July 2019 arXiv papers — page 119

Kenichiro Kimura

We will show that the singular cohomology groups of a smooth quasi-projective complex variety relative to a normal crossing divisor can be described in terms of delta-admissible chains. Roughly speaking, a delta-admissible chain is a simplicial semi-algebraic chain meeting the "faces" properly. As an application, we show that the Abel-Jacobi map for

R. Cartas-Fuentevilla, A. Escalante-Hernandez, A. Herrera-Aguilar, R. Gonzalez-Quaglia

Using a hyperbolic complex plane, we study the realization of the underlying hyperbolic symmetry as an internal symmetry that enables the unification of scalar fields of cosmological and particle physics interest. Such an unification is achieved along the universal prescriptions used in physics, avoiding the use of concepts as Euclideanization, non-canonical

Yanyuet Man, Xiangyun Ding, Xingcheng Yao, Han Bao

Throughout the world, breast cancer is one of the leading causes of female death. Recently, deep learning methods are developed to automatically grade breast cancer of histological slides. However, the performance of existing deep learning models is limited due to the lack of large annotated biomedical datasets. One promising way to relieve the annotating bu

Hamidreza Amini Khorasgani, Hemanta K. Maji, Tamalika Mukherjee

Consider designing a distributed coin-tossing protocol for n processors such that the probability of heads is X0 in [0,1], and an adversary can reset one processor to change the distribution of the final outcome. For X0=1/2, in the non-cryptographic setting, Blum's majority protocol is $\frac1{\sqrt{2πn}}$ insecure. For computationally bounded adversarie

Chenfeng Guo, Dongrui Wu

Multi-view learning (MVL) is a strategy for fusing data from different sources or subsets. Canonical correlation analysis (CCA) is very important in MVL, whose main idea is to map data from different views onto a common space with maximum correlation. Traditional CCA can only be used to calculate the linear correlation of two views. Besides, it is unsupervis

Sai Krishna Hari, Abhishek Nayak, Sivakumar Rathinam

This article presents an approximation algorithm for a task allocation, sequencing and scheduling problem involving a team of human operators and robots. Specifically, we present an algorithm with an approximation ratio as a function of the number of human operators ($m$) and the number of robots ($k$) in the team. The approximation ratios are $\frac{7}{2} -

Alejandro Cohen, Nir Shlezinger, Salman Salamatian, Yonina C. Eldar

Sparse signals are encountered in a broad range of applications. In order to process these signals using digital hardware, they must be first sampled and quantized using an analog-to-digital convertor (ADC), which typically operates in a serial scalar manner. In this work, we propose a method for serial quantization of sparse time sequences (SQuaTS) inspired

Hongjie Dong, Qi S Zhang

We prove the analyticity in time for solutions of two parabolic equations in the whole space, without any decaying or vanishing conditions. One of them involves solutions to the heat equation of exponential growth of order $2$ on $\M$. Here $\M$ is $\R^d$ or a complete noncompact manifold with Ricci curvature bounded from below by a constant. An implication

John M. Correa, Raúul A. Becerra, Asdrubal A. Ramírez, Gerardo Gordillo

Solar cells based on kesterite-type $Cu_2ZnSnS_4$ (CZTS) thin films were fabricated using a chemical route to prepare the $CZTS$ films, consisting in sequential deposition of $Cu_2SnS_3$ (CTS) and $ZnS$ thin films followed by annealing at $550^\circ C$ in nitrogen atmosphere. The $CTS$ compound was prepared in a one-step process using a novel chemical proced

Yao Yu, Giuseppe Michetti, Ahmed Kord, Michele Pirro

This paper reports the first demonstration of a magnet-free, high performance microelectromechanical system (MEMS) based circulator. An innovative circuit based on the commutation of MEMS resonators with high quality (Q) factor using RF switches is designed and implemented. Thanks to the high Q factor, a much smaller modulation frequency can be achieved comp

J. Sengupta, C. Jacob

The effect of Fe and Ni catalysts on the synthesis of carbon nanotubes (CNTs) using atmospheric pressure chemical vapor deposition (APCVD) was investigated. Field emission scanning electron microscopy (FESEM) analysis suggests that the samples grow through a tip growth mechanism. High-resolution transmission electron microscopy (HRTEM) measurements show mult

Nitish Nag, Vaibhav Pandey, Likhita Navali, Prateek Mohan

The health effects of air pollution have been subject to intense study in recent decades. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in morbidity and mortality, especially with regards to respiratory and cardiovascular diseases. Unfortunately, individuals do not have readily accessible methods by w

Frédéric Lavancier, Thierry Pécot, Liu Zengzhen, Charles Kervrann

Colocalization aims at characterizing spatial associations between two fluorescently-tagged biomolecules by quantifying the co-occurrence and correlation between the two channels acquired in fluorescence microscopy. Colocalization is presented either as the degree of overlap between the two channels or the overlays of the red and green images, with areas of

Zhuangzi Li

Image super-resolution is a challenging task and has attracted increasing attention in research and industrial communities. In this paper, we propose a novel end-to-end Attention-based DenseNet with Residual Deconvolution named as ADRD. In our ADRD, a weighted dense block, in which the current layer receives weighted features from all previous levels, is pro

Fuyuan Xiao

In this paper, we generalize the belief function on complex plane from another point of view. We first propose a new concept of complex mass function based on the complex number, called complex basic belief assignment, which is a generalization of the traditional mass function in Dempster-Shafer evidence theory. On the basis of the de nition of complex mass

Antoine Deleforge, Diego Di Carlo, Martin Strauss, Romain Serizel

Unmanned aerial vehicles (UAV), commonly referred to as drones, have raised increasing interest in recent years. Search and rescue scenarios where humans in emergency situations need to be quickly found in areas difficult to access constitute an important field of application for this technology. While research efforts have mostly focused on developing video

Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono

We study the problem of learning sequential decision-making policies in settings with multiple state-action representations. Such settings naturally arise in many domains, such as planning (e.g., multiple integer programming formulations) and various combinatorial optimization problems (e.g., those with both integer programming and graph-based formulations).

Olivier Bodini, Matthieu Dien, Antoine Genitrini, Frédéric Peschanski

In this paper we study the notion of synchronization from the point of view of combinatorics. As a first step, we address the quantitative problem of counting the number of executions of simple processes interacting with synchronization barriers. We elaborate a systematic decomposition of processes that produces a symbolic integral formula to solve the probl

S. I. Dimitrov

In this short paper we shall prove that there exist infinitely many consecutive square-free numbers of the form $[αp]$, $[αp]+1$, where $p$ is prime and $α>0$ is irrational algebraic number. We also establish an asymptotic formula for the number of such square-free pairs when $p$ does not exceed given sufficiently large positive integer.

V. P. Neznamov, I. I. Safronov

We have studied self-conjugate second-order equations with spinor wavefunctions for fermions moving in an external Coulomb field. For stationary states, the equations are characterized by separated states with positive and negative energies, which render probabilistic interpretation possible. For the Coulomb field of attraction, the energy spectrum of the se

David Garfinkle

we hear that..., by David Garfinkle Gravitational-wave Standard Sirens, by Daniel Holz and Maya Fishbach HartleFest, by Gary Horowitz

Ekta U. Samani, Wei Guo, Ashis G. Banerjee

Accurate estimation of the positions and shapes of microscale objects is crucial for automated imaging-guided manipulation using a non-contact technique such as optical tweezers. Perception methods that use traditional computer vision algorithms tend to fail when the manipulation environments are crowded. In this paper, we present a deep learning model for s

John McMillan

A rapid method of finding light leaks in photomultiplier systems is described, in which an audible signal derived from the light level is produced. It uses equipment commonly available in laboratories. In practice it is like using a geiger counter to detect radioactivity.

Yu. F. Novoseltsev, M. M. Boliev, I. M. Dzaparova, M. M. Kochkarov

The experiment on recording neutrino bursts operates since the mid-1980. As the target, we use two parts of the facility with the total mass of 240 tons. The current status of the experiment and some results related to the investigation of background events and the stability of facility operation are presented. Over the period of June 30, 1980 to December 31

Fabrice Daniel

This article studies the financial time series data processing for machine learning. It introduces the most frequent scaling methods, then compares the resulting stationarity and preservation of useful information for trend forecasting. It proposes an empirical test based on the capability to learn simple data relationship with simple models. It also speaks

Japan K. Patel, John J. Kuczek, Richard Vasques

Therapies such as combined-hyperthermia-radiotherapy (CHR) take advantage of excellent radiosensitization properties of hyperthermia and treat of tumors with both radiation and heat. To appropriately model a CHR treatment, features like tumor heating (heat transfer), dosimetry (radiation transport), and tumor dynamics (cell population dynamics) must be consi

Surendra Kumar Soni, Pavan Kumar Kirar, Pankaj Kolhe, Kirti Chandra Sahu

We experimentally investigate the deformation and breakup of droplets interacting with an oblique continuous air stream. A high-speed imaging system is employed to record the trajectories and topological changes of the droplets of different liquids. The droplet size, the orientation of the air nozzle to the horizontal and fluid properties (surface tension an

Lamei Yuan, Yanjie Wang

Let $\mathcal{R}$ be a free Lie conformal algebra of rank $2$ with $\mathbb{C}[\partial]$-basis $\{L,I\}$ and relations \begin{eqnarray*} \left[L_λ L\right]=(\partial+2 λ) (L+I),\ \left[L_λ I\right]=(\partial+λ) I, \ \left[I_λ L\right]=λI,\ \left[I_λ I\right]=0. \end{eqnarray*} In this paper, we first classify all finite nontrivial irreducible conformal modu

Miaowen Wen, Beixiong Zheng, Kyeong Jin Kim, Marco Di Renzo

Spatial modulation (SM) is an innovative and promising digital modulation technology that strikes an appealing trade-off between spectral efficiency and energy efficiency with a simple design philosophy. SM enjoys plenty of benefits and shows great potential to fulfill the requirements of future wireless communications. The key idea behind SM is to convey ad

Alexander Birx, Yann Disser, Kevin Schewior

We consider the open, non-preemptive online Dial-a-Ride problem on the real line, where transportation requests appear over time and need to be served by a single server. We give a lower bound of 2.0585 on the competitive ratio, which is the first bound that strictly separates online Dial-a-Ride on the line from online TSP on the line in terms of competitive

Lia Morra, Fabrizio Lamberti

Unsupervised near-duplicate detection has many practical applications ranging from social media analysis and web-scale retrieval, to digital image forensics. It entails running a threshold-limited query on a set of descriptors extracted from the images, with the goal of identifying all possible near-duplicates, while limiting the false positives due to visua

V. V. Sargsyan, H. Lenske, G. G. Adamian, N. V. Antonenko

The evolution of contact binary star systems in mass asymmetry (transfer) coordinate is considered. The orbital period changes is explained by an evolution in mass asymmetry towards the symmetry (symmetrization of binary system). It is predicted that a decreasing and an increasing orbital periods are related, respectively, with the non-overlapping and overla

Marcos Castelli, Gleb Doronin

Initial-boundary value problem for the modified Zakharov-Kuznetsov equation posed on a bounded rectangle is considered. The main difficulty is the critical power in nonlinear term. The results on existence, uniqueness and asymptotic behavior of solutions are presented.

Eloisa Detomi, Guram Donadze, Marta Morigi, Pavel Shumyatsky

Let $γ_n=[x_1,\dots,x_n]$ be the $n$th lower central word. Denote by $X_n$ the set of $γ_n$-values in a group $G$ and suppose that there is a number $m$ such that $|g^{X_n}|\leq m$ for each $g\in G$. We prove that $γ_{n+1}(G)$ has finite $(m,n)$-bounded order. This generalizes the much celebrated theorem of B. H. Neumann that says that the commutator subgrou

Mario Santilli

We prove that the support of an $ m $ dimensional rectifiable varifold with a uniform lower bound on the density and bounded generalized mean curvature can be covered $ \mathscr{H}^{m} $ almost everywhere by a countable union of $m$ dimensional submanifolds of class $ \mathcal{C}^{2} $. We obtain this result using the notion of curvature of arbitrary closed

Kenjiro Kondo, Akihiko Ishikawa, Masashi Kimura

Early prediction of the prevalence of influenza reduces its impact. Various studies have been conducted to predict the number of influenza-infected people. However, these studies are not highly accurate especially in the distant future such as over one month. To deal with this problem, we investigate the sequence to sequence (Seq2Seq) with attention model us

Mai T. P. Le, Luca Sanguinetti, Emil Björnson, Maria-Gabriella Di Benedetto

In overloaded Massive MIMO systems, wherein the number K of user equipments (UEs) exceeds the number of base station antennas M, it has recently been shown that non-orthogonal multiple access (NOMA) can increase performance. This paper aims at identifying cases of the classical operating regime K < M, where code-domain NOMA can also improve the spectral effi

F. William Townes

Generalized principal component analysis (GLM-PCA) facilitates dimension reduction of non-normally distributed data. We provide a detailed derivation of GLM-PCA with a focus on optimization. We also demonstrate how to incorporate covariates, and suggest post-processing transformations to improve interpretability of latent factors.

Ankita Shukla, Gullal Singh Cheema, Saket Anand, Qamar Qureshi

Ecological imbalance owing to rapid urbanization and deforestation has adversely affected the population of several wild animals. This loss of habitat has skewed the population of several non-human primate species like chimpanzees and macaques and has constrained them to co-exist in close proximity of human settlements, often leading to human-wildlife confli

S. Frauendorf, M. Beard, M. Mumpower, R. Schwengner

A pronounced spike at low energy in the strength function for magnetic radiation (LEMAR) is found by means of Shell Model calculations, which explains the experimentally observed enhancement of the dipole strength. LEMAR originates from statistical low-energy M1-transitions between many excited complex states. Re-coupling of the proton and neutron high-j orb

Maarten de Jong

A C++ software design is presented that can be used to interpolate data in any number of dimensions. The design is based on a combination of templates of functional collections of elements and so-called type lists. The design allows for different search methodologies and interpolation techniques in each dimension. It is also possible to expand and reduce the

Abderrazak Chahid, Fahad Albalawi, Turky Nayef Alotaiby, Majed Hamad Al-Hameed

Epilepsy is a neurological disorder classified as the second most serious neurological disease known to humanity, after stroke. Localization of the epileptogenic zone is an important step for epileptic patient treatment, which starts with epileptic spike detection. The common practice for spike detection of brain signals is via visual scanning of the recordi

Arnaud Ducrot, Thomas Giletti, Hiroshi Matano

We investigate spreading properties of solutions of a large class of two-component reaction-diffusion systems, including prey-predator systems as a special case. By spreading properties we mean the long time behaviour of solution fronts that start from localized (i.e. compactly supported) initial data. Though there are results in the literature on the existe

Hlynur Davíð Hlynsson, Alberto N. Escalante-B., Laurenz Wiskott

In this paper, we propose a new experimental protocol and use it to benchmark the data efficiency --- performance as a function of training set size --- of two deep learning algorithms, convolutional neural networks (CNNs) and hierarchical information-preserving graph-based slow feature analysis (HiGSFA), for tasks in classification and transfer learning sce

Nursadul Mamun, Soheil Khorram, John H. L. Hansen

Attempts to develop speech enhancement algorithms with improved speech intelligibility for cochlear implant (CI) users have met with limited success. To improve speech enhancement methods for CI users, we propose to perform speech enhancement in a cochlear filter-bank feature space, a feature-set specifically designed for CI users based on CI auditory stimul

Mohamed Grissa, Attila A. Yavuz, Bechir Hamdaoui

Spectrum database-based cognitive radio networks (CRNs) have become the de facto approach for enabling unlicensed secondary users (SUs) to identify spectrum vacancies in channels owned by licensed primary users (PUs). Despite its merits, the use of spectrum databases incurs privacy concerns for both SUs and PUs. Single-server private information retrieval (P

Liliana Borcea, Josselin Garnier

The goal of synthetic aperture imaging is to estimate the reflectivity of a remote region of interest by processing data gathered with a moving sensor which emits periodically a signal and records the backscattered wave. We introduce and analyze a high-resolution interferometric method for synthetic aperture imaging through an unknown scattering medium which

David Cheban

The known Levitan&#39;s Theorem states that the linear differential equation $$ x&#39;=A(t)x+f(t) \ \ \ (*) $$ with Bohr almost periodic coefficients $A(t)$ and $f(t)$ admits at least one Levitan almost periodic solution if it has a bounded solution. The main assumption in this theorem is the separation among bounded solutions of homogeneous equations $$ x&#

Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini

Reconstructing observed images from fMRI brain recordings is challenging. Unfortunately, acquiring sufficient &#34;labeled&#34; pairs of {Image, fMRI} (i.e., images with their corresponding fMRI responses) to span the huge space of natural images is prohibitive for many reasons. We present a novel approach which, in addition to the scarce labeled data (train

Samuel S. Ogden, Tian Guo

Today&#39;s clusters often have to divide resources among a diverse set of jobs. These jobs are heterogeneous both in execution time and in their rate of arrival. Execution time heterogeneity has lead to the development of hybrid schedulers that can schedule both short and long jobs to ensure good task placement. However, arrival rate heterogeneity, or burst

Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala

Differential privacy, a notion of algorithmic stability, is a gold standard for measuring the additional risk an algorithm&#39;s output poses to the privacy of a single record in the dataset. Differential privacy is defined as the distance between the output distribution of an algorithm on neighboring datasets that differ in one entry. In this work, we prese

Ankit Sharma, Hassan Foroosh

We introduce a computationally-efficient CNN micro-architecture Slim Module to design a lightweight deep neural network Slim-Net for face attribute prediction. Slim Modules are constructed by assembling depthwise separable convolutions with pointwise convolution to produce a computationally efficient module. The problem of facial attribute prediction is chal

Yuki M. Asano, Jakob J. Kolb, Jobst Heitzig, J. Doyne Farmer

Standard macroeconomic models assume that households are rational in the sense that they are perfect utility maximizers, and explain economic dynamics in terms of shocks that drive the economy away from the stead-state. Here we build on a standard macroeconomic model in which a single rational representative household makes a savings decision of how much to

Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang

Modern deep learning applications urge to push the model inference taking place at the edge devices for multiple reasons such as achieving shorter latency, relieving the burden of the network connecting to the cloud, and protecting user privacy. The Convolutional Neural Network (\emph{CNN}) is one of the most widely used model family in the applications. Giv

Daesung Yu, Junbeom Kim, Seok-Hwan Park

This work studies the optimization of rate-splitting multiple access (RSMA) transmission technique for a cloud radio access network (C-RAN) downlink system. Main idea of RSMA is to split the message for each user equipment (UE) to private and common messages and perform superposition coding at transmitters so as to enable flexible decoding at receivers. It i

Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang

We develop a method for obtaining safe initial policies for reinforcement learning via approximate dynamic programming (ADP) techniques for uncertain systems evolving with discrete-time dynamics. We employ kernelized Lipschitz estimation and semidefinite programming for computing admissible initial control policies with provably high probability. Such admiss

Florian Piewak, Peter Pinggera, Marius Zöllner

State-of-the-art approaches for the semantic labeling of LiDAR point clouds heavily rely on the use of deep Convolutional Neural Networks (CNNs). However, transferring network architectures across different LiDAR sensor types represents a significant challenge, especially due to sensor specific design choices with regard to network architecture as well as da

Hagen Knaf, Erich Selder, Karlheinz Spindler

We derive an efficient algorithm to find solutions to Euler&#39;s concordant form problem and rational points on elliptic curves associated with this problem.

Leonid Piterbarg

Inertial particles in 2D driven by a Gaussian white noise forcing are considered. For two examples of the forcing (compressible and incompressible) upper and lower bounds are found for the mean number of caustics as a function of Stokes number. Efficiency of the bounds is verified by numerical methods.

Frédéric Simard

Link Streams were proposed a few years ago as a model of temporal networks. We seek to understand the topological and temporal nature of those objects through efficiently computing the distances, latencies and lengths of shortest fastest paths. We develop different algorithms to compute those values efficiently. Proofs of correctness for those methods are pr

Suzan Ali, Tousif Osman, Mohammad Mannan, Amr Youssef

Open access WiFi hotspots are widely deployed in many public places, including restaurants, parks, coffee shops, shopping malls, trains, airports, hotels, and libraries. While these hotspots provide an attractive option to stay connected, they may also track user activities and share user/device information with third-parties, through the use of trackers in

Thomas Alazard, Omar Lazar

We paralinearize the Muskat equation to extract an explicit parabolic evolution equation having a compact form. This result is applied to give a simple proof of the local well-posedness of the Cauchy problem for rough initial data, in homogeneous Sobolev spaces $\dot{H}^1(\mathbb{R})\cap \dot{H}^s(\mathbb{R})$ with $s>3/2$. This paper is essentially self-con

Richard Varro

Peirce-evanescent baric identities are polynomial identities verified by baric algebras such that their Peirce polynomials are the null polynomial. In this paper procedures for constructing such homogeneous and non homogeneous identities are given. For this we define an algebraic system structure on the free commutative nonassociative algebra generated by a

Sarah Bockting-Conrad, Hau-Wen Huang

Let $\mathbb{F}$ denote a field with ${\rm char\,}\mathbb{F}\not=2$. The Racah algebra $\Re$ is the unital associative $\mathbb{F}$-algebra defined by generators and relations in the following way. The generators are $A$, $B$, $C$, $D$. The relations assert that \begin{equation*} [A,B]=[B,C]=[C,A]=2D \end{equation*} and each of the elements \begin{gather*} α

Noah Forman, Soumik Pal, Douglas Rizzolo, Matthias Winkel

We first consider interval partitions whose complements are Lebesgue-null and introduce a complete metric that induces the same topology as the Hausdorff distance (between complements). This is done using correspondences between intervals. Further restricting to interval partitions with alpha-diversity, we then adjust the metric to incorporate diversities. W

Pál András Papp, Roger Wattenhofer

We analyze the stabilization time of minority processes in graphs. A minority process is a dynamically changing coloring, where each node repeatedly changes its color to the color which is least frequent in its neighborhood. First, we present a simple $Ω(n^2)$ stabilization time lower bound in the sequential adversarial model. Our main contribution is a grap

Thomas J. Maccarone, Thomas J. Nelson, Peter J. Brown, Koji Mukai

Supersoft X-ray sources are stellar objects which emit X-rays with temperatures of about 1 million Kelvin and luminosities well in excess of what can be produced by stellar coronae. It has generally been presumed that the objects in this class are binary star systems in which mass transfer leads to nuclear fusion on the surface of a white dwarf. Classical no

Marat Dukhan

Deep learning frameworks commonly implement convolution operators with GEMM-based algorithms. In these algorithms, convolution is implemented on top of matrix-matrix multiplication (GEMM) functions, provided by highly optimized BLAS libraries. Convolutions with 1x1 kernels can be directly represented as a GEMM call, but convolutions with larger kernels requi

Subarno Banerjee, Lazaro Clapp, Manu Sridharan

NullPointerExceptions (NPEs) are a key source of crashes in modern Java programs. Previous work has shown how such errors can be prevented at compile time via code annotations and pluggable type checking. However, such systems have been difficult to deploy on large-scale software projects, due to significant build-time overhead and / or a high annotation bur

ChangYu Hsieh, Junjie Liu, Chenru Duan, Jianshu Cao

We propose a nonequilibrium variational polaron transformation, based on an ansatz for nonequilibrium steady state (NESS) with an effective temperature, to study quantum heat transport at the nanoscale. By combining the variational polaron transformed master equation with the full counting statistics, we have extended the applicability of the polaron-based f

Shitij Kumar, Ferat Sahin

In this paper, an analysis of the sensing volume coverage of robot workspace as well as the shared human-robot collaborative workspace for various configurations of on-robot Time-of-Flight (ToF) sensor array rings is presented. A methodology for volumetry using octrees to quantify the detection/sensing volume of the sensors is proposed. The change in sensing

Kaye Silva

We study an abstract equation in a reflexive Banach space, depending on a real parameter $λ$. The equation is composed by homogeneous potential operators. By analyzing the Nehari sets, we prove a bifurcation result. In some particular cases we describe the full bifurcation diagram, and in general, we estimate the parameter $λ_b$ for which the problem does no

Isaac Shiri, Hassan Maleki, Ghasem Hajianfar, Hamid Abdollahi

Aim: In the present work, we aimed to evaluate a comprehensive radiomics framework that enabled prediction of EGFR and KRAS mutation status in NSCLC cancer patients based on PET and CT multi-modalities radiomic features and machine learning (ML) algorithms. Methods: Our study involved 211 NSCLC cancer patient with PET and CTD images. More than twenty thousan

Rodrigo S. Gonçalves, Susana Landau, Jailson S. Alcaniz, Rodrigo F. L. Holanda

The possibility of variation of the fundamental constants of nature has been a long-standing question, with important consequences for fundamental physics and cosmology. In particular, it has been shown that variations in the fine-structure constant, $α$, are directly related to violation of the distance duality relation (DDR), which holds true as long as ph

Paria Mehrani, Andrei Mouraviev, John K. Tsotsos

There is still much to understand about the color processing mechanisms in the brain and the transformation from cone-opponent representations to perceptual hues. Moreover, it is unclear which areas(s) in the brain represent unique hues. We propose a hierarchical model inspired by the neuronal mechanisms in the brain for local hue representation, which revea

Nicolau Molina Bom, Érik Oda Usuda, Mariana da Silva Gigliotti, Denílson José Marcolino de Aguiar

Management of discarded tires is a compelling environmental issue worldwide. Although several approaches have been developed to recycle waste tire rubbers, their application in solid-state cooling is still unexplored. Considering the high barocaloric potential verified for elastomers, the use of waste tire rubber (WTR) as refrigerant in solid-state cooling d

Anna Hughes, Aaron Boley, Rachel Osten, Jacob White

TRAPPIST-1 is an ultracool dwarf (UCD) with a system of 7 terrestrial planets, at least three of which orbit in the habitable zone. The radio emission of such low-mass stars is poorly understood; few UCDs have been detected at radio frequencies at all, and the likelihood of detection is only loosely correlated with stellar properties. Relative to other low-m

Jimit Doshi, Guray Erus, Mohamad Habes, Christos Davatzikos

Segmentation has been a major task in neuroimaging. A large number of automated methods have been developed for segmenting healthy and diseased brain tissues. In recent years, deep learning techniques have attracted a lot of attention as a result of their high accuracy in different segmentation problems. We present a new deep learning based segmentation meth

Ana Inés Ennis, Lilia Patricia Bassino, Juan Pablo Caso, Bruno Javier De Bórtoli

We present the results of a photometric study of the early-type galaxy NGC 6876 and the surrounding globular cluster system (GCS). The host galaxy is a massive elliptical, the brightest of this type in the Pavo Group. According to its intrinsic brightness (M_v~-22.7), it is expected to belong to a galaxy cluster instead of a poor group. Observational materia

Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In the last year, the company adopted Semantic Web technologies to create a knowledge graph that aims to represent the vast amount of content and users on Pinterest, t

M. Carmen Calderón-Moreno, Pablo J. Gerlach-Mena, José A. Prado-Bassas

In this paper we look for the existence of large linear and algebraic structures of sequences of measurable functions with different modes of convergence. Concretely, the algebraic size of the family of sequences that are convergent in measure but not a.e.~pointwise, uniformly but not pointwise convergent, and uniformly convergent but not in $L^1$-norm, are

Tanmay Randhavane, Aniket Bera, Kyra Kapsaskis, Rahul Sheth

We present a novel, real-time algorithm, EVA, for generating virtual agents with various perceived emotions. Our approach is based on using Expressive Features of gaze and gait to convey emotions corresponding to happy, sad, angry, or neutral. We precompute a data-driven mapping between gaits and their perceived emotions. EVA uses this gait emotion associati

Emir Hrnjic, Nikodem Tomczak

Behavioral economics changed the way we think about market participants and revolutionized policy-making by introducing the concept of choice architecture. However, even though effective on the level of a population, interventions from behavioral economics, nudges, are often characterized by weak generalisation as they struggle on the level of individuals. R

J. M. D. S. Dos Santos, A. P. Silveira, A. E. S. Trocado

In order to implement a STEAM approach including the use of technology, namely the use of interactive mathematics software GeoGebra, in mathematics classes, in the lusophone space, the materials presented here were conceived, to be implemented in a first phase among teachers. Later, with the necessary adaptations, these tasks will be applied to the students.

Yanhong Wu

Quick detection of common changes is critical in sequential monitoring of multi-stream data where a common change is referred as a change that only occurs in a portion of panels. After a common change is detected by using a combined CUSUM-SR procedure, we first study the joint distribution for values of the CUSUM process and the estimated delay detection tim

Domonkos Varga

Significant progress has been made in the past decade for full-reference image quality assessment (FR-IQA). However, new large scale image quality databases have been released for evaluating image quality assessment algorithms. In this study, our goal is to give a comprehensive evaluation of state-of-the-art FR-IQA metrics using the recently published KADID-

Galen Reeves, Henry Pfister

The ability to understand and solve high-dimensional inference problems is essential for modern data science. This article examines high-dimensional inference problems through the lens of information theory and focuses on the standard linear model as a canonical example that is both rich enough to be practically useful and simple enough to be studied rigorou

Michael de Moraes, Josnei Novacoski

In this paper we present a matricial result that generalizes Hironaka&#39;s game and Perron transforms simultaneously. We also show how one can deduce the various forms in which the algorithm of Perron appears in proofs of local uniformization from our main result.

James Angthopo, Ignacio Ferreras, Joseph Silk

The distribution of galaxies on a colour-magnitude diagram reveals a bimodality, featuring a passively evolving red sequence and a star-forming blue cloud. The region between these two, the Green Valley (GV), represents a fundamental transition where quenching processes operate. We exploit an alternative definition of the GV using the 4,000 Angstrom break st

Maira Gatti de Bayser, Paulo Cavalin, Claudio Pinhanez, Bianca Zadrozny

This paper investigates the application of machine learning (ML) techniques to enable intelligent systems to learn multi-party turn-taking models from dialogue logs. The specific ML task consists of determining who speaks next, after each utterance of a dialogue, given who has spoken and what was said in the previous utterances. With this goal, this paper pr

Soumak Maitra, Raghunathan Srianand, Patrick Petitjean, Hadi Rahmani

We present analysis of two- and three-point correlation functions of Ly$α$ forest (at $2\le z\le 2.5$) using X-Shooter spectra of three background quasar triplets probing transverse separations of 0.5-1.6 pMpc. We present statistics based on transmitted flux and clouds identified using Voigt profile fitting. We show that the observed two-, three-point correl

Riccarda Bonsignori, Paola Ruggiero, Pasquale Calabrese

We consider the symmetry resolved Rényi entropies in the one dimensional tight binding model, equivalent to the spin-1/2 XX chain in a magnetic field. We exploit the generalised Fisher-Hartwig conjecture to obtain the asymptotic behaviour of the entanglement entropies with a flux charge insertion at leading and subleading orders. The o(1) contributions are f

Michael Kuffmeier, Hannah Calcutt, Lars E. Kristensen

Observations with modern instruments such as Herschel reveal that stars form clustered inside filamentary arms of ~1 pc length embedded in Giant Molecular Clouds. On smaller scales (~1000 au), observations of, e.g., IRAS 16293--2422 show signs of filamentary `bridge&#39; structures connecting young protostars in their birth environment. We investigate the fo

Ignacio D. Gargiulo, Antonela Monachesi, Facundo A. Gómez, Robert J. J. Grand

We study the galactic bulges in the Auriga simulations, a suite of thirty cosmological magneto-hydrodynamical zoom-in simulations of late-type galaxies in Milky Way-sized dark matter haloes performed with the moving-mesh code AREPO. We aim to characterize bulge formation mechanisms in this large suite of galaxies simulated at high resolution in a fully cosmo

I. M. Christie, A. Lalakos, A. Tchekhovskoy, R. Fernández

Neutron star mergers are unique laboratories of accretion, ejection, and r-process nucleosynthesis. We used 3D general relativistic magnetohydrodynamic simulations to study the role of the post-merger magnetic geometry in the evolution of merger remnant discs around stationary Kerr black holes. Our simulations fully capture mass accretion, ejection, and jet

I. Soszyński, A. Udalski, M. K. Szymański, P. Pietrukowicz

We present the final release of the OGLE collection of classical pulsators (Cepheids and RR Lyr stars) in the Large and Small Magellanic Clouds. The sky coverage has been increased from 670 to 765 square degrees compared to the previous edition of the collection. We also add some Cepheids and RR Lyr stars found by the Gaia team and reclassify three Cepheids.

Masato Minamitsuji, James Edholm

We show that most classes of shift-symmetric degenerate higher-order scalar-tensor (DHOST) theories which satisfy certain degeneracy conditions are not compatible with the conditions for the existence of exact black hole solutions with a linearly time-dependent scalar field whose canonical kinetic term takes a constant value. Combined with constraints from t

Andreas Koch, Siyi Xu, R. Michael Rich

Globular clusters (GCs) in the outer Milky Way halo are important tracers of the assembly history of our Galaxy. Only a few of these objects show spreads in heavier elements beyond the canonical light-element variations that have essentially been found throughout the entire Galactic GC system, suggesting a more complex origin and evolution of these objects.

Zhongbo Yan

As platforms of Majorana modes, topological insulator (quantum anomalous Hall insulator)/superconductor (SC) heterostructures have attracted tremendous attention over the past decade. Here we substitute the topological insulator by its higher-order counterparts. Concretely, we consider second-order topological insulators (SOTIs) without time-reversal symmetr

Bert Vandenbroucke, Kenneth Wood

There is strong evidence that the diffuse ionized gas (DIG) in disc galaxies is photoionized by radiation from UV luminous O and B stars in the galactic disc, both from observations and detailed numerical models. However, it is still not clear what mechanism is responsible for providing the necessary pressure support for a diffuse gas layer at kpc-scale abov