May 2020 arXiv papers — page 5

Yujie Hu, Harvey J Miller, Xiang Li

Capabilities for collecting and storing data on mobile objects have increased dramatically over the past few decades. A persistent difficulty is summarizing large collections of mobile objects. This paper develops methods for extracting and analyzing hotspots or locations with relatively high levels of mobility activity. We use kernel density estimation (KDE

Rebecca Mitchell, Roger Maull, Simon Pearson, Steve Brewer

The resilience of the food supply chain is a matter of critical importance, both for national security and broader societal well bring. COVID19 has presented a test to the current system, as well as means by which to explore whether the UK's food supply chain will be resilient to future disruptions. In the face of a growing need to ensure that food supply is

Aleksandr Rotkevich

Let $\Omega\subset\mathbb{C}^n$ be a strictly pseudoconvex Runge domain with $C^2$-smooth defining function, $l\in\mathbb{N},$ $p\in(1,\infty).$ We prove that the holomorphic function $f$ has derivatives of order $l$ in $H^p(\Omega)$ if and only if there exists a sequence on polynomials $P_n$ of degree $n$ such that $\sum\limits_{k=1}^{\infty}2^{2lk}\left\lv

Yujie Hu, Fahui Wang

Excess or wasteful commuting is measured as the proportion of actual commute that is over minimum (optimal) commute when assuming that people could freely swap their homes and jobs in a city. Studies usually rely on survey data to define actual commute, and measure the optimal commute at an aggregate zonal level by linear programming (LP). Travel time from a

Alexis Derumigny, Johannes Schmidt-Hieber

It is a common phenomenon that for high-dimensional and nonparametric statistical models, rate-optimal estimators balance squared bias and variance. Although this balancing is widely observed, little is known whether methods exist that could avoid the trade-off between bias and variance. We propose a general strategy to obtain lower bounds on the variance of

Yujie Hu, Fahui Wang

Based on the 1990-2010 CTPP data in Baton Rouge, this research analyzes the temporal trends of commuting patterns in both time and distance. In comparison to previous work, commuting length is calibrated more accurately by Monte Carlo based simulation of individual journey-to-work trips to mitigate the zonal effect. First, average commute distance kept climb

Esther S. Daus, Mariya Ptashnyk, Claudia Raithel

In this article a fractional cross-diffusion system is derived as the rigorous many-particle limit of a multi-species system of moderately interacting particles that is driven by L\'{e}vy noise. The form of the mutual interaction is motivated by the porous medium equation with fractional potential pressure. Our approach is based on the techniques developed b

Liuyuan Chen, Kanglei Zhou, Junchang Jing, Haiju Fan

The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems. However, it suffers from difficulties in effective solution of multi-classification and fast model selection. This work devotes to the fast regularization parameter tuning algorithm for the twin multi-class support vector machine. S

Fahui Wang, Yujie Hu, Shuai Wang, Xiaojuan Li

Most existing point-based colocation methods are global measures (e.g., join count statistic, cross K function, and global colocation quotient). Most recently, a local indicator such as the local colocation quotient is proposed to capture the variability of colocation across areas. Our research advances this line of work by developing a simulation-based stat

Shoujin Wang, Longbing Cao, Liang Hu, Shlomo Berkovsky

A transaction-based recommender system (TBRS) aims to predict the next item by modeling dependencies in transactional data. Generally, two kinds of dependencies considered are intra-transaction dependency and inter-transaction dependency. Most existing TBRSs recommend next item by only modeling the intra-transaction dependency within the current transaction

Yujie Hu, Fahui Wang, Chester Wilmot

Residential segregation recently has shifted to more class or income-based in the United States, and neighborhoods are undergoing significant changes such as commuting patterns over time. To better understand the commuting inequality across neighborhoods of different income levels, this research analyzes commuting variability (in both distance and time) acro

Yujie Hu, Fahui Wang, Imam Xierali

Objective. To develop an automated, data-driven, and scale-flexible method to delineate HSAs and HRRs that are up-to-date, representative of all patients, and have the optimal localization of hospital visits. Data Sources. The 2011 State Inpatient Database (SID) in Florida from the Healthcare Cost and Utilization Project (HCUP). Study Design. A network optim

L. Saha, A. Domínguez, L. Tibaldo, S. Marchesi

We report a detailed study of an unidentified gamma-ray source located in the region of the compact stellar cluster NGC 3603. This is a star-forming region (SFR) powered by a massive cluster of OB stars. A dedicated analysis of about 10 years of data from 10 GeV - 1 TeV, provided by the Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope,

Mahbubunnabi Tamal

To accurately quantify in vivo radiotracer uptake using Positron Emission Tomography (PET) is a challenging task due to low signal-to-noise ratio (SNR) and poor spatial resolution of PET camera along with the finite image sampling constraint. Furthermore, inter lesion variations of the SNR and contrast along with the variations in size of the lesion make the

Silvia Amabilino, Lars A. Bratholm, Simon J. Bennie, Michael B. O'Connor

The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm for deriving energy functions of hyperdimensional molecular systems, which involves generating data for low-dimensional systems in virtual reality (VR) to then efficiently train a

Yujie Hu, Yu Zhang, Kyle Shelton

Pedestrians and cyclists are vulnerable road users. They are at greater risk for being killed in a crash than other road users. The percentage of fatal crashes that involve a pedestrian or cyclist is higher than the overall percentage of total trips taken by both modes. Because of this risk, finding ways to minimize problematic street environments is critica

Yujie Hu, Fahui Wang, Cecile Guin, Haojie Zhu

Predictive hotspot mapping plays a critical role in hotspot policing. Existing methods such as the popular kernel density estimation (KDE) do not consider the temporal dimension of crime. Building upon recent works in related fields, this article proposes a spatio-temporal framework for predictive hotspot mapping and evaluation. Comparing to existing work in

Georgios P. Balomenos, Yujie Hu, Jamie E. Padgett, Kyle Shelton

The mobility of residents and their access to essential services can be highly affected by transportation network closures that occur during and after coastal hazard events. Few studies have used geographic information systems coupled with infrastructure vulnerability models to explore how spatial accessibility to goods and services shifts after a hurricane.

Camila Dias dos Reis Barros, Janaina Cardozo Rocha, Ivan Napoleão Bastos, José Antônio da Cunha Ponciano Gomes

Micromovements that occur in the joint between dental prostheses and implants can lead to wear-induced degradation. This process can be enhanced by corrosion in the oral environment influenced by the presence of solutions containing fluoride. Moreover, the eventual galvanic interactions between NiCr and Ti alloys can accelerate the wear-corrosion process. In

Jiawei Zhao, Yifan Zhao, Jia Li, Xiaowu Chen

Salient object detection (SOD) is a crucial and preliminary task for many computer vision applications, which have made progress with deep CNNs. Most of the existing methods mainly rely on the RGB information to distinguish the salient objects, which faces difficulties in some complex scenarios. To solve this, many recent RGBD-based networks are proposed by

Yujie Hu, Joni Downs

Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically desig

Chengjian Sun, Changyang She, Chenyang Yang

Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems. Considering that labeled training samples are hard to obtain, unsupervised deep learning has been proposed to solve functional optimization problems with statistical constraints re

Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden

This paper focuses on the problem of modeling and estimating interaction effects between covariates and a continuous treatment variable on an outcome, using a single-index regression approach. The primary motivation is to estimate an optimal individualized dose rule in an observational study. To model possibly nonlinear interaction effects between patients'

Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden

A novel functional additive model is proposed which is uniquely modified and constrained to model nonlinear interactions between a treatment indicator and a potentially large number of functional and/or scalar pretreatment covariates. The primary motivation for this approach is to optimize individualized treatment rules based on data from a randomized clinic

Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden

Sparse additive modeling is a class of effective methods for performing high-dimensional nonparametric regression. This paper develops a sparse additive model focused on estimation of treatment effect-modification with simultaneous treatment effect-modifier selection. We propose a version of the sparse additive model uniquely constrained to estimate the inte

Doriann Albertin, Vincent Pilaud, Julian Ritter

The associahedron is classically constructed as a removahedron, i.e. by deleting inequalities in the facet description of the permutahedron. This removahedral construction extends to all permutreehedra (which interpolate between the permutahedron, the associahedron and the cube). Here, we investigate removahedra constructions for all quotientopes (which real

Z. Yousaf

The aim of this paper is to explore the complexity factor (CF) for those self-gravitating relativistic spheres whose evolution proceeds non-dynamically. We are adopting the definition of CF mentioned in \cite{PhysRevD.97.044010}, modifying it to the static spherically symmetric case, within the framework of a modified gravity theory (the Palatini $f(R)$ theo

Cecilia Cavaterra, Serena Dipierro, Zu Gao, Enrico Valdinoci

We provide global gradient estimates for solutions to a general type of nonlinear parabolic equations, possibly in a Riemannian geometry setting. Our result is new in comparison with the existing ones in the literature, in light of the validity of the estimates in the global domain, and it detects several additional regularity effects due to special paraboli

Sosuke Nishikawa, Ryokan Ri, Yoshimasa Tsuruoka

Unsupervised cross-lingual word embedding (CLWE) methods learn a linear transformation matrix that maps two monolingual embedding spaces that are separately trained with monolingual corpora. This method relies on the assumption that the two embedding spaces are structurally similar, which does not necessarily hold true in general. In this paper, we argue tha

Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden

Dimension reduction lies at the heart of many statistical methods. In regression, dimension reduction has been linked to the notion of sufficiency whereby the relation of the response to a set of predictors is explained by a lower dimensional subspace in the predictor space. In this paper, we consider the notion of a dimension reduction in regression on subs

Sekhar Ghosh, Debajyoti Choudhuri, Ratan Kr. Giri

We prove the existence of infinitely many nonnegative solutions to the following nonlocal elliptic partial differential equation involving singularities \begin{align} (-\Delta)_{p(\cdot)}^{s} u&=\frac{\lambda}{|u|^{\gamma(x)-1}u}+f(x,u)~\text{in}~\Omega,\nonumber u&=0~\text{in}~\mathbb{R}^N\setminus\Omega,\nonumber \end{align} where $\Omega\subset\mathbb{R}^

Q. B. Chen, S. Frauendorf, N. Kaiser, Ulf-G. Meißner

The $g$-factor and static quadrupole moment for the wobbling mode in the nuclide $^{133}$La are investigated as functions of the spin $I$by employing the particle rotor model. The model can reproduce the available experimental data of $g$-factor and static quadrupole moment. The properties of the $g$-factor and static quadrupole moment as functions of $I$ ar

Corrado Mascia, Donato Pera, Chiara Simeoni

We introduce a variant of the Gatenby-Gawlinski model for acid-mediated tumor invasion, accounting for anisotropic and heterogeneous diffusion of the lactic acid across the surrounding healthy tissues. Numerical simulations are performed for two-dimensional data by employing finite volume schemes on staggered Cartesian grids, and parallel implementation thro

Hanna Le Jeannic, Tomás Ramos, Signe F. Simonsen, Tommaso Pregnolato

Coherent photon-emitter interfaces offer a way to mediate efficient nonlinear photon-photon interactions, much needed for quantum information processing. Here we experimentally study the case of a two-level emitter, a quantum dot, coupled to a single optical mode in a nanophotonic waveguide. We carry out few-photon transport experiments and record the statis

Varun Narayanan, Jithin Ravi, Vivek K. Mishra, Bikash Kumar Dey

We study the fundamental problem of index coding under an additional privacy constraint that requires each receiver to learn nothing more about the collection of messages beyond its demanded messages from the server and what is available to it as side information. To enable such private communication, we allow the use of a collection of independent secret ke

Elena Agliari, Linda Albanese, Adriano Barra, Gabriele Ottaviani

In this paper we adapt the broken replica interpolation technique (developed by Francesco Guerra to deal with the Sherrington-Kirkpatrick model, namely a pairwise mean-field spin-glass whose couplings are i.i.d. standard Gaussian variables) in order to work also with the Hopfield model (i.e., a pairwise mean-field neural-network whose couplings are drawn acc

C. Smorra, Y. V. Stadnik, P. E. Blessing, M. Bohman

Astrophysical observations indicate that there is roughly five times more dark matter in the Universe than ordinary baryonic matter, with an even larger amount of the Universe's energy content due to dark energy. So far, the microscopic properties of these dark components have remained shrouded in mystery. In addition, even the five percent of ordinary matte

Helge Glockner

For suitable finite-dimensional smooth manifolds M (possibly with various kinds of boundary or corners), locally convex topological vector spaces F and non-negative integers k, we construct continuous linear operators S_n from the space of F-valued k times continuously differentiable functions on M to the corresponding space of smooth functions such that S_n

A. Lapi, L. Pantoni, L. Boco, L. Danese

We generalize the analytic solutions presented in Pantoni et al. (2019) by including a simple yet effective description of wind recycling and galactic fountains, with the aim of self-consistently investigating the spatially-averaged time evolution of the gas, stellar, metal, and dust content in disc-dominated late-type galaxies (LTGs). Our analytic solutions

Yusuke Mukuhira, Michael C. Fehler, Takatoshi Ito, Hiroshi Asanuma

Like natural seismicity, induced seismicity caused by fluid injection also shows a power law size distribution, and its gradient b-value (ratio of small to large earthquakes) is often used for seismic hazard analysis. Despite well-known relationship that b-value is negatively correlated with differential stress for natural earthquakes, there is no understand

Shashank Kumar Ojha, Sanat Kumar Gogoi, Manju Mishra Patidar, Ranjan Kumar Patel

The discovery of skyrmions has sparked tremendous interests about topologically nontrivial spin textures in recent times. The signature of noncoplanar nature of magnetic moments can be observed as topological Hall effect (THE) in electrical measurement. Realization of such nontrivial spin textures in new materials and through new routes is an ongoing endeavo

Anthony DiSpirito, Daiwei Li, Tri Vu, Maomao Chen

One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM images and transcend the trade-off between spatial resolution and imaging speed. We compared various convolutional

Ziyue Jia, Linfeng Yang, Zhenrong Zhang, Hui Liu

Non Intrusive Load Monitoring (NILM) or Energy Disaggregation (ED), seeks to save energy by decomposing corresponding appliances power reading from an aggregate power reading of the whole house. It is a single channel blind source separation problem (SCBSS) and difficult prediction problem because it is unidentifiable. Recent research shows that deep learnin

Yuekun Yao, Barry Haddow

For spoken language translation (SLT) in live scenarios such as conferences, lectures and meetings, it is desirable to show the translation to the user as quickly as possible, avoiding an annoying lag between speaker and translated captions. In other words, we would like low-latency, online SLT. If we assume a pipeline of automatic speech recognition (ASR) a

Benita S. Mackay, Matthew Praeger, James A. Grant-Jacob, Janos Kanczler

The response of adult human bone marrow stromal stem cells to surface topographies generated through femtosecond laser machining can be predicted by a deep neural network. The network is capable of predicting cell response to a statistically significant level, including positioning predictions with a probability P < 0.001, and therefore can be used as a mode

Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens

In this paper, we attempt to solve a long-lasting open question for non-positive definite (non-PD) kernels in machine learning community: can a given non-PD kernel be decomposed into the difference of two PD kernels (termed as positive decomposition)? We cast this question as a distribution view by introducing the \emph{signed measure}, which transforms posi

Luca Banetta, Alessio Zaccone

The pair correlation function of charge stabilized colloidal particles under strongly sheared conditions is studied using the analytical intermediate asymptotics method recently developed in [L. Banetta and A. Zaccone, Phys. Rev. E 99, 052606 (2019)] to solve the steady-state Smoluchowski equation for medium to high values of the P\'eclet number; the analyti

Parvathy Panicker

This paper presents a critical review of the challenges to the implementation of learning technologies with particular focus on developing countries. A comprehensive literature review on learning technologies was undertaken for the purpose of understanding the challenges in developing countries. The research question is: what extent does education empower le

Aritra Banerjee, Haiying Cai, Lavinia Heisenberg, Eoin Ó Colgáin

Local determinations of the Hubble constant $H_0$ favour a higher value than Planck based on CMB and $\Lambda$CDM. Through a model-independent expansion, we show that low redshift ($z \lesssim 0.7$) data comprising baryon acoustic oscillations (BAO), cosmic chronometers and Type Ia supernovae has a preference for Quintessence models that lower $H_0$ relative

Mohamed Anis Haddouche, Dominique Fourdrinier, Fatiha Mezoued

We consider the problem of estimating the scale matrix $\Sigma$ of the additif model $Y_{p\times n} = M + \mathcal{E}$, under a theoretical decision point of view. Here, $ p $ is the number of variables, $ n$ is the number of observations, $ M $ is a matrix of unknown parameters with rank $q<p$ and $ \mathcal {E}$ is a random noise, whose distribution is ell

Onur Kaya, Mehmet Önder

In this study, we define the generalized normal ruled surface of a curve in the Euclidean 3-space $E^3$. We study the geometry of such surfaces by calculating the Gaussian and mean curvatures to determine when the surface is flat or minimal (equivalently, helicoid). We examine the conditions for the curves lying on this surface to be asymptotic curves, geode

E. Mompó, M. A. López-Castaño, A. Torrente, F. Vega Reyes

We study a granular gas of viscoelastic particles (kinetic energy loss upon collision is a function of the particles' relative velocities at impact) subject to a stochastic thermostat. We show that the system displays anomalous cooling and heating rates during thermal relaxation processes, this causing the emergence of thermal memory. In particular, a signif

Tian Liang

In this paper we build up a criteria for fractional Orlicz-Sobolev extension and imbedding domains on Ahlfors $n$-regular domains.

Wen-Chiao Tsai, Chieh-Fang Teng, Han-Mo Ou, An-Yeu Wu

Recently, deep learning-assisted communication systems have achieved many eye-catching results and attracted more and more researchers in this emerging field. Instead of completely replacing the functional blocks of communication systems with neural networks, a hybrid manner of BCJRNet symbol detection is proposed to combine the advantages of the BCJR algori

Luigi Appolloni, Simone Secchi

We investigate the existence of solutions to the fractional nonlinear Schr\"{o}dinger equation $(-\Delta)^s u = f(u)$ with prescribed $L^2$-norm $\int_{\mathbb{R}^N} |u|^2 \, dx =m$ in the Sobolev space $H^s(\mathbb{R}^N)$. Under fairly general assumptions on the nonlinearity $f$, we prove the existence of a ground state solution and a multiplicity result in

W. N. Faugno, J. K. Jain, Ajit C. Balram

We consider a non-Abelian candidate state at filling factor $\nu=3/7$ state belonging to the parton family. We find that, in the second Landau level of GaAs (i.e. at filling factor $\nu=2+3/7$), this state is energetically superior to the standard Jain composite-fermion state and also provides a very good representation of the ground state found in exact dia

Gh. Haghighatdoost, J. Ojbag

In this paper, we introduce right-invariant (similarly, left-invariant) Poisson-Nijenhuis Structures on Lie groupoids and their infinitesimal counterparts as called $(\Lambda , \mathbf{n})-$structures. We present a mutual correspondence between $(\Lambda ,\mathbf{n})-$structures on Lie algebroids with Poisson-Nijenhuis structures $(\Pi , \mathbf{N})$ on thei

Rik Eshuis

Case Management supports knowledge workers in performing knowledge-intensive processes in a flexible way. An essential ingredient of Case Management are template processes that are modified for a specific case to suit the context of that case. Modifying templates results in many different yet related process variants. However, modifying a template is time co

Haijin Zeng, Xiaozhen Xie, Jifeng Ning

Hyperspectral image (HSI) denoising aims to restore clean HSI from the noise-contaminated one. Noise contamination can often be caused during data acquisition and conversion. In this paper, we propose a novel spatial-spectral total variation (SSTV) regularized nonconvex local low-rank (LR) tensor approximation method to remove mixed noise in HSIs. From one a

Fan Zhang, MinChao Yan, Chen Hu, Jun Ni

The land cover classification has played an important role in remote sensing because it can intelligently identify things in one huge remote sensing image to reduce the work of humans. However, a lot of classification methods are designed based on the pixel feature or limited spatial feature of the remote sensing image, which limits the classification accura

Fabio Castagna, Stefano Andreon

High-resolution observations of the thermal Sunyaev-Zeldovich (SZ) effect and of the X-ray emission of galaxy clusters are becoming more and more widespread, offering us an unique asset to the study of the thermodynamic properties of the intracluster medium. We present JoXSZ, a Bayesian forward-modelling Python code designed to jointly fit the SZ data and th

Thi Kim Thoa Thieu, Adrian Muntean

We study the well-posedness of a coupled system of Skorohod-like stochastic differential equations with reflecting boundary condition. The setting describes the evacuation dynamics of a mixed crowd composed of both active and passive pedestrians moving through a domain with obstacles, fire and smoke. As main working techniques, we use compactness methods and

Nasir Saeed, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini

Global climate change is significantly affecting the life on planet Earth. Predicting timely changes in the climate is a big challenge and requires great attention from the scientific community. Research now suggests that using the internet of X-things (X-IoT) helps in monitoring global climate change.

Ioannis Arapakis, Luis A. Leiva

Tracking mouse cursor movements can be used to predict user attention on heterogeneous page layouts like SERPs. So far, previous work has relied heavily on handcrafted features, which is a time-consuming approach that often requires domain expertise. We investigate different representations of mouse cursor movements, including time series, heatmaps, and traj

Wensha Gou, Siyu Huang, Qinghua Chen, Jiawei Chen

Cross-border migration brings economic and cultural impacts to the origin and destination, and is also a key to reflect the international relations of related countries. In fact, the migration relationships of countries are complex and multilateral, but most traditional migration models are bilateral. Network theories could provide a better description of gl

L. Bufaiçal, L. T. Coutrim, E. M. Bittar, F. Garcia

In this work we propose an alternative model to explain the spontaneous exchange bias (SEB) effect observed in spin glass (SG)-like systems. As in a previously proposed model (Ref. 1), it is based on the unconventional dynamics of the SG-like moments at the magnetic hysteresis cycle. However, using a reliable estimate of the amount of SG-spins that are relax

Roberto Grimaudo, Hiromichi Nakazato, Antonino Messina, Nikolay V. Vitanov

It has been theoretically demonstrated that two spins (qubits or qutrits), coupled by exchange interaction only, undergo a coupling-based joint Landau-Majorana-St\"uckelberg-Zener (LMSZ) transition when a linear ramp acts upon one of the two spins. Such a transition, under appropriate conditions on the parameters, drives the two-spin system toward a maximall

Prabir Rudra

In this note a time dependent spacetime is explored in the background of $f(R,T)$ gravity via the gravitational collapse of a massive star. The star is modelled by the Vaidya spacetime which is time dependent in nature. The coupling of matter with curvature is the key feature of $f(R,T)$ theory and here we have investigated its effects on a collapsing scenar

Yang Song, Yu Gu, Rui Zhang, Ge Yu

Bregman distances (also known as Bregman divergences) are widely used in machine learning, speech recognition and signal processing, and kNN searches with Bregman distances have become increasingly important with the rapid advances of multimedia applications. Data in multimedia applications such as images and videos are commonly transformed into space of hun

Fahri Aydos, A. Murat Özbayoğlu, Yahya Şirin, M. Fatih Demirci

In this paper, we introduce a novel method that combines multiple neural network results to decide the class of the input. This is the first study which used the method for web pages classification. In our model, each element is represented by multiple descriptive images. After the training process of the neural network model, each element is classified by c

A. Saha, S. Ghose

We discuss Tsallis holographic dark energy (THDE) model in higher dimension. An interacting dark energy model is proposed with Generalized Chaplygin Gas (GCG) in the framework of Compact Kaluza-Klein gravity. It is shown that a stable configuration can be found in the present epoch which is also compatible with the observed value of the density parameter. It

Mark A. Hughes, Naitik A. Panjwani, Matias Urdampilleta, Nafsika Theodoropoulou

Erbium implanted silicon as a quantum technology platform has both telecommunications and integrated circuit (IC) processing compatibility. The electron spin coherence time of Er implanted Si with an Er concentration of 3X1017 cm-3 is measured to be ~10 {\mu}s at 5 K and the spin echo decay profile displays strong modulation due to super-hyperfine interactio

Naoto Iguchi, Yoichi Itoh

We carried out optical high-resolution spectroscopy of T Tauri stars using the Subaru Telescope. Using archived data from the Keck Telescope and the Very Large Telescope, we detected forbidden lines of [S II] at 4069 A, in addition to those of [O I] at 5577 A and 6300 A, for 13 T Tauri stars. We consider that low-velocity components of these forbidden lines

Catarina Moreira, Matheus Hammes, Rasim Serdar Kurdoglu, Peter Bruza

This paper provides the foundations of a unified cognitive decision-making framework (QulBIT) which is derived from quantum theory. The main advantage of this framework is that it can cater for paradoxical and irrational human decision making. Although quantum approaches for cognition have demonstrated advantages over classical probabilistic approaches and b

Alexey V. Podobryaev

Any free nilpotent Lie algebra is determined by its rank and step. We consider free nilpotent Lie algebras of steps 3, 4 and corresponding connected and simply connected Lie groups. We construct Casimir functions of such groups, i.e., invariants of the coadjoint representation. For free 3-step nilpotent Lie groups we get a full description of coadjoint orbit

Aya Iwai, Yoichi Itoh, Tsuyoshi Terai, Ranjan Gupta

We carried out low-resolution optical spectroscopy of 51 main-belt asteroids, most of which have highly-inclined orbits. They are selected from D-type candidates in the SDSS-MOC 4 catalog. Using the University of Hawaii 2.2 m telescope and the Inter-University Centre for Astronomy and Astrophysics 2 m telescope in India, we determined the spectral types of 3

Dag Normann, Sam Sanders

The Axiom of Choice (AC for short) is the most (in)famous axiom of the usual foundations of mathematics, ZFC set theory. The (non-)essential use of AC in mathematics has been well-studied and thoroughly classified. Now, fragments of countable AC not provable in ZF have recently been used in Kohlenbach's higher-order Reverse Mathematics to obtain equivalences

Suparna Biswas, Dibyendu Shee, B. K. Guha, Saibal Ray

In the current article, we study anisotropic spherically symmetric strange star under the background of $f(R,T)$ gravity using the metric potentials of Tolman-Kuchowicz type~\cite{Tolman1939,Kuchowicz1968} as $\lambda(r)=\ln(1+ar^2+br^4)$ and $\nu(r)=Br^2+2\ln C$ which are free from singularity, satisfy stability criteria and also well behaved. We calculate

Shanshan Wang, Lei Zhang

Existing adversarial domain adaptation methods mainly consider the marginal distribution and these methods may lead to either under transfer or negative transfer. To address this problem, we present a self-adaptive re-weighted adversarial domain adaptation approach, which tries to enhance domain alignment from the perspective of conditional distribution. In

Zengjing Chen, Shuhui Liu, Zhongmin Qian, Xingcheng Xu

In this paper, we investigate a class of nonlinear backward stochastic differential equations (BSDEs) arising from financial economics, and give specific information about the nodal sets of the related solutions. As applications, we are able to obtain the explicit solutions to an interesting class of nonlinear BSDEs including the k-ignorance BSDE arising fro

Yoichi Itoh, Yumiko Oasa

Star-forming regions are often associated with nebulosity. In this study, we investigated infrared diffuse emission in Spitzer IRAC images. The infrared nebula L1527 traces outflows emanating from a low-mass protostar. The nebular color is consistent with the color of a stellar photosphere with large extinction. Nebulae around the HII region W5-East are brig

Masud Mansuripur

The Fourier transform operation is an important conceptual as well as computational tool in the arsenal of every practitioner of physical and mathematical sciences. We discuss some of its applications in optical science and engineering, with the goal of providing a broad perspective on the intimate relation between the physical and mathematical concepts that

Haruka Tabata, Yoichi Itoh

The results of near-infrared photometric observations of a transit event of an extrasolar planet HAT-P-54b are presented herein. Precise near-infrared photometry was carried out using the Nayuta 2 m telescope at Nishi-Harima Astronomical Observatory, Japan and Nishi-harima Infrared Camera (NIC). 170 J-, H-, and Ks-band images were taken in each band in 196 m

Kensuke Hosoya, Yoichi Itoh, Yumiko Oasa, Ranjan Gupta

The results of a spectroscopic survey of H alpha emission line stars associated with fourteen bright rimmed clouds are presented. Slit-less optical spectroscopy was carried out with the Inter University Centre for Astronomy and Astrophysics (IUCAA) 2m telescope and IUCAA Faint Object Spectrograph and Camera (IFOSC). H alpha emission line was detected from 17

Imanol Perez Arribas, Cristopher Salvi, Lukasz Szpruch

Mathematical models, calibrated to data, have become ubiquitous to make key decision processes in modern quantitative finance. In this work, we propose a novel framework for data-driven model selection by integrating a classical quantitative setup with a generative modelling approach. Leveraging the properties of the signature, a well-known path-transform fr

Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen

Despite their great performance over the years, handcrafted speech features are not necessarily optimal for any particular speech application. Consequently, with greater or lesser success, optimal filterbank learning has been studied for different speech processing tasks. In this paper, we fill in a gap by exploring filterbank learning for keyword spotting (

Takafumi Inoue, Shunsuke Inenaga, Hideo Bannai

The longest square subsequence (LSS) problem consists of computing a longest subsequence of a given string $S$ that is a square, i.e., a longest subsequence of form $XX$ appearing in $S$. It is known that an LSS of a string $S$ of length $n$ can be computed using $O(n^2)$ time [Kosowski 2004], or with (model-dependent) polylogarithmic speed-ups using $O(n^2

A. Borghese, F. Coti Zelati, N. Rea, P. Esposito

A few years after its discovery as a magnetar, SGR J1935+2154 started a new burst-active phase on 2020 April 27, accompanied by a large enhancement of its X-ray persistent emission. Radio single bursts were detected during this activation, strengthening the connection between magnetars and fast radio bursts. We report on the X-ray monitoring of SGR J1935+215

Denis V. Vasilyev, Andrey Grankin, Mikhail A. Baranov, Lukas M. Sieberer

We discuss monitoring the time evolution of an analog quantum simulator via a quantum non-demolition (QND) coupling to an auxiliary `clock' qubit. The QND variable of interest is the `energy' of the quantum many-body system, represented by the Hamiltonian of the quantum simulator. We describe a physical implementation of the underlying QND Hamiltonian for Ry

Xiang Fu

This document is the specification of the CC-Light instantiation of executable QASM (eQASM), a quantum instruction set architecture (QISA) developed in QuTech targeting to control a seven-qubit superconducting quantum processor. This document can serve as a reference manual for low-level programmers, compiler backend developers, and microarchitecture impleme

C. G. Wang, Yoshiaki Honjo, L. X. Zhao, G. F. Chen

The electronic and superconducting properties associated with the topologically non-trivial bands in Weyl semimetals have recently attracted much attention. We report the microscopic properties of the type-I Weyl semimetal TaAs measured by $^{75}$As nuclear magnetic (quadrupole) resonance under zero and elevated magnetic fields over a wide temperature range

Bo Pang, Kaiwen Zha, Hanwen Cao, Jiajun Tang

Understanding sequential information is a fundamental task for artificial intelligence. Current neural networks attempt to learn spatial and temporal information as a whole, limited their abilities to represent large scale spatial representations over long-range sequences. Here, we introduce a new modeling strategy called Semi-Coupled Structure (SCS), which

Ce Xu

Recently, a new kind of multiple zeta value level two $T({\bf k})$ (which is called multiple $T$-values) was introduced and studied by Kaneko and Tsumura. In this paper, we define a kind of alternating version of multiple $T$-values, and study several duality formulas of weighted sum formulas about alternating multiple $T$-values by using the methods of iter

Ahmed Abdalazeez, Ira Didenkulova, Denys Dutykh, Céline Labart

The runup of initial Gaussian narrow-banded and wide-banded wave fields and its statistical characteristics are investigated using direct numerical simulations, based on the nonlinear shallow water equations. The bathymetry consists of the section of a constant depth, which is matched with the beach of constant slope. To address different levels of nonlinear

Julia Novo, Samuele Rubino

Proper orthogonal decomposition (POD) stabilized methods for the Navier-Stokes equations are considered and analyzed. We consider two cases, the case in which the snapshots are based on a non inf-sup stable method and the case in which the snapshots are based on an inf-sup stable method. For both cases we construct approximations to the velocity and the pres

Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, Elizabeth Sherly

There is an increasing demand for sentiment analysis of text from social media which are mostly code-mixed. Systems trained on monolingual data fail for code-mixed data due to the complexity of mixing at different levels of the text. However, very few resources are available for code-mixed data to create models specific for this data. Although much research

Dibyendu Roy, Arijit Sinharay, Brojeshwar Bhowmick, Raj Rakshit

In this paper, we propose a novel non-contact vibration measurement system that is competent in estimating linear and/or rotational motions of machine parts. The technique combines microwave radar, standard camera, and optical strobe to capture vibrational or rotational motions in a relatively fast and affordable manner when compared to the current technolog

Anand Prakash Singh

Let $f$ be a transcendental entire function. For $n \in \mathbb{N},$ let $ f^{n}$ denote the $n^{th}$ iterate of $f$. Let $ I(f) = \{z \in \mathbb{C} : f^n \rightarrow \infty $ as $ n \rightarrow \infty \} $ and $ K(f) = \{z: \textrm{ there exists } R > 0 \textrm{ such that } | f^n(z) | \leq R \textrm{ for } n \geq 0 \}. $ Then the set $ \mathbb{C}\ \setminu

Kevin Zelaya, Ian Marquette, Véronique Hussin

In this work, we introduce a new realization of exactly-solvable time-dependent Hamiltonians based on the solutions of the fourth Painlev\'e and the Ermakov equations. The latter is achieved by introducing a shape-invariant condition between an unknown quantum invariant and a set of third-order intertwining operators with time-dependent coefficients. The new

Bharathi Raja Chakravarthi, Vigneshwaran Muralidaran, Ruba Priyadharshini, John P. McCrae

Understanding the sentiment of a comment from a video or an image is an essential task in many applications. Sentiment analysis of a text can be useful for various decision-making processes. One such application is to analyse the popular sentiments of videos on social media based on viewer comments. However, comments from social media do not follow strict ru