May 2022 arXiv papers — page 75

Paul Poncet

We recall the notion of abstract bornology, and connect it with topological spaces and size functions. As a generalization of measures of non-compactness, we show how every size function can be mapped to a maxitive measure.

Simone Ceppi, Nicolás Cuello, Giuseppe Lodato, Cathie Clarke

Young multiple systems accrete most of their final mass in the first few Myr of their lifetime, during the protostellar and protoplanetary phases. Previous studies showed that in binary systems the majority of the accreted mass falls onto the lighter star, thus evolving to mass equalisation. However, young stellar systems often comprise more than two stars,

Yao Li, Vinu Kamalasanan, Mariana Batista, Monika Sester

The shared space design is applied in urban streets to support barrier-free movement and integrate traffic participants (such as pedestrians, cyclists and vehicles) into a common road space. Regardless of the low-speed environment, sharing space with motor vehicles can make vulnerable road users feel uneasy. Yet, walking in groups increases their confidence

Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller

Inverse probability problems whose generative models are given by strictly nonlinear Gaussian random fields show the all-or-nothing behavior: There exists a critical rate at which Bayesian inference exhibits a phase transition. Below this rate, the optimal Bayesian estimator recovers the data perfectly, and above it the recovered data becomes uncorrelated. T

Liujun Xu, Jinrong Liu, Peng Jin, Guoqiang Xu

Black holes are one of the most intriguing predictions of general relativity. So far, metadevices have enabled analogous black holes to trap light or sound in laboratory spacetime. However, trapping heat in a conductive ambient is still challenging because diffusive behaviors are directionless. Inspired by black holes, we construct graded heat-conduction met

Jie Xiang, Yun Wang, Lifeng An, Haiyang Liu

Although existing monocular depth estimation methods have made great progress, predicting an accurate absolute depth map from a single image is still challenging due to the limited modeling capacity of networks and the scale ambiguity issue. In this paper, we introduce a fully Visual Attention-based Depth (VADepth) network, where spatial attention and channe

Tue Herlau

The most fundamental problem in statistical causality is determining causal relationships from limited data. Probability trees, which combine prior causal structures with Bayesian updates, have been suggested as a possible solution. In this work, we quantify the information gain from a single intervention and show that both the anticipated information gain,

Masaki Yasuhara, Isao Nambu, Yoshiko Maruyama, Shohei Yano

In existing biometric authentication methods, the user must perform an authentication operation such as placing a finger in a scanner or facing a camera. With ear acoustic authentication, acoustic characteristics of the ear canal are used as biometric information. Therefore, a person wearing earphones does not need to perform any authentication operation. In

Deepak Chaurasiya, Anil Surisetty, Nitish Kumar, Alok Singh

Entity Alignment (EA) identifies entities across databases that refer to the same entity. Knowledge graph-based embedding methods have recently dominated EA techniques. Such methods map entities to a low-dimension space and align them based on their similarities. With the corpus of EA methodologies growing rapidly, this paper presents a comprehensive analysi

Juyong Jiang, Peiyan Zhang, Yingtao Luo, Chaozhuo Li

Sequential recommendation (SR) aims to model users dynamic preferences from a series of interactions. A pivotal challenge in user modeling for SR lies in the inherent variability of user preferences. An effective SR model is expected to capture both the long-term and short-term preferences exhibited by users, wherein the former can offer a comprehensive unde

Abhisek Ghosal, Amlan K. Roy

In this communication, we present a new approach towards RT-TDDFT through time-dependent KS equations based on an \emph{adiabatic eigenstate subspace} (AES) procedure. It introduces a second-order split operator technique in energy representation to implement the approximate TD propagator in AES. Most of the elements in TDKS matrix are directly computed in C

Chintan Jansari, Stéphane P. A. Bordas, Elena Atroshchenko

There has been a growing interest in controlled heat flux manipulation to increase the efficiency of thermal apparatus. Heat manipulators control and manipulate heat flow. A key to the effective performance of these heat manipulators is their thermal design. Such designs can be achieved by a periodic assembly of unit cells (known as metamaterials or meta-str

Luca Becchetti, Andrea Clementi, Francesco Pasquale, Luca Trevisan

\emph{Full-bond percolation} with parameter $p$ is the process in which, given a graph, for every edge independently, we delete the edge with probability $1-p$. Bond percolation is motivated by problems in mathematical physics and it is studied in parallel computing and network science to understand the resilience of distributed systems to random link failur

Jing Ma, Ronghui Wu

Let $f$ be an arithmetic function satisfying some simple conditions. The aim of this paper is to establish an asymptotical formula for the quantity \[ S_f(x):=\sum_{n\leq x}\frac{f([x/n])}{[x/n]} \] as $x\rightarrow\infty$, where $[t]$ is the integral part of the real number $t$. This generalizes some recent results of Bordell\`es, Dai, Heyman, Pan and Shpar

Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng

Cross-domain sentiment classification (CDSC) aims to use the transferable semantics learned from the source domain to predict the sentiment of reviews in the unlabeled target domain. Existing studies in this task attach more attention to the sequence modeling of sentences while largely ignoring the rich domain-invariant semantics embedded in graph structures

Hung-Jui Huang, Xiaofeng Guo, Wenzhen Yuan

Humans perceive the world by interacting with objects, which often happens in a dynamic way. For example, a human would shake a bottle to guess its content. However, it remains a challenge for robots to understand many dynamic signals during contact well. This paper investigates dynamic tactile sensing by tackling the task of estimating liquid properties. We

Zhen Wan, Fei Cheng, Qianying Liu, Zhuoyuan Mao

Contrastive pre-training on distant supervision has shown remarkable effectiveness in improving supervised relation extraction tasks. However, the existing methods ignore the intrinsic noise of distant supervision during the pre-training stage. In this paper, we propose a weighted contrastive learning method by leveraging the supervised data to estimate the

René van Bevern, Andrey Melnikov, Pavel Smirnov, Oxana Tsidulko

We study a dynamic vector bin packing (DVBP) problem. We show hardness for shrinking arbitrary DVBP instances to size polynomial in the number of request types or in the maximal number of requests overlapping in time. We also present a simple polynomial-time data reduction algorithm that allows to recover $(1 + {\varepsilon})$-approximate solutions for arbit

Andreas Stadelmeier, Martin Plümicke, Peter Thiemann

Java's type system mostly relies on type checking augmented with local type inference to improve programmer convenience. We study global type inference for Featherweight Generic Java (FGJ), a functional Java core language. Given generic class headers and field specifications, our inference algorithm infers all method types if classes do not make use of polym

Robert Brandenberger, Paola C. M. Delgado, Alexander Ganz, Chunshan Lin

We study the parametric resonance excitation of the electromagnetic field by a gravitational wave. We show that there is narrow band resonance. For an electromagnetic field in the vacuum the resonance occurs only in the second band, and its strength is thus suppressed by two powers of amplitude of the gravitational wave. On the other hand, in the case of an

Andreas Kirsch, Jannik Kossen, Yarin Gal

Principled Bayesian deep learning (BDL) does not live up to its potential when we only focus on marginal predictive distributions (marginal predictives). Recent works have highlighted the importance of joint predictives for (Bayesian) sequential decision making from a theoretical and synthetic perspective. We provide additional practical arguments grounded i

Pavol Quittner

This paper deals with necessary and sufficient conditions for weak and strong minimizers of functionals $\Phi(u)=\int_a^b f(x,u(x),u'(x))\,dx$, where $u\in C^1([a,b],{\mathbb R}^N)$. We first derive conditions which are simpler than the known ones, and then apply them to several particular problems, including stability problems in the elasticity theory. In p

Carsten Carstensen, Rekha Khot, Amiya K. Pani

The lowest-order nonconforming virtual element extends the Morley triangular element to polygons for the approximation of the weak solution $u\in V:=H^2_0(\Omega)$ to the biharmonic equation. The abstract framework allows (even a mixture of) two examples of the local discrete spaces $V_h(P)$ and a smoother allows rough source terms $F\in V^*=H^{-2}(\Omega)$.

Jatadhari Mishra, Marc Jankowski, Alexander Y. Hwang, Hubert S. Stokowski

Thin-film lithium niobate (TFLN) is an emerging platform for compact, low-power nonlinear-optical devices, and has been used extensively for near-infrared frequency conversion. Recent work has extended these devices to mid-infrared wavelengths, where broadly tunable sources may be used for chemical sensing. To this end, we demonstrate efficient and broadband

Ryan Doenges, Tobias Kappé, John Sarracino, Nate Foster

We present Leapfrog, a Coq-based framework for verifying equivalence of network protocol parsers. Our approach is based on an automata model of P4 parsers, and an algorithm for symbolically computing a compact representation of a bisimulation, using "leaps." Proofs are powered by a certified compilation chain from first-order entailments to low-level bitvect

Shen Bian, Quan Wang

We investigate the global existence and blow-up of solutions to the Keller-Segel model with nonlocal reaction term $u\left(M_0-\int_{\R^2} u dx\right)$ in dimension two. By introducing a transformation in terms of the total mass of the populations to deal with the lack of mass conservation, we exhibit that the qualitative behavior of solutions is decided by

Ryan Hofmann, Kevin Reardon, Ivan Milic, Momchil Molnar

We present observations of a solar plage in the millimeter-continuum with the ALMA and in the Ca 8542 and Na 5896 spectral lines with the Interferometric BIdimensional Spectrometer (IBIS). Our goal is to compare the measurement of local gas temperatures provided by ALMA with the temperature diagnostics provided by non-LTE inversions using STIC. In performing

M. Durjasz, M. Szymczak, M. Olech, A. Bartkiewicz

Context: Class II methanol masers at 6.7 GHz originate close to high-mass young stellar objects (HMYSOs). Their high sensitivity to local condition variations makes them a useful marker of the activity of the emerging massive stars. Aims: We aim to closely examine the variability of the 6.7 GHz methanol masers in Cep A HW2 using the new and archival single-d

Neeraj Kumar, Soham Sen, Sunandan Gangopadhyay

In this paper we have considered the thermodynamics of a Born-Infeld $AdS$ black hole using inputs from the dual boundary field theory. Here, we have varied the cosmological constant $\Lambda$ and the Newton's gravitational constant $G$ along with the Born-Infeld parameter $b$ in the bulk. A novel universal critical behaviour of the central charge (occurring

Arup Kumar Mandal, Aprajita Joshi, Surajit Saha, Binoy Krishna De

In recent years, photosensitive materials have been in huge demand because of their fascinating ability to convert absorbed photon energy to generate strain and henceforth tuning the physical properties. In this report we detect the photosensitive activity of SrMnO3. Using the power dependent and temperature dependent Raman study with different laser sources

Apoorva Verma, Pranjal Gulati, Sarthak Gupta

This effort aims to reproduce the results of experiments and analyze the robustness of the review framework for knowledge distillation introduced in the CVPR '21 paper 'Distilling Knowledge via Knowledge Review' by Chen et al. Previous works in knowledge distillation only studied connections paths between the same levels of the student and the teacher, and c

Juan Ferrera, Mohamad R. Pouryayevali, Hajar Radmanesh

We give a definition of weak geodesics on prox-regular subsets of Riemannian manifolds as continuous curves with some weak regularities. Then obtaining a suitable Lipschitz constant of the projection map, we characterize weak geodesics on a prox-regular set with assigned end points as viscosity critical points of the energy functional.

Aparna MP, P. Paramanathan

Fractal interpolation technique is an alternative to the classical interpolation methods especially when a chaotic signal is involved. The logic behind the formulation of an iterated function system for the construction of fractal interpolation functions is to divide the entire interpolating domain into subdomains and define functions on each subdomain piece

Meijun Liu, Ajay Jaiswal, Yi Bu, Chao Min

Incorporating fresh members in teams is considered a pathway to team creativity. However, whether freshness improves team performance or not remains unclear, as well as the optimal involvement of fresh members for team performance. This study uses a group of authors on the byline of a publication as a proxy for a scientific team. We extend an indicator, i.e.

Heydar Soudani, Mohammad Hassan Mojab, Hamid Beigy

Incorporating information from other languages can improve the results of tasks in low-resource languages. A powerful method of building functional natural language processing systems for low-resource languages is to combine multilingual pre-trained representations with cross-lingual transfer learning. In general, however, shared representations are learned

Wensheng Li, Chao Zhang, Chuncheng Wang, Hanting Guan

Physics-informed neural networks (PINNs) provide a deep learning framework for numerically solving partial differential equations (PDEs), and have been widely used in a variety of PDE problems. However, there still remain some challenges in the application of PINNs: 1) the mechanism of PINNs is unsuitable (at least cannot be directly applied) to exploiting a

Philippe Jaming, Martin Rathmair

In this paper we consider the question of finding an as small as possible family of operators $(T_j)_{j\in J}$ on $L^2(R)$ that does phase retrieval: every $\varphi$ is uniquely determined (up to a constant phase factor) by the phaseless data $(|T_j\varphi|)_{j\in J}$. This problem arises in various fields of applied sciences where usually the operators obey

Clément Aubert, Thomas Rubiano, Neea Rusch, Thomas Seiller

This work explores an unexpected application of Implicit Computational Complexity (ICC) to parallelize loops in imperative programs. Thanks to a lightweight dependency analysis, our algorithm allows splitting a loop into multiple loops that can be run in parallel, resulting in gains in terms of execution time similar to state-of-the-art automatic paralleliza

Huixin Li, Andreas Fischer, Marc Avila, Duo Xu

Inhomogeneous refractive index fields lead to errors in optical flow velocity measurements. Former respective studies are mostly in quasi two-dimensional flows, and attribute the measurement errors to spatial gradients in the refractive index field, while less attention has been paid to flows with three-dimensional refractive index fields which usually chang

Appalabathula Venkatesh

In this paper, An Improved Adaptive Sliding Mode Observer (ASMO) is proposed to a Sensorless DSFOC Induction Motor Drives and their stability is analyzed. ASMO is used to estimate the Rotor Speed, Rotor Resistance, Flux, Stator and Rotor currents and the developed electromagnetic Torques.To improve the robustness and accuracy of an adaptive SMO during very l

Lucas Böttcher, Sascha Wald, Tom Chou

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinica

Yves Benoist

We prove that on the cyclic groups of odd order d, there exist non zero functions whose convolution square f*f(2t) is proportional to their square f(t)^2 when the proportionality constant is given by an imaginary quadratic integer of norm d which is equal to 1 modulo 2. The proof involves theta functions on elliptic curves with complex multiplication.

Nhan-Phu Chung, Quoc-Hung Nguyen

We study families of porous medium equation with nonlocal pressure. We construct their weak solutions via JKO schemes for modified Wasserstein distances. We also establish the regularization effect and decay estimates for the $L^p$ norms.

André Galligo

In this paper, we consider nonlocal, nonlinear partial differential equations to model anisotropic dynamics of complex root sets of random polynomials under differentiation. These equations aim to generalise the recent PDE obtained by Stefan Steinerberger (2019) in the real case, and the PDE obtained by Sean O'Rourke and Stefan Steinerberger (2020) in the ra

Dimitrios Loukrezis, Herbert De Gersem

We consider the problem of optimizing the design of a heat sink used for cooling an insulated gate bipolar transistor (IGBT) power module. The thermal behavior of the heat sink is originally estimated using a high-fidelity computational fluid dynamics (CFD) simulation, which renders numerical optimization too computationally demanding. To enable optimization

Philémon Beghin, Anne-Emmanuelle Ceulemans, Paul Fisette, François Glineur

Some early violins have been reduced during their history to fit imposed morphological standards, while more recent ones have been built directly to these standards. We propose an objective photogrammetric approach to differentiate between a reduced and an unreduced instrument, whereby a three-dimensional mesh is studied geometrically by examining 2D slices.

Yves Colin de Verdière

We give a new proof ofan extension of the Chazarain-Duistermaat-Guillemin wave traceformula to the case of 3D-contact manifolds.We use a normal form allowing to reduce to the case of the Heisenberg group.

Y. Zhang, Z. Jin, J. Wei, G. Yin

In this paper, we study closed-loop equilibrium strategies for mean-variance portfolio selection problem in a hidden Markov model with dynamic attention behavior. In addition to the investment strategy, the investor's attention to news is introduced as a control of the accuracy of the news signal process. The objective is to find equilibrium strategies by nu

Corinne Berzin, Alain Latour, José León

The book develops the fundamental ideas of the famous Kac-Rice formula for vectorvalued random fields. This formula allows to compute the expectation and moments of the measure, and integrals with respect to this measure, of the sets of levels of such fields. After a presentation of the historical context of the Kac-Rice formula, we give an elementary demons

Yen-Chieh Huang, Luo-Hao Peng, Hossein Shirvani, Wen-Chi Chen

A conventional free-electron laser is useful but large, driven by a beam with many relativistic electrons. Although, recently, keV electron beams have been used to excite broadband radiation from material chips, there remains a quest for a chip-size free-electron laser capable of emitting coherent radiation. Unfortunately, those keV emitters from electron mi

Alicia Lara-Clares, Juan J. Lastra-Díaz, Ana Garcia-Serrano

This registered report introduces the largest, and for the first time, reproducible experimental survey on biomedical sentence similarity with the following aims: (1) to elucidate the state of the art of the problem; (2) to solve some reproducibility problems preventing the evaluation of most of current methods; (3) to evaluate several unexplored sentence si

Jinyoung Kim, Yujin Lee, Byoung-cheol Koh, Chang Hyon Ha

Thallium-doped sodium iodide (NaI(Tl)) crystals are widely used in radiation detection applications, from gamma-ray spectroscopy to particle dark matter searches. However, if the crystal is exposed to relative humidity of even a few percent, its light emission degrades, making the crystal impractical as a detector. Surrounding the crystal with organic scinti

Jiahao Zhu, Huajun Zhou, Zixuan Chen, Yi Zhou

3D deep models consuming point clouds have achieved sound application effects in computer vision. However, recent studies have shown they are vulnerable to 3D adversarial point clouds. In this paper, we regard these malicious point clouds as 3D steganography examples and present a new perspective, 3D steganalysis, to counter such examples. Specifically, we p

Li-Tao Deng, Da-Bin Lin, Li Zhou, Kai Wang

We report on a very bright, long-duration gamma-ray burst (GRB), GRB~220426A, observed by \emph{Fermi} satellite. GRB~220426A with total duration of $T_{90}=6$~s is composed with two main pulses and some sub-peaks. The spectral analysis of this burst with Band function reveals that both the time-integrated and the time-resolved spectra are very narrow with h

Ritz Ann Aguilar, Damian Dailisan

Single-pixel imaging (SPI) is a novel, unconventional method that goes beyond the notion of traditional cameras but can be computationally expensive and slow for real-time applications. Deep learning has been proposed as an alternative approach for solving the SPI reconstruction problem, but a detailed analysis of its performance and generated basis patterns

C. Sasmal

When two fluids of different electrical conductivities are transported side by side in a microfluidic device under the influence of an electric field, an electrokinetic instability (EKI) is often generated after some critical values of the applied electric field strength and conductivity ratio. Many prior experimental and numerical studies show that this phe

Baibhab Chatterjee, Mayukh Nath, Gaurav Kumar K, Shulan Xiao

Wireless communication using electro-magnetic (EM) fields acts as the backbone for information exchange among wearable devices around the human body. However, for Implanted devices, EM fields incur high amount of absorption in the tissue, while alternative modes of transmission including ultrasound, optical and magneto-electric methods result in large amount

Chika Koyama

Brain waves still cannot reliably distinguish between awake and asleep states. Here, I present new original indices, voltage subthreshold wave $\tau$ and abovethreshold wave burst, for advanced LFP/EEG readings. Assuming that $\tau$ is a microwave that fluctuates every sample such as the equipotential, the total number of $\tau$ ($N\tau$) is inferred to be t

Suman Sarkar, Ganesh Narayanan, Arunima Banerjee, Prem Prakash

Spiral galaxies can be classified into the {\it Grand-designs} and {\it Flocculents} based on the nature of their spiral arms. The {\it Grand-designs} exhibit almost continuous and high contrast spiral arms and are believed to be driven by density waves, while the {\it Flocculents} have patchy and low-contrast spiral features and are primarily stochastic in

Ling-Feng Zhang, Zhi Wang, Xiao Hu

A recent Little-Parks experiment on Kagome-structured superconductor CsV_3Sb_5 demonstrated remarkable resistance oscillations with period \phi0/3=hc/6e. Here, we perform analysis based on a theory involving three 2e superconductivity (SC) order parameters associated with the three reciprocal lattice vectors which connect M points of the hexagonal Brillouin

Alexander Bartler, Florian Bender, Felix Wiewel, Bin Yang

Nowadays, deep neural networks outperform humans in many tasks. However, if the input distribution drifts away from the one used in training, their performance drops significantly. Recently published research has shown that adapting the model parameters to the test sample can mitigate this performance degradation. In this paper, we therefore propose a novel

Juan Chen, Yingchun Zhou

Causal inference is widely used in various fields, such as biology, psychology and economics, etc. In observational studies, we need to balance the covariates before estimating causal effect. This study extends the one-dimensional entropy balancing method to multiple dimensions to balance the covariates. Both parametric and nonparametric methods are proposed

A. Janiuk, B. James

We explore the formation, energetics, and geometry of relativistic jets along with the variability of their central engine. We study both fast and slowly rotating black holes and address our simulations to active galaxy (AGN) centers and gamma ray burst (GRB) engines. The structured jets are postulated to account for emission properties of high energy source

Xiaoliang Liu, Furao Shen, Jian Zhao, Changhai Nie

Data augmentation plays a crucial role in enhancing the robustness and performance of machine learning models across various domains. In this study, we introduce a novel mixed-sample data augmentation method called RandoMix. RandoMix is specifically designed to simultaneously address robustness and diversity challenges. It leverages a combination of linear a

Tomoyuki Tani, Yusuke Nago, Satoshi Murakawa, Keiya Shirahama

We review our study of critical phenomena in superfluid $^4$He confined in nanoporous glasses. $^4$He in nanoporous media is an ideal ground to survey the quantum phase transition of bosons. In the present work, critical phenomena were examined using a newly developed hydrodynamic mechanical resonator. The critical exponent of superfluid density $\zeta$ was

Suresh Govindarajan, Sutapa Samanta, P Shanmugapriya, Amitabh Virmani

Black holes carry more information about the microstates than just the total degeneracy. As a concrete example, the Z(N)-twined helicity trace indices for 1/4-BPS black holes of the CHL models allow extracting information about the distribution of the Z(N) charges among the black hole microstates. The number of black hole microstates carrying a definite eige

Xiaobao Liu, Jiliang Jing, Zehua Tian, Weiping Yao

We investigate the ultimate estimation precision, characterized by the quantum Fisher information, of a two-level atom as a detector which is coupled to massless scalar field in the Minkowski vacuum. It has been shown that for an inertial detector moving with a constant velocity, its quantum Fisher information is completely unaffected by the velocity, howeve

Matthew Olckers, Alicia Vidler, Toby Walsh

Rejected job applicants seldom receive explanations from employers. Techniques from Explainable AI (XAI) could provide explanations at scale. Although XAI researchers have developed many different types of explanations, we know little about the type of explanations job applicants want. We use a survey of recent job applicants to fill this gap. Our survey gen

Mao Yuan, Weiwei Zhu, Haiyan Zhang, Shijie Huang

Radio frequency interference (RFI) is a significant challenge faced by today's radio astronomers. While most past efforts were devoted to cleaning the RFI from the data, we develop a novel method for categorizing and cataloguing RFI for forensic purpose. We present a classifier that categorizes RFI into different types based on features extracted using Princ

N. J. Spinks, L. J. Bignell, G. J. Lane, A. Akber

The scintillation mechanism in NaI:Tl crystals produces different pulse shapes that are dependent on the incoming particle type. The time distribution of scintillation light from nuclear recoil events decays faster than for electron recoil events and this difference can be categorised using various Pulse Shape Discrimination (PSD) techniques. In this study,

Aloka Fernando, Surangika Ranathunga

Out-of-Vocabulary (OOV) is a problem for Neural Machine Translation (NMT). OOV refers to words with a low occurrence in the training data, or to those that are absent from the training data. To alleviate this, word or phrase-based Data Augmentation (DA) techniques have been used. However, existing DA techniques have addressed only one of these OOV types and

Y. Nishino, M. Kimura, S. Sako, J. Beniyama

We report on simultaneous optical and X-ray observations of the dwarf nova SS Cyg with Tomo-e Gozen/1.05 m Kiso Schmidt and Neutron star Interior Composition ExploreR (it NICER) / International Space Station (ISS). A total of four observations were carried out in the quiescent state and highly correlated light variations between the two wavelengths were dete

Yong Ye, Yi Zhao, Jiaying Zhou

In this paper, based on the epidemiological microparasite model, a parasite-host model is established by considering the fear effect of susceptible individuals on infectors. We explored the pattern formation with the help of numerical simulation, and analyzed the effects of fear effect, infected host mortality, population diffusion rate and reducing reproduc

Yixuan Qiao, Shanshan Zhao, Jun Wang, Hao Chen

This paper describes the PASH participation in TREC 2021 Deep Learning Track. In the recall stage, we adopt a scheme combining sparse and dense retrieval method. In the multi-stage ranking phase, point-wise and pair-wise ranking strategies are used one after another based on model continual pre-trained on general knowledge and document-level data. Compared t

Wei Li, Bin Yang, Junsheng Qiao

Since Bustince et al. introduced the concepts of overlap and grouping functions, these two types of aggregation functions have attracted a lot of interest in both theory and applications. In this paper, the depiction of $(O,G)$-granular variable precision fuzzy rough sets ($(O,G)$-GVPFRSs for short) is first given based on overlap and grouping functions. Mea

Harold Carr, Christa Jenkins, Mark Moir, Victor Cacciari Miraldo

We are using the Agda programming language and proof assistant to formally verify the correctness of a Byzantine Fault Tolerant consensus implementation based on HotStuff / LibraBFT. The Agda implementation is a translation of our Haskell implementation based on LibraBFT. This short paper focuses on one aspect of this work. We have developed a library that e

Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi

The emerging field of learning-augmented online algorithms uses ML techniques to predict future input parameters and thereby improve the performance of online algorithms. Since these parameters are, in general, real-valued functions, a natural approach is to use regression techniques to make these predictions. We introduce this approach in this paper, and ex

Han Wang, Archit Sakhadeo, Adam White, James Bell

The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, testing different hyperparameter configurations directly on the environment can be financially prohibitive, dangerous, or time consuming. We propose a new approach to tune hyperparam

Keerti Anand, Rong Ge, Debmalya Panigrahi

A popular line of recent research incorporates ML advice in the design of online algorithms to improve their performance in typical instances. These papers treat the ML algorithm as a black-box, and redesign online algorithms to take advantage of ML predictions. In this paper, we ask the complementary question: can we redesign ML algorithms to provide better

Jaeyoung Yoo, Hojun Lee, Seunghyeon Seo, Inseop Chung

Recent end-to-end multi-object detectors simplify the inference pipeline by removing hand-crafted processes such as non-maximum suppression (NMS). However, during training, they still heavily rely on heuristics and hand-crafted processes which deteriorate the reliability of the predicted confidence score. In this paper, we propose a novel framework to train

Shunsuke Tada

We study prime tensor ideals in tensor abelian categories of quiver representations. Specifically, we classify the prime tensor ideals in the category of representations of zigzag quivers (with bounded path length) whose vertex set is the set of integers. We show that prime tensor ideals in these categories are in canonical bijection with prime ideals of a B

Andrey Pak, Hemanth Manjunatha, Dimitar Filev, Panagiotis Tsiotras

Autonomous driving has received a lot of attention in the automotive industry and is often seen as the future of transportation. Passenger vehicles equipped with a wide array of sensors (e.g., cameras, front-facing radars, LiDARs, and IMUs) capable of continuous perception of the environment are becoming increasingly prevalent. These sensors provide a stream

Shigenori Nakatsuka

Feigin-Semikhatov conjecture, now established, states algebraic isomorphisms between the cosets of the subregular $\mathcal{W}$-algebras and the principal $\mathcal{W}$-superalgebras of type A by their full Heisenberg subalgebras. It can be seen as a variant of Feigin-Frenkel duality between the $\mathcal{W}_n$-algebras and also as a generalization of the co

Parthsarthi Rawat, Sayan Das, Jorge Aguirre, Akhil Daphara

In this paper, we describe a novel architecture which can generate hilarious captions for a given input image. The architecture is split into two halves, i.e. image captioning and hilarious text conversion. The architecture starts with a pre-trained CNN model, VGG16 in this implementation, and applies attention LSTM on it to generate normal caption. These no

Pan-Pan Wang, Wei-Liang Qian, Yu-Jie Tan, Han-Zhong Wu

The time delay interferometry (TDI) is an algorithm proposed to suppress the laser frequency noise in space-borne gravitational wave detectors. As a post-processing technique, it is implemented by constructing a virtual equal arm interferometer through an appropriate combination of the time-shifted data streams. Such an approach is tailored to the intrinsic

Joseph Ryan

The dynamics of some non-conservative and dissipative systems can be derived by calculating the first variation of an action-dependent action, according to the variational principle of Herglotz. This is directly analogous to the variational principle of Hamilton commonly used to derive the dynamics of conservative systems. In a similar fashion, just as the s

Rebecca Bourn, William Q. Erickson, Jeb F. Willenbring

Let $G$ be a complex classical group, and let $V$ be its defining representation (possibly plus a copy of the dual). A foundational problem in classical invariant theory is to write down generators and relations for the ring of $G$-invariant polynomial functions on the space $\mathcal{P}^m(V)$ of degree-$m$ homogeneous polynomial functions on $V$. In this pa

Vladimir Dzhunushaliev, Vladimir Folomeev, Nassurlla Burtebayev

Within general relativity, we construct sequences of rapidly rotating Dirac stars consisting of a spinor fluid described by an effective equation of state. We find the physically relevant domain of stable configurations and calculate their principal characteristics which are completely determined by the central density of the spinor fluid, the mass of the no

Maysa M. Garcia de Macedo, Wyatt Clarke, Eli Lucherini, Tyler Baldwin

Rapid technological innovation threatens to leave much of the global workforce behind. Today's economy juxtaposes white-hot demand for skilled labor against stagnant employment prospects for workers unprepared to participate in a digital economy. It is a moment of peril and opportunity for every country, with outcomes measured in long-term capital allocation

Xun Xu, Manh Cuong Nguyen, Yasin Yazici, Kangkang Lu

Recent work on curvilinear structure segmentation has mostly focused on backbone network design and loss engineering. The challenge of collecting labelled data, an expensive and labor intensive process, has been overlooked. While labelled data is expensive to obtain, unlabelled data is often readily available. In this work, we propose SemiCurv, a semi-superv

Tahir Shamsher, S. Pirzada, Mushtaq A. Bhat

Let $\Gamma=(G,\sigma)$ be a signed graph, where $\sigma$ is the sign function on the edges of $G$. In this paper, we use the operation of partial transpose to obtain non-isomorphic Laplacian cospectral signed graphs. We will introduce two new operations on signed graphs. These operations will establish a relationship between the adjacency spectrum of one si

Xuran Li, Peng Wu, Jing Su

Accuracy and individual fairness are both crucial for trustworthy machine learning, but these two aspects are often incompatible with each other so that enhancing one aspect may sacrifice the other inevitably with side effects of true bias or false fairness. We propose in this paper a new fairness criterion, accurate fairness, to align individual fairness wi

Abhi Mangipudi, Evgeni Grishin, Alessandro A. Trani, Ilya Mandel

Triple stars and compact objects are ubiquitously observed in nature. Their long-term evolution is complex; in particular, the von-Zeipel-Lidov-Kozai (ZLK) mechanism can potentially lead to highly eccentric encounters of the inner binary. Such encounters can lead to a plethora of interacting binary phenomena, as well as stellar and compact-object mergers. He

Alvin J. K. Chua

I define here a novel function on a modeled space of gravitational-wave signals, before studying its properties as a statistic for detection, as an objective function for identification, and as an effective likelihood function for inference. The main motivation behind this work is the open data-analysis problem for signals from extreme-mass-ratio inspirals,

Subodh Mishra, Srikanth Saripalli

In this work we present a novel method to jointly calibrate a sensor suite consisting a 3D-LiDAR, Inertial Measurement Unit (IMU) and Camera under an Extended Kalman Filter (EKF) framework. We exploit pairwise constraints between the 3 sensor pairs to perform EKF update and experimentally demonstrate the superior performance obtained with joint calibration a

Agustín Garrone

Interest in Riemannian manifolds with holonomy equal to the exceptional Lie group $\mathrm{G}_2$ have spurred extensive research in geometric flows of $\mathrm{G}_2$-structures defined on seven-dimensional manifolds in recent years. Among many possible geometric flows, the so-called \textit{isometric flow} has the distinctive feature of preserving the underl

Da-tong Chen, Jun Jing

In the quantum-computation scenario, geometric phase-gates are becoming increasingly attractive for their intrinsic fault tolerance to disturbance. With an adiabatic cyclic evolution, Berry phase appears to realize a geometric transformation. Performing the quantum gates as many as possible within the timescale of coherence, however, remains an inconvenient

Yufan Zhang, Honglin Wen, Qiuwei Wu, Qian Ai

Prediction intervals offer an effective tool for quantifying the uncertainty of loads in distribution systems. The traditional central PIs cannot adapt well to skewed distributions, and their offline training fashion is vulnerable to unforeseen changes in future load patterns. Therefore, we propose an optimal PI estimation approach, which is online and adapt

Ken-ichi Amano, Satoshi Furukawa, Rina Ishii, Ayane Tanase

It is important to understand mechanism of colloidal particles assembly near a substrate for developments of batteries, heterogeneous catalysts, paints, and cosmetics. Knowledge of the mechanism is also important for crystallizations of the colloidal particles and proteins. In this study, we calculated the physical adsorption of colloidal particles on a flat

Yilun Zhou, Julie Shah

Feature attribution methods are popular for explaining neural network predictions, and they are often evaluated on metrics such as comprehensiveness and sufficiency. In this paper, we highlight an intriguing property of these metrics: their solvability. Concretely, we can define the problem of optimizing an explanation for a metric, which can be solved by be