bloch band theory can describe energy bands in a one-dimensional (1D) non-Hermitian system. On the other hand, whether the non-Bloch band theory can be extended to higher-dimensional non-Hermitian systems is nontrivial. In this work, we construct the non-Bloch band theory in two classes of two-dimensional non-Hermitian systems, by reducing the proble

Atsuki Kumashita, Hiroo Tajiri, Akira Yamaguchi, Jun Usami

We carried out simulations of crystal truncation rod (CTR) scatterings, i.e., one of the surface X-ray diffraction techniques with atomic resolution, from a monolayer He film adsorbed on graphite. Our simulations reveal that the 00L rod scatterings from the He monolayer exhibit notable intensity modifications for those from a graphite surface in the ranges o

Minghui Liwang, Zhipeng Cheng, Wei Gong, Li Li

The challenge of exchanging and processing of big data over mobile crowdsensing (MCS) networks calls for designing seamless data service provisioning mechanisms to enable utilization of resources of mobile devices/users for crowdsensing tasks. Although conventional onsite spot trading of resources based on real-time network conditions can facilitate data sha

Qiong Liu, Ye Guo, Lirong Deng, Haotian Liu

Reference-model-assisted deep reinforcement learning (DRL) for inverter-based Volt-Var Control (IB-VVC) in active distribution networks is proposed. We investigate that a large action space increases the learning difficulties of DRL and degrades the optimization performance in the process of generating data and training neural networks. To reduce the action

Rong Lu

IMPORTANCE: Feature selection with respect to time-to-event outcomes is one of the fundamental problems in clinical trials and biomarker discovery studies. But it's unclear which statistical methods should be used when sample size is small or some of the key covariates are not measured. DESIGN: In this simulation study, the true models are multivariate Cox p

Fan Zhang, Asmaul Smitha Rashid, Mostafa Tanhayi Ahari, Wei Zhang

There is growing interest in using multi-terminal Josephson junctions (MTJJs) as a platform to artificially emulate topological phases and to investigate complex superconducting mechanisms such as quartet and multiplet Cooper pairings. Current experimental signatures in MTJJs have led to conflicting interpretations of the salient features. In this work, we r

Lucy O. McNeill, Naoki Seto

We propose a novel method to examine whether Galactic double neutron star binaries are formed in the LISA band. In our method, we assign an effective time fraction $\tau$ to each double neutron star binary detected by LISA. This fraction is given as a function of the observed orbital period and eccentricity and should be uniformly distributed in the absence

Hongyi Zheng, Yanyu Chen, Zihan Zhang

Our project probes the relationship between temperatures and the blossom date of cherry trees. Through modeling, future flowering will become predictive, helping the public plan travels and avoid pollen season. To predict the date when the cherry trees will blossom exactly could be viewed as a multiclass classification problem, so we applied the multi-class

Yunlei Liang, Jiawei Zhu, Wen Ye, Song Gao

Community Detection algorithms are used to detect densely connected components in complex networks and reveal underlying relationships among components. As a special type of networks, spatial networks are usually generated by the connections among geographic regions. Identifying the spatial network communities can help reveal the spatial interaction patterns

William Chang, Hanjie Ji

Thin film rupture is a type of nonlinear instability that causes the solution to touch down to zero at finite time. We investigate the finite-time rupture behavior of a generalized elastohydrodynamic lubrication model. This model features the interplay between destabilizing disjoining pressure and stabilizing elastic bending pressure and surface tension. The

Arvind Balachandrasekaran, Davood Karimi, Camilo Jaimes, Ali Gholipour

Quantitative Susceptibility Mapping is a parametric imaging technique to estimate the magnetic susceptibilities of biological tissues from MRI phase measurements. This problem of estimating the susceptibility map is ill posed. Regularized recovery approaches exploiting signal properties such as smoothness and sparsity improve reconstructions, but suffer from

Ekta Gujral

Graphs emerge in almost every real-world application domain, ranging from online social networks all the way to health data and movie viewership patterns. Typically, such real-world graphs are big and dynamic, in the sense that they evolve over time. Furthermore, graphs usually contain multi-aspect information i.e. in a social network, we can have the "means

Haneul Kwak, Jong Heum Jung, Yong-il Shin

When a superfluid flows past an obstacle, quantized vortices can be created in the wake above a certain critical velocity. In the experiment by Kwon et al. [Phys. Rev. A 91, 053615 (2015)], the critical velocity $v_c$ was measured for atomic Bose-Einstein condensates (BECs) using a moving repulsive Gaussian potential and $v_c$ was minimized when the potentia

Shichao Kan, Zhiquan He, Yigang Cen, Yang Li

Recent methods for deep metric learning have been focusing on designing different contrastive loss functions between positive and negative pairs of samples so that the learned feature embedding is able to pull positive samples of the same class closer and push negative samples from different classes away from each other. In this work, we recognize that there

Wei-Yang Wang, Jin-Chen Jiang, Kejia Lee, Renxin Xu

Fast radio busts (FRBs) can exhibit a wide variety of polarisation properties, not only between sources but also from burst to burst for a same one. In this work, we revisit the polarisation characters of coherent curvature radiation from a bulk of charged bunches in the magnetosphere of a highly magnetized neutron star. FRBs have been observed to have a var

Eason Chen, Yuen Hsien Tseng, Kuo-Ping Lo

Distance teaching has become popular these years because of the COVID-19 epidemic. However, both students and teachers face several challenges in distance teaching, like being easy to distract. We proposed Focus+, a system designed to detect learners' status with the latest AI technology from their web camera to solve such challenges. By doing so, teachers c

Han Chen, Yifan Jiang, Hanseok Ko

Graph convolutional networks (GCNs), which can model the human body skeletons as spatial and temporal graphs, have shown remarkable potential in skeleton-based action recognition. However, in the existing GCN-based methods, graph-structured representation of the human skeleton makes it difficult to be fused with other modalities, especially in the early stag

Sujuan Hou, Jiacheng Li, Weiqing Min, Qiang Hou

When logos are increasingly created, logo detection has gradually become a research hotspot across many domains and tasks. Recent advances in this area are dominated by deep learning-based solutions, where many datasets, learning strategies, network architectures, etc. have been employed. This paper reviews the advance in applying deep learning techniques to

Anji Liu, Honghua Zhang, Guy Van den Broeck

Probabilistic Circuits (PCs) are a unified framework for tractable probabilistic models that support efficient computation of various probabilistic queries (e.g., marginal probabilities). One key challenge is to scale PCs to model large and high-dimensional real-world datasets: we observe that as the number of parameters in PCs increases, their performance i

Minghao Shen, R. Austin Dollar, Tamas G. Molnar, Chaozhe R. He

In this paper, we propose a framework for the longitudinal control of connected and automated vehicles traveling in mixed traffic consisting of connected and non-connected human-driven vehicles. Reactive and predictive controllers are proposed. Reactive controllers are given by explicit feedback control laws. In predictive controllers, the control input is o

Sorin Popa

Given an inclusion of II$_1$ factors $N\subset M$ with finite Jones index, $[M:N]<\infty$, we prove that for any $F\subset M$ finite and $\varepsilon >0$, there exists a partition of $1$ with $r\leq \lceil 16\varepsilon^{-2}\rceil$ $\cdot \lceil 4 [M:N]\varepsilon^{-2}\rceil$ projections $p_1, ..., p_r\in N$ such that $\|\sum_{i=1}^r p_ixp_i - E_{N'\cap M}(x

Susanna V. Haziot, Benoît Pausader

We consider the dissipation of the Muskat problem and we give an elementary proof of a surprising inequality of Constantin-Cordoba-Gancedo-Strain which holds in greater generality.

Gee-Choon Lau, Wai-Chee Shiu, Ruixue Zhang, K. Premalatha

An edge labeling of a connected graph $G = (V, E)$ is said to be local antimagic if it is a bijection $f:E \to\{1,\ldots ,|E|\}$ such that for any pair of adjacent vertices $x$ and $y$, $f^+(x)\not= f^+(y)$, where the induced vertex label $f^+(x)= \sum f(e)$, with $e$ ranging over all the edges incident to $x$. The local antimagic chromatic number of $G$, de

Mai Nguyen, Tung Thanh Bui, Quan Van Nguyen, Thanh Tung Nguyen

Polyp segmentation is still known as a difficult problem due to the large variety of polyp shapes, scanning and labeling modalities. This prevents deep learning model to generalize well on unseen data. However, Transformer-based approach recently has achieved some remarkable results on performance with the ability of extracting global context better than CNN

Zhiyuan Tong, Farid H. Benvidi, Mattia Bacca

Strong adhesives rely on reduced stress concentrations, often obtained via specific geometry or composition of materials. In many examples in nature and engineering prototypes, the adhesive performance relies on structural rigidity being placed in specific locations. A few design principles have been formulated, based on parametric optimization, while a gene

Iosif Pinelis

Spherical symmetry arguments are used to produce a general device to convert identities and inequalities for the $p$th absolute moments of real-valued random variables into the corresponding identities and inequalities for the $p$th moments of the norms of random vectors in Hilbert spaces. Particular results include the following: (i) an expression of the $p

Luca Innocenti, Lukas Lachman, Radim Filip

The nonclassicality of quantum states is a fundamental resource for quantum technologies and quantum information tasks in general. In particular, a pivotal aspect of quantum states lies in their coherence properties, encoded in the nondiagonal terms of their density matrix in the Fock-state bosonic basis. We present operational criteria to detect the nonclas

Siqi Xu, Lin Liu, Zhonghua Liu

Causal mediation analysis can unpack the black box of causality and is therefore a powerful tool for disentangling causal pathways in biomedical and social sciences, and also for evaluating machine learning fairness. To reduce bias for estimating Natural Direct and Indirect Effects in mediation analysis, we propose a new method called DeepMed that uses deep

Hai-Ming Xu, Lingqiao Liu, Qiuchen Bian, Zhen Yang

Semi-supervised semantic segmentation requires the model to effectively propagate the label information from limited annotated images to unlabeled ones. A challenge for such a per-pixel prediction task is the large intra-class variation, i.e., regions belonging to the same class may exhibit a very different appearance even in the same picture. This diversity

A. Hofstrand, H. Li, M. I. Weinstein

In this work, we study the dynamics of an infinite array of nonlinear dimer oscillators which are linearly coupled as in the classical model of Su, Schrieffer and Heeger (SSH). The ratio of in-cell and out-of-cell couplings of the SSH model defines distinct $\textit{phases}$: topologically trivial and topologically non-trivial. We first consider the case of