October 2020 arXiv papers — page 116

Bingbing Fan, Yuanzhu Zhao, Budi Riza Putra, Christian Harito

The polymer of intrinsic microporosity PIM 1 is employed to disperse and deposit a Pt at titanate nanosheet photocatalyst film. The resulting microporous films allow electrolyte and oxygen permeation to give conventional oxygen reduction voltammetric responses on glassy carbon or on platinum disk electrodes in the dark. Preliminary data are presented showing

Jan Čejka, Fotis Liarokapis

Underwater sites are a harsh environment for augmented reality applications. Obstacles that must be battled include poor visibility conditions, difficult navigation, and hard manipulation with devices under water. This chapter focuses on the problem of localizing a device under water using markers. It discusses various filters that enhance and improve images

Bui Tuan Khai

CANDLES experiment in Kamioka Underground Observatory aims to obtain the neutrino-less double beta decay ($0νββ$) from $^{48}$Ca. This measurement is a big challenge due to the extremely rare decay rate of $^{48}$Ca. Thus, in order to obtain 0νββ, it is needed to reduce background as much as possible. Series of alpha and beta decays originated from radioacti

Arslan Sajid Raja, Sophie Lange, Maxim Karpov, Kai Shi

Networks inside current data centers comprise a hierarchy of power-hungry electronic packet switches interconnected via optical fibers and transceivers. As the scaling of such electrically-switched networks approaches a plateau, a power-efficient solution is to implement a flat network with optical circuit switching (OCS), without electronic switches and a r

Laurence A. Clarfeld, Margaret J. Eppstein

In the group-testing literature, efficient algorithms have been developed to minimize the number of tests required to identify all minimal "defective" sub-groups embedded within a larger group, using deterministic group splitting with a generalized binary search. In a separate literature, researchers have used a stochastic group splitting approach to

Qi Zhao

This paper presents a deep learning framework based on Long Short-term Memory Network(LSTM) that predicts price movement of cryptocurrencies from trade-by-trade data. The main focus of this study is on predicting short-term price changes in a fixed time horizon from a looking back period. By carefully designing features and detailed searching for best hyper-

V. Simovic, M. Varga, V. Simovic

This research is about integration of information subsystems from:information system procurement, financial information system, information system security, technical information systems and legal information systems, and about their mutual dependence and close connections in Croatian public companies for energy distribution and supply. Also, herewe research

Deepak P, Savitha Sam Abraham

Incorporating fairness constructs into machine learning algorithms is a topic of much societal importance and recent interest. Clustering, a fundamental task in unsupervised learning that manifests across a number of web data scenarios, has also been subject of attention within fair ML research. In this paper, we develop a novel notion of fairness in cluster

Miguel Moscoso, Alexei Novikov, George Papanicolaou, Chrysoula Tsogka

We present a novel approach for recovering a sparse signal from cross-correlated data. Cross-correlations naturally arise in many fields of imaging, such as optics, holography and seismic interferometry. Compared to the sparse signal recovery problem that uses linear measurements, the unknown is now a matrix formed by the cross correlation of the unknown sig

Rui Fang, Maochao Xu, Peng Zhao

Ransomware has emerged as one of the most concerned cyber risks in recent years, which has caused millions of dollars monetary loss over the world. It typically demands a certain amount of ransom payment within a limited timeframe to decrypt the encrypted victim's files. This paper explores whether the ransomware should be paid in a novel game-theoretic

Rocky Talchabhadel, Ganesh R. Ghimire, Sanjib Sharma, Piyush Dahal

Extreme rainfall is one of the major causes of natural hazards (for example flood, landslide, and debris flow) in the central Himalayan region, Nepal. The performance of strategies to manage these risks relies on the accuracy of quantitative rainfall estimates. Rain gauges have traditionally been used to measure the amount of rainfall at a given location. Th

Steffen Wittrock, Philippe Talatchian, Miguel Romera Rabasa, Samh Menshawy

In the present study, we investigate a dynamical mode beyond the gyrotropic (G) motion of a magnetic vortex core in a confined magnetic disk of a nano-pillar spin torque nano oscillator. It is characterized by the in-plane circular precession associated to a C-shaped magnetization distribution. We show a transition between G and C-state mode which is found t

Alireza Aghasi, Barmak Heshmat, Leihao Wei, Moqian Tian

Creating immersive 3D stereoscopic, autostereoscopic, and lightfield experiences are becoming the center point of optical design of future head mounted displays and lightfield displays. However, despite the advancement in 3D and light field displays; there is no consensus on what are the necessary quantized depth levels for such emerging displays at stereosc

Debjyoti Mukherjee, Alireza Ahmadi, Maryam Vahdat Pour, Joel Reardon

Application markets provide a communication channel between app developers and their end-users in form of app reviews, which allow users to provide feedback about the apps. Although security and privacy in mobile apps are one of the biggest issues, it is unclear how much people are aware of these or discuss them in reviews. In this study, we explore the priv

Kazbek Kazhyken, Juha Videman, Clint Dawson

A dispersive wave hydro-sediment-morphodynamic model developed by complementing the shallow water hydro-sediment-morphodynamic (SHSM) equations with the dispersive term from the Green-Naghdi equations is presented. A numerical solution algorithm for the model based on the second-order Strang operator splitting is presented. The model is partitioned into two

Abdoreza Armakan, Sergei Silvestrov

Representations of color Hom-Lie algebras are reviewed, and it is shown that there exist a series of coboundary operators. We also introduce the notion of a color omni-Hom-Lie algebra associated to a vector space and an even invertible linear map. We show how regular color Hom-Lie algebra structures on a vector space can be characterized. Moreover, it is sho

Jie Qiu, Junsoo Han, Ryan Schoell, Miroslav Popovic

The impedance behavior of pre-oxidized iron in liquid lead-bismuth eutectic (LBE) at 200 oC is studied using electrochemical impedance spectroscopy. The structures and resistance of oxide grown on iron oxidized in air at different temperatures and durations are compared. The results show that the resistance of the oxide film increases with increasing oxidizi

Matthieu Herrmann, Geoffrey I. Webb

The Dynamic Time Warping ("DTW") distance is widely used in time series analysis, be it for classification, clustering or similarity search. However, its quadratic time complexity prevents it from scaling. Strategies, based on early abandoning DTW or skipping its computation altogether thanks to lower bounds, have been developed for certain use cases

Roy Bar-Haim, Yoav Kantor, Lilach Eden, Roni Friedman

When summarizing a collection of views, arguments or opinions on some topic, it is often desirable not only to extract the most salient points, but also to quantify their prevalence. Work on multi-document summarization has traditionally focused on creating textual summaries, which lack this quantitative aspect. Recent work has proposed to summarize argument

Dmytro Mishkin, Amy Tabb, Jiri Matas

We claim, and present evidence, that allowing arXiv publication before a conference or journal submission benefits researchers, especially early career, as well as the whole scientific community. Specifically, arXiving helps professional identity building, protects against independent re-discovery, idea theft and gate-keeping; it facilitates open research re

Alex Warstadt, Yian Zhang, Haau-Sing Li, Haokun Liu

One reason pretraining on self-supervised linguistic tasks is effective is that it teaches models features that are helpful for language understanding. However, we want pretrained models to learn not only to represent linguistic features, but also to use those features preferentially during fine-turning. With this goal in mind, we introduce a new English-lan

Alfredo Rueda

In the recent years important experimental advances in resonant electro-optic modulators as high efficient sources for coherent frequency combs and as devices for quantum information transfer have been realized, where strong optical and microwave mode coupling were achieved. These features suggest electro-optic based devices as candidates for entangled optic

Vishnu M. Bashyam, Jimit Doshi, Guray Erus, Dhivya Srinivasan

Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and by contributing to precision medicine. However, these methods have yet to see widespread clinical adoption, in part due to limited generalization performance across various imaging

Deepak P

Clustering is a fundamental task in unsupervised learning, one that targets to group a dataset into clusters of similar objects. There has been recent interest in embedding normative considerations around fairness within clustering formulations. In this paper, we propose 'local connectivity' as a crucial factor in assessing membership desert in centr

Qishen Ha, Bo Liu, Fuxu Liu

We present our winning solution to the SIIM-ISIC Melanoma Classification Challenge. It is an ensemble of convolutions neural network (CNN) models with different backbones and input sizes, most of which are image-only models while a few of them used image-level and patient-level metadata. The keys to our winning are: (1) stable validation scheme (2) good choi

Qishen Ha, Bo Liu, Fuxu Liu, Peiyuan Liao

We present our third place solution to the Google Landmark Recognition 2020 competition. It is an ensemble of global features only Sub-center ArcFace models. We introduce dynamic margins for ArcFace loss, a family of tune-able margin functions of class size, designed to deal with the extreme imbalance in GLDv2 dataset. Progressive finetuning and careful post

Stefano Markidis, Ivy Peng, Artur Podobas, Itthinat Jongsuebchoke

Numerical simulations of plasma flows are crucial for advancing our understanding of microscopic processes that drive the global plasma dynamics in fusion devices, space, and astrophysical systems. Identifying and classifying particle trajectories allows us to determine specific on-going acceleration mechanisms, shedding light on essential plasma processes.

C. E. Whittaker, T. Dowling, A. V. Nalitov, A. V. Yulin

The concept of gauge fields plays a significant role in many areas of physics from particle physics and cosmology to condensed matter systems, where gauge potentials are a natural consequence of electromagnetic fields acting on charged particles and are of central importance in topological states of matter. Here, we report on the experimental realization of

Jonatan Gomez, Carlos Rivera

Gomez proposes a formal and systematic approach for characterizing stochastic global optimization algorithms. Using it, Gomez formalizes algorithms with a fixed next-population stochastic method, i.e., algorithms defined as stationary Markov processes. These are the cases of standard versions of hill-climbing, parallel hill-climbing, generational genetic, st

Ihor Protsenko, Taras Lehinevych, Dmytro Voitekh, Ihor Kroosh

Models based on self-attention mechanisms have been successful in analyzing temporal data and have been widely used in the natural language domain. We propose a new model architecture for video face representation and recognition based on a self-attention mechanism. Our approach could be used for video with single and multiple identities. To the best of our

Elif Sensoy

We exhibit an algorithm with continuous instructions for two robots moving without collisions on a track shaped as a wedge of three circles. We show that the topological complexity of the configuration space associated with this problem is 3. The topological complexity is a homotopy invariant that can be thought of as the minimum number of continuous instruc

Ramy Baly, Giovanni Da San Martino, James Glass, Preslav Nakov

We explore the task of predicting the leading political ideology or bias of news articles. First, we collect and release a large dataset of 34,737 articles that were manually annotated for political ideology -left, center, or right-, which is well-balanced across both topics and media. We further use a challenging experimental setup where the test examples c

S. M. Bilenky

In the introductory part we briefly consider basics of neutrino oscillations and convenient phenomenology of neutrino oscillations in vacuum. Main part of this report is dedicated to a discussion of a plausible BSM scenarios of neutrino mass generation, based on assumptions of massless left-handed SM neutrinos and violation of the total lepton number. It is

Danielle Saunders, Bill Byrne

The 2020 WMT Biomedical translation task evaluated Medline abstract translations. This is a small-domain translation task, meaning limited relevant training data with very distinct style and vocabulary. Models trained on such data are susceptible to exposure bias effects, particularly when training sentence pairs are imperfect translations of each other. Thi

Hansi Hettiarachchi, Tharindu Ranasinghe

Identifying informative tweets is an important step when building information extraction systems based on social media. WNUT-2020 Task 2 was organised to recognise informative tweets from noise tweets. In this paper, we present our approach to tackle the task objective using transformers. Overall, our approach achieves 10th place in the final rankings scorin

S. V. Trofymenko

Processes of K-shell ionization and accompanying characteristic x-ray radiation (CXR) by high-energy electrons moving through a multifoil copper target are considered. Expressions describing the main characteristics of these processes are derived. It is shown that the average K-shell ionization cross section in the target is not defined just by the target ma

Tharindu Ranasinghe, Marcos Zampieri

Offensive content is pervasive in social media and a reason for concern to companies and government organizations. Several studies have been recently published investigating methods to detect the various forms of such content (e.g. hate speech, cyberbulling, and cyberaggression). The clear majority of these studies deal with English partially because most an

Hieu M. Vu, Diep Thi-Ngoc Nguyen

FUNSD is one of the limited publicly available datasets for information extraction from document im-ages. The information in the FUNSD dataset is defined by text areas of four categories ("key", "value", "header", "other", and "background") and connectivity between areas as key-value relations. In-specting FUNSD, we fo

Viet Anh Nguyen, Xuhui Zhang, Jose Blanchet, Angelos Georghiou

We consider the parameter estimation problem of a probabilistic generative model prescribed using a natural exponential family of distributions. For this problem, the typical maximum likelihood estimator usually overfits under limited training sample size, is sensitive to noise and may perform poorly on downstream predictive tasks. To mitigate these issues,

S. L. Yakovlev

Asymptotic representations for large values of the hyperradius are constructed for the scattering wave function of a system of $ N $ particles considered as a generalized function of angular variable coordinates. The coefficients of the asymptotic representations are expressed in terms of the $N$-particle scattering matrix. The phenomenon of asymptotic filtr

Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov

This paper presents the team TransQuest's participation in Sentence-Level Direct Assessment shared task in WMT 2020. We introduce a simple QE framework based on cross-lingual transformers, and we use it to implement and evaluate two different neural architectures. The proposed methods achieve state-of-the-art results surpassing the results obtained by Op

Dhruvesh Patel, Sandeep Konam, Sai P. Selvaraj

Automated Medication Regimen (MR) extraction from medical conversations can not only improve recall and help patients follow through with their care plan, but also reduce the documentation burden for doctors. In this paper, we focus on extracting spans for frequency, route and change, corresponding to medications discussed in the conversation. We first descr

Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis

We propose a novel type of balanced clustering algorithm to approximate attention. Attention complexity is reduced from $O(N^2)$ to $O(N \log N)$, where $N$ is the sequence length. Our algorithm, SMYRF, uses Locality Sensitive Hashing (LSH) in a novel way by defining new Asymmetric transformations and an adaptive scheme that produces balanced clusters. The b

Simone Santini

We develop a model of infection spread that takes into account the existence of a vulnerable group as well as the variability of the social relations of individuals. We develop a compartmentalized power-law model, with power-law connections between the vulnerable and the general population, considering these connections as well as the connections among the v

Peri Akiva, Matthew Purri, Kristin Dana, Beth Tellman

Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information. Instruments and sensors useful for flood detection are only available in low resolution, low latency satellites with region re-visit periods of up to 16 days, making flood alerting

Yanan Li, Ziqiao Wang, Run Xiao, Qi Li

Understanding the superconductivity at the interface of FeSe/SrTiO3 is a problem of great contemporary interest due to the significant increase in critical temperature (Tc) compared to that of bulk FeSe, as well as the possibility of an unconventional pairing mechanism and topological superconductivity. We report a study of the influence of a capping layer o

Yiheng Liu, Elina Robeva, Huanqing Wang

In this paper we propose a new method to learn the underlying acyclic mixed graph of a linear non-Gaussian structural equation model given observational data. We build on an algorithm proposed by Wang and Drton, and we show that one can augment the hidden variable structure of the recovered model by learning {\em multidirected edges} rather than only directe

Seonwoo Kim, Emanuele Contini, Hoseung Choi, San Han

Mass segregation, a tendency of more massive galaxies being distributed closer to the cluster center, is naturally expected from dynamical friction, but its presence is still controversial. Using deep optical observations of 14 Abell clusters (KYDISC) and a set of hydrodynamic simulations (YZiCS), we find in some cases a hint of mass segregation inside the v

Hongbin Sun

For any oriented cusped hyperbolic $3$-manifold $M$, we study its $(R,ε)$-panted cobordism group, which is the abelian group generated by $(R,ε)$-good curves in $M$ modulo the oriented boundaries of $(R,ε)$-good pants. In particular, we prove that for sufficiently small $ε>0$ and sufficiently large $R>0$, some modified version of the $(R,ε)$-panted cobordism

Wen Guo, Enric Corona, Francesc Moreno-Noguer, Xavier Alameda-Pineda

Recent literature addressed the monocular 3D pose estimation task very satisfactorily. In these studies, different persons are usually treated as independent pose instances to estimate. However, in many every-day situations, people are interacting, and the pose of an individual depends on the pose of his/her interactees. In this paper, we investigate how to

Yulin Wang, Kangchen Lv, Rui Huang, Shiji Song

The accuracy of deep convolutional neural networks (CNNs) generally improves when fueled with high resolution images. However, this often comes at a high computational cost and high memory footprint. Inspired by the fact that not all regions in an image are task-relevant, we propose a novel framework that performs efficient image classification by processing

L. A. Lessa, R. Oliveira, J. E. G. Silva, C. A. S. Almeida

We obtain a static spherically symmetric wormhole solution due to the vacuum expectation value (VEV) of a Kalb-Ramond field. The Kalb-Ramond VEV is a background tensor field which produces a local Lorentz symmetry breaking (LSB) of spacetime. Considering a non-minimal coupling between the Kalb-Ramond (VEV) and the Ricci tensor, we found an exact traversable

Duc-Phong Le, Rongxing Lu, Ali A. Ghorbani

The advances of the Internet of Things (IoT) have had a fundamental impact and influence in sharping our rich living experiences. However, since IoT devices are usually resource-constrained, lightweight block ciphers have played a major role in serving as a building block for secure IoT protocols. In CHES 2015, SIMECK, a family of block ciphers, was designed

Yifan Peng, Lin Lin, Lexing Ying, Leonardo Zepeda-Núñez

The efficient treatment of long-range interactions for point clouds is a challenging problem in many scientific machine learning applications. To extract global information, one usually needs a large window size, a large number of layers, and/or a large number of channels. This can often significantly increase the computational cost. In this work, we present

Jared Millson

The study of defeasible reasoning unites epistemologists with those working in AI, in part, because both are interested in epistemic rationality. While it is traditionally thought to govern the formation and (with)holding of beliefs, epistemic rationality may also apply to the interrogative attitudes associated with our core epistemic practice of inquiry, su

Sumantra Sarkar, Sandeep Choubey

Inter and intra-cellular signaling are essential for individual cells to execute various physiological tasks and accurately respond to changes in their environment. Signaling is carried out via diffusible molecules, the transport of which is often aided by active processes that provide directional advection. How diffusion and advection together impact the ac

Alperen Gündogan, H. Murat Gürsu, Volker Pauli, Wolfgang Kellerer

We consider the distributed resource selection problem in Vehicle-to-vehicle (V2V) communication in the absence of a base station. Each vehicle autonomously selects transmission resources from a pool of shared resources to disseminate Cooperative Awareness Messages (CAMs). This is a consensus problem where each vehicle has to select a unique resource. The pr

Marek Demianski, Elisabeta Lusso, Maurizio Paolillo, Ester Piedipalumbo

Several independent cosmological data, collected within the last twenty years, revealed the accelerated expansion rate of the Universe, usually assumed to be driven by the so called dark energy, which, according to recent estimates, provides now about 70 % of the total amount of matter-energy in the Universe. The nature of dark energy is yet unknown. Several

Dave Witte Morris

Let $X$ be a connected Cayley graph on an abelian group of odd order, such that no two distinct vertices of $X$ have exactly the same neighbours. We show that the direct product $X \times K_2$ (also called the "canonical double cover" of $X$) has only the obvious automorphisms (namely, the ones that come from automorphisms of its factors $X$ and $K_2

Anna Laura Suarez

We revisit results concerning the connection between subspaces of a space and sublocales of its locale of open sets. The approach we present is based on the observation that for every locale $L$ its spatial sublocales $\mathsf{sp}[\mathsf{S}(L)]$ form a coframe which is isomorphic to the coframe $\mathsf{sob}[\mathcal{P}(\mathsf{pt}(L))]$ of sober subspaces

Jeff Katen

The goal of this article is to define an analogue of the Weil-pairing for Drinfeld modules using explicit formulas and to deduce its main properties from these formulas. Our result generalizes the formula currently known for rank 2 Drinfeld modules and works as a more explicit, elementary proof of the Weil-pairing's existence than the one appearing in th

Mohamed Lamine Boucenna, Malek Benslama

Maximum distance separable erasure coding has been introduced in wireless networks based on random medium access protocols in order to recover collided and erased packets. So, this help to avoid retransmission process which weaken the network throughput and prolong the overall propagation delay. However, erasure coding may degrade the network performances by

Simon Becker, Mark Embree, Jens Wittsten, Maciej Zworski

Twisted bilayer graphene (TBG) has been experimentally observed to exhibit almost flat bands when the twisting occurs at certain magic angles. In this letter, we report new results on the continuum model of twisted bilayer graphene and its electronic band structure. Under we show that in the approximation of vanishing AA-coupling, the magic angles (at which

Gaurav Shukla, Dariya Salykina, Gaetano Frascella, Devendra Kumar Mishra

For a squeezing-enhanced SU(2) interferometer, we theoretically investigate the possibility to broaden the phase range of sub-shot-noise sensitivity. We show that this goal can be achieved by implementing detection in both output ports, with the optimal combination of the detectors outputs, leading to a phase sensitivity independent of the interferometer ope

T. L. Yap, A. Sasidhara, N. X. Ang, X. Guo

Modulator testing involved complex biasing conditions, hardware connections and data analysis. Also, any optical signal distortion due to the grating coupler effect could potentially induce additional difficulty in setting the correct bias condition for an accurate measurement of the modulator performance. In this paper, we proposed to use SciPy, an open-sou

Vivek Mahato, Pádraig Cunningham

It is well understood that Dynamic Time Warping (DTW) is effective in revealing similarities between time series that do not align perfectly. In this paper, we illustrate this on spectroscopy time-series data. We show that DTW is effective in improving accuracy on a regression task when only a single wavelength is considered. When combined with k-Nearest Nei

Khalid Alnajjar, Mika Hämäläinen, Niko Partanen, Jack Rueter

This study uses a character level neural machine translation approach trained on a long short-term memory-based bi-directional recurrent neural network architecture for diacritization of Medieval Arabic. The results improve from the online tool used as a baseline. A diacritization model have been published openly through an easy to use Python package availab

Holger Grosshans, Claus Bissinger, Mathieu Calero, Miltiadis V. Papalexandris

We report on direct numerical simulations of the effect of electrostatic charges on particle-laden duct flows. The corresponding electrostatic forces are known to affect particle dynamics at small scales and the associated turbophoretic drift. Our simulations, however, predicted that electrostatic forces also dominate the vortical motion of the particles, in

Junfu Pu, Wengang Zhou, Hezhen Hu, Houqiang Li

Continuous sign language recognition (SLR) deals with unaligned video-text pair and uses the word error rate (WER), i.e., edit distance, as the main evaluation metric. Since it is not differentiable, we usually instead optimize the learning model with the connectionist temporal classification (CTC) objective loss, which maximizes the posterior probability ov

Jens Bickmann, Stephan Bröker, Julian Jeggle, Raphael Wittkowski

We consider chirality in active systems by exemplarily studying the phase behavior of planar systems of interacting Brownian circle swimmers with a spherical shape. Continuing previous work presented in [G.-J. Liao, S. H. L. Klapp, Soft Matter, 2018, 14, 7873-7882], we derive a predictive field theory that is able to describe the collective dynamics of circl

S. S. Wang, Y. G. Ma, X. G. Cao, D. Q. Fang

Anisotropic flow can offer significant information of evolution dynamics in heavy-ion collisions. A systematic study of the directed flow $v_1$ and elliptic flow $v_2$ of hard photons and free nucleons is performed for $^{40}$Ca+$^{40}$Ca collisions in a framework of isospin dependent quantum molecular dynamics (IQMD) model. The study firstly reveals that th

Chao Ma, Guohua Gu, Xin Miao, Minjie Wan

Infrared target tracking plays an important role in both civil and military fields. The main challenges in designing a robust and high-precision tracker for infrared sequences include overlap, occlusion and appearance change. To this end, this paper proposes an infrared target tracker based on proximal robust principal component analysis method. Firstly, the

Lei Luo, William Hsu, Shangxian Wang

Generative adversarial networks (GANs) have been successfully applied to transfer visual attributes in many domains, including that of human face images. This success is partly attributable to the facts that human faces have similar shapes and the positions of eyes, noses, and mouths are fixed among different people. Attribute transfer is more challenging wh

Torkan Gholamalizadeh, Sune Darkner, Paolo Maria Cattaneo, Peter Søndergaard

Previous studies on computational modeling of tooth movement in orthodontic treatments are limited to a single model and fail in generalizing the simulation results to other patients. To this end, we consider multiple patients and focus on tooth movement variations under the identical load and boundary conditions both for intra- and inter-patient analyses. W

H. L. Liu, D. D. Han, P. Ji, Y. G. Ma

Nuclear reaction rate ($λ$) is a significant factor in the process of nucleosynthesis. A multi-layer directed-weighted nuclear reaction network in which the reaction rate as the weight, and neutron, proton, $^4$He and the remainder nuclei as the criterion for different reaction-layers is for the first time built based on all thermonuclear reactions in the JI

Yutai Hou, Yongkui Lai, Yushan Wu, Wanxiang Che

In this paper, we study the few-shot multi-label classification for user intent detection. For multi-label intent detection, state-of-the-art work estimates label-instance relevance scores and uses a threshold to select multiple associated intent labels. To determine appropriate thresholds with only a few examples, we first learn universal thresholding exper

Alexander Berndt, Niels Van Duijkeren, Luigi Palmieri, Tamas Keviczky

In this paper we consider multiple Automated Guided Vehicles (AGVs) navigating a common workspace to fulfill various intralogistics tasks, typically formulated as the Multi-Agent Path Finding (MAPF) problem. To keep plan execution deadlock-free, one approach is to construct an Action Dependency Graph (ADG) which encodes the ordering of AGVs as they proceed a

Eleonora Rossi

The trilinear self-coupling can be measured directly using the Higgs-boson-pair production cross section, or indirectly through the measurement of single-Higgs-boson production and decay modes. In fact, at next-to-leading order in electroweak interaction, the Higgs-decay partial widths and the cross sections of the main single-Higgs production processes depe

Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian

Accurate and reliable measurement of energy consumption is critical for making well-informed design choices when choosing and training large scale NLP models. In this work, we show that existing software-based energy measurements are not accurate because they do not take into account hardware differences and how resource utilization affects energy consumptio

Balazs P. Vagvolgyi, Mikhail Khrenov, Jonathan Cope, Anton Deguet

Since the first reports of a novel coronavirus (SARS-CoV-2) in December 2019, over 33 million people have been infected worldwide and approximately 1 million people worldwide have died from the disease caused by this virus, COVID-19. In the US alone, there have been approximately 7 million cases and over 200,000 deaths. This outbreak has placed an enormous s

V. Simovic, T. Alajbeg, J. Curkovic

The tree ammeter method and the three voltmeter method are used for measurements of power. More specifically, they are used to calculate the power factor of a specific load. Both methods are used on the Fundamentals of electrical engineering course in professional study of electrical engineering at the Zagreb University of Applied Sciences as an introduction

Yuta Akimoto, Kouki Taniyama

It is known that the unknotting number $u(L)$ of a link $L$ is less than or equal to half the crossing number $c(L)$ of $L$. We show that there are a planar graph $G$ and its spatial embedding $f$ such that the unknotting number $u(f)$ of $f$ is greater than half the crossing number $c(f)$ of $f$. We study relations between unknotting number and crossing num

Volodymyr Lyubashenko

We recall the notions of a graded cocategory, conilpotent cocategory, morphisms of such (cofunctors), coderivations and define their analogs in $\mathbb L$-filtered setting. The difference with the existing approaches: we do not impose any restriction on $Λ$-modules of morphisms (unlike Fukaya and collaborators), we consider a wider class of filtrations than

D. J. Durian, J. Kroll, E. J. Mele

The distribution of string tension on the contact line between an ideal string and a massive pulley is a frequently-discussed but incompletely-posed problem that confronts students in introductory mechanics. We highlight ambiguities in the usual presentation of this problem by the massive Atwood's machine and discuss two compact resolutions that treat si

V Simovic, V Simovic

After the U.S market earned strong returns in 2003, day trading made a comeback and once again became a popular trading method among traders. Although there is no comprehensive empirical evidence available to answer the question do individual day traders make money, there is a number of studies that point out that only few are able to consistently earn profi

Jan Heyda, Halil I. Okur, Jana Hladílková, Kelvin B. Rembert

A combination of Fourier transform infrared and phase transition measurements as well as molecular computer simulations, and thermodynamic modeling were performed to probe the mechanisms by which guanidinium salts influence the stability of the collapsed versus uncollapsed state of an elastin-like polypeptide (ELP), an uncharged thermoresponsive polymer. We

Jinliang Xie, Jie Tang, Shaoshan Liu

Autonomous Driving is now the promising future of transportation. As one basis for autonomous driving, High Definition Map (HD map) provides high-precision descriptions of the environment, therefore it enables more accurate perception and localization while improving the efficiency of path planning. However, an extremely large amount of map data needs to be

Tirawut Worrakitpoonpon

We present the numerical study of the formation of spiral structure in the context of violent relaxation. Initial conditions are the out-of-equilibrium disks of self-gravitating particles in rigid rotation. By that mechanism, robust and non-stationary spiral arms can be formed within a few free-fall times by the shearing of the mass ejection following the co

Feifei Xu, Xinpeng Wang, Yunpu Ma, Volker Tresp

Story generation, which aims to generate a long and coherent story automatically based on the title or an input sentence, is an important research area in the field of natural language generation. There is relatively little work on story generation with appointed emotions. Most existing works focus on using only one specific emotion to control the generation

Aditya Ohri, Tanya Schmah

We have implemented a machine translation system, the PolyMath Translator, for LaTeX documents containing mathematical text. The current implementation translates English LaTeX to French LaTeX, attaining a BLEU score of 53.5 on a held-out test corpus of mathematical sentences. It produces LaTeX documents that can be compiled to PDF without further editing. T

Peter Johnson, Fadekemi Janet Osaye

Let $G$ be a connected edge-weighted graph of order $n$ and size $m$. Let $w:E(G)\rightarrow \mathbb{R}^{\geq 0}$ be the weighting function. We assume that $w$ is normalised, that is, $\sum_{e\in E(G)} w(e)=m$. The weighted distance $d_w(u,v)$ between any two vertices $u$ and $v$ is the least weight between them and the eccentricity $e_w(v)$ of a vertex $v$

Shreesha Rao D. S., Mikkel Jensen, Lars Grüner-Nielsen, Jesper Toft Olsen

We present the first demonstration of shot-noise limited supercontinuum-based spectral domain optical coherence tomography (SD-OCT) with axial resolution of 5.9 $μ$m at a center wavelength of 1370 nm. Current supercontinuum-based SD-OCT systems cannot be operated in the shot-noise limited detection regime because of severe pulse-to-pulse relative intensity n

Xiaoming Man, Yanguang Chen

Fractal dimension curves of urban growth can be modeled with sigmoid functions, including logistic function and quadratic logistic function. Different types of logistic functions indicate different spatial dynamics. The fractal dimension curves of urban growth in western countries follows the common logistic function, while these curves of cities in northern

Harshil Jain, Akshat Agarwal, Kumar Shridhar, Denis Kleyko

Deep neural networks have demonstrated their superior performance in almost every Natural Language Processing task, however, their increasing complexity raises concerns. In particular, these networks require high expenses on computational hardware, and training budget is a concern for many. Even for a trained network, the inference phase can be too demanding

Annabelle Doerr, Anthony Strittmatter

We study the identification of channels of policy reforms with multiple treatments and different types of selection for each treatment. We disentangle reform effects into policy effects, selection effects, and time effects under the assumption of conditional independence, common trends, and an additional exclusion restriction on the non-treated. Furthermore,

Erin E. Gabriel, Arvid Sjölander, Michael C. Sachs

Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments making the intervention effect that the experiment was designed to estimate nonidentifiable. Nonparametric causal bounds provide a way to narrow the range of possible values for a nonidentifiable causal effect with minimal assumptions. We derive novel bounds for

Yu Wu, Bowen Hou, Ying Chen, Jiang Cao

The interactions between electrons and lattice vibrational modes play the key role in determining the carrier transport properties, thermoelectric performance and other physical quantities related to phonons in semiconductors. However, for two-dimensional (2D) materials, the widely-used models for carrier transport only consider the interactions between elec

Orlando Luongo, Marco Muccino

The dynamics of the Universe are revised using high-redshift data from gamma-ray bursts to constrain cosmographic parameters by means of model-independent techniques. Considering samples from four gamma-ray burst correlations and two hierarchies up to $j_0$ and $s_0$, respectively, we derived limits over the expansion history of the Universe. Since cosmic da

Sigurd Assing, Franco Flandoli, Umberto Pappalettera

We study stochastic model reduction for evolution equations in infinite dimensional Hilbert spaces, and show the convergence to the reduced equations via abstract results of Wong-Zakai type for stochastic equations driven by a scaled Ornstein-Uhlenbeck process. Both weak and strong convergence are investigated, depending on the presence of quadratic interact

Sarika Jain

Most of the existing techniques to product discovery rely on syntactic approaches, thus ignoring valuable and specific semantic information of the underlying standards during the process. The product data comes from different heterogeneous sources and formats giving rise to the problem of interoperability. Above all, due to the continuously increasing influx