December 2020 arXiv papers — page 112

Xiuying Liu, Frane Lunić, Daohong Song, Zhixuan Dai

The toolbox quantities used for manipulating the flow of light include typically amplitude, phase, and polarization. Pseudospins, such as those arising from valley degrees of freedom in photonic structures, have recently emerged as an excellent candidate for this toolbox, in parallel with rapid development of spintronics and valleytronics in condensed-matter

Matteo Simioni, Carmelo Arcidiacono, Andrea Grazian, Yann Clenet

The point spread function reconstruction (PSF-R) capability is a deliverable of the MICADO@ESO-ELT project. The PSF-R team works on the implementation of the instrument software devoted to reconstruct the point spread function (PSF), independently of the science data, using adaptive optics (AO) telemetry data, both for Single Conjugate (SCAO) and Multi-Conju

Marco Gaido, Beatrice Savoldi, Luisa Bentivogli, Matteo Negri

In automatic speech translation (ST), traditional cascade approaches involving separate transcription and translation steps are giving ground to increasingly competitive and more robust direct solutions. In particular, by translating speech audio data without intermediate transcription, direct ST models are able to leverage and preserve essential information

Denis Coquenet, Yann Soullard, Clément Chatelain, Thierry Paquet

Unconstrained handwritten text recognition remains an important challenge for deep neural networks. These last years, recurrent networks and more specifically Long Short-Term Memory networks have achieved state-of-the-art performance in this field. Nevertheless, they are made of a large number of trainable parameters and training recurrent neural networks do

Ahmed Ali Abdelalim, Biswaranjan Das, Shaaban Khalil, Stefano Moretti

In the context of the $B-L$ Supersymmetric Standard Model (BLSSM), we investigate the consistency of a light Higgs boson, with mass around $90-95$ GeV, with the results of a search performed by the CMS collaboration in the di-photon channel at the integrated luminosity of 35.9 fb$^{-1}$ and $\sqrt s$ = 13 TeV.

Vasil Khalidov, Florence Forbes, Radu Horaud

The problem of multimodal clustering arises whenever the data are gathered with several physically different sensors. Observations from different modalities are not necessarily aligned in the sense there there is no obvious way to associate or to compare them in some common space. A solution may consist in considering multiple clustering tasks independently

Haiming Liu, Huanli Gao, Shuping Guo, He Cai

This paper studies the distributed dual objective control problem of a heterogenous flywheel energy storage matrix system aiming at simultaneous reference power track-ing and state-of-energy balancing. We first prove that the solution to this problem exists by showing the existence of a common state-of-energy trajectory for all the flywheel systems on which

Juan Emmanuel Johnson, Valero Laparra, Gustau Camps-Valls

Gaussian Processes (GPs) are a class of kernel methods that have shown to be very useful in geoscience applications. They are widely used because they are simple, flexible and provide very accurate estimates for nonlinear problems, especially in parameter retrieval. An addition to a predictive mean function, GPs come equipped with a useful property: the pred

Wenyi Xiao, Huan Zhao, Haojie Pan, Yangqiu Song

In modern social media platforms, an effective content recommendation should benefit both creators to bring genuine benefits to them and consumers to help them get really interesting content. To address the limitations of existing methods for social recommendation, we propose Social Explorative Attention Network (SEAN), a social recommendation framework that

Tony Liimatainen, Yi-Hsuan Lin, Mikko Salo, Teemu Tyni

We study inverse problems for semilinear elliptic equations with fractional power type nonlinearities. Our arguments are based on the higher order linearization method, which helps us to solve inverse problems for certain nonlinear equations in cases where the solution for a corresponding linear equation is not known. By using a fractional order adaptation o

R. Correa, A. Hantoute, M. A. López

The first part of the paper provides new characterizations of the normal cone to the effective domain of the supremum of an arbitrary family of convex functions. These results are applied in the second part to give new formulas for the subdifferential of the supremum function, which use both the active and nonactive functions at the reference point. Only the

Xi Cheng, Emiliana Fabbri, Yuya Yamashita, Ivano E. Castelli

The correlation between ex situ electronic conductivity, oxygen vacancy content, flat-band potential (Efb), and the oxygen evolution reaction (OER) activity for a wide range of perovskite compositions are investigated experimentally and theoretically. It is found that all of these parameters can affect the OER activity; however, none of them alone play a cru

Pierre-Emmanuel Chaput, Nicolas Perrin

In a previous paper Affine symmetries of the equivariant quantum cohomology of rational homogeneous spaces, a general formula was given for the multiplication by some special Schubert classes in the quantum cohomology of any homogeneous space. Although this formula is correct in the non equivariant setting, the stated equivariant version was wrong. We provid

Kumari Deepshikha, Anugunj Naman

Class imbalance is a challenging issue in practical classification problems for deep learning models as well as for traditional models. Traditionally successful countermeasures such as synthetic over-sampling have had limited success with complex, structured data handled by deep learning models. In this work, we propose to use a Generative Adversarial Networ

Yadong Zhang, Xin Chen

In the time-series analysis, the time series motifs and the order patterns in time series can reveal general temporal patterns and dynamic features. Triadic Motif Field (TMF) is a simple and effective time-series image encoding method based on triadic time series motifs. Electrocardiography (ECG) signals are time-series data widely used to diagnose various c

Venice Erin Liong, Thi Ngoc Tho Nguyen, Sergi Widjaja, Dhananjai Sharma

In this paper, we present an Assertion-based Multi-View Fusion network (AMVNet) for LiDAR semantic segmentation which aggregates the semantic features of individual projection-based networks using late fusion. Given class scores from different projection-based networks, we perform assertion-guided point sampling on score disagreements and pass a set of point

Julia Auernhammer, Alena K. Bell, Marcus Schulze, Yue Du

Polymer coatings on cellulosic fibres are widely used to enhance the natural fibre properties by improving, for example, the hydrophobicity and wet strength. Here, we investigate the effects of a terpolymer P(S-co-MABP-co-PyMA) coating on cotton linters and eucalyptus fibres to improve the resistance of cellulose fibres against wetness. Coated and uncoated f

Alexandra Angerd, Keshav Balasubramanian, Murali Annavaram

Modern machine learning techniques are successfully being adapted to data modeled as graphs. However, many real-world graphs are typically very large and do not fit in memory, often making the problem of training machine learning models on them intractable. Distributed training has been successfully employed to alleviate memory problems and speed up training

Chonghyuk Song, Eunseok Kim, Inwook Shim

Integrating model-based machine learning methods into deep neural architectures allows one to leverage both the expressive power of deep neural nets and the ability of model-based methods to incorporate domain-specific knowledge. In particular, many works have employed the expectation maximization (EM) algorithm in the form of an unrolled layer-wise structur

Aozhu Chen, Xinyi Huang, Hailan Lin, Xirong Li

Cross-lingual image captioning, with its ability to caption an unlabeled image in a target language other than English, is an emerging topic in the multimedia field. In order to save the precious human resource from re-writing reference sentences per target language, in this paper we make a brave attempt towards annotation-free evaluation of cross-lingual im

M. S. Butuzova, A. B. Pushkarev, E. S. Shablovinskaya, S. V. Nazarov

For the interpretation of X-ray radiation from kiloparsec jets of quasars, the inverse Compton scattering of the cosmic microwave background has been widely used for almost 20 years. A recent analysis of the Fermi-LAT observational data showed that this assumption is inapplicable for jets of several quasars. In this paper, we consider the inverse Compton sca

Emiliano Díaz, Adrián Pérez-Suay, Valero Laparra, Gustau Camps-Valls

This paper introduces a novel statistical regression framework that allows the incorporation of consistency constraints. A linear and nonlinear (kernel-based) formulation are introduced, and both imply closed-form analytical solutions. The models exploit all the information from a set of drivers while being maximally independent of a set of auxiliary, protec

Bae Jung Kim, Xi Cheng, Daniel Abbott, Emiliana Fabbri

It is shown that producing PrBaCo2O5 and Ba0.5Sr0.5Co0.8Fe0.2O3 nanoparticle by a scalable synthesis method leads to high mass activities for the oxygen evolution reaction with outstanding improvements by 10 and 50 times, respectively, compared to those prepared via the state of the art synthesis method. Here, detailed comparisons at both laboratory and indu

José A. Padrón-Hidalgo, Valero Laparra, Nathan Longbotham, Gustau Camps-Valls

Anomalous change detection (ACD) is an important problem in remote sensing image processing. Detecting not only pervasive but also anomalous or extreme changes has many applications for which methodologies are available. This paper introduces a nonlinear extension of a full family of anomalous change detectors. In particular, we focus on algorithms that util

Wenzhe Liu, Wei Liu, Lei Shi, Yuri Kivshar

Polarization singularities of vectorial electromagnetic fields locate at the positions (such as points, lines, or surfaces) where properties of polarization ellipses are not defined. They are manifested as circular and linear polarization, for which respectively the semi-major axes and normal vectors of polarization ellipses become indefinite. First observed

Xenia Klimentova, Péter Biró, Ana Viana, Virginia Costa

Kidney exchange programs (KEP's) represent an additional possibility of transplant for patients suffering from end stage kidney disease. If a patient has a willing living donor with whom the patient is not compatible, the pair patient--donor can join a pool of incompatible pairs and, if compatibility between patient and donor in two our more pairs exists

Md Habib Ullah, Anas Alseyat, Jae-Do Park

The rapid growth of proactive consumers with distributed power generation and storage capacity, empowered by Internet of Things (IoT) devices, is transforming modern power markets into an independent, flexible, and distributed structure. In particular, the recent trend is peer-to-peer (P2P) transactive energy systems, wherein the traditional consumers became

Carlo Sanna

For every positive integer $n$ and for every $α\in [0, 1]$, let $\mathcal{B}(n, α)$ denote the probabilistic model in which a random set $\mathcal{A} \subseteq \{1, \dots, n\}$ is constructed by picking independently each element of $\{1, \dots, n\}$ with probability $α$. Cilleruelo, Rué, Šarka, and Zumalacárregui proved an almost sure asymptotic formula for

Cihan Tugrul Cicek, Zuo-Jun Max Shen, Hakan Gultekin, Bulent Tavli

We address a dynamic covering location problem of an Unmanned Aerial Vehicle Base Station (UAV-BS), where the location sequence of a single UAV-BS in a wireless communication network is determined to satisfy data demand arising from ground users. This problem is especially relevant in the context of smart grid and disaster relief. The vertical movement abili

Giovanni Abramo, Ciriaco Andrea D'Angelo, Flavia Di Costa

Literature about the scholarly impact of scientific research offers very few contributions on private sector research, and the comparison with public sector. In this work, we try to fill this gap examining the citation-based impact of Italian 2010-2017 publications distinguishing authorship by the private sector from the public sector. In particular, we inve

Amit Kumar Mandal, Suvendu Rakshit, C. S. Stalin, Dominika Wylezalek

We report results of the dust reverberation mapping (DRM) on the Seyfert 1 galaxy Z229-15 at z = 0.0273. Quasi-simultaneous photometric observations for a total of 48 epochs were acquired during the period 2017 July to 2018 December in B, V, J, H and Ks bands. The calculated spectral index (α) between B and V bands for each epoch was used to correct for the

Xina Zhang

In this paper, based on the theory of defining sets, a class of four-weight or five-weight linear codes over Fp is constructed. The complete weight enumerators of the linear codes are determined by means of Weil sums. In some case, there is an almost optimal code with respect to Griesmer bound, which is also an optimal one according to the online code table.

Nuki Susanti, Holger Grosshans

Deposits which form during the pneumatic transport of particles are a frequent source of explosions in industrial facilities. Thus, to contribute to the operational safety of industrial plants, we explore the deposit formation of powder flows with our new experimental test-rig. To this end, the particle flow was analyzed optically using a square-shaped trans

Hilmi Kumdakcı, Cihan Öngün, Alptekin Temizel

Scarcity of training data is one of the prominent problems for deep networks which require large amounts data. Data augmentation is a widely used method to increase the number of training samples and their variations. In this paper, we focus on improving vehicle detection performance in aerial images and propose a generative augmentation method which does no

N. Pinto, C. Di Nicola, A. Trapananti, M. Minicucci

Preliminary evidence for the occurrence of high-Tc superconductivity in alkali-doped organic materials, such as potassium-doped p-terphenyl (KPT), were recently obtained by magnetic susceptibility measurements and by the opening of a large superconducting gap as measured by ARPES and STM techniques. In this work, KPT samples have been synthesized by a chemic

Nguyen Hoang Phuc, Dao T. Khoa, Nguyen Tri Toan Phuc

Elastic $^{16}$O+$^{12}$C scattering is known to exhibit the nuclear rainbow pattern at incident energies $E_\text{lab}\gtrsim 200$ MeV, with the Airy structure of the far-side scattering cross section clearly seen at medium and large angles. Such a rainbow pattern is well described by the deep real optical potential (OP) given by the double-folding model (D

David J. Brady, Timothy J. Schulz, Chengyu Wang

While characterization of coherent wavefields is essential to laser, x-ray and electron imaging, sensors measure the squared magnitude of the field, rather than the field itself. Holography or phase retrieval must be used to characterize the field. The need for a reference severely restricts the utility of holography. Phase retrieval, in contrast, is theoret

Jieli Qin, Lu Zhou

We studied a system of atomic Bose-Einstein condensate coupled to a ring cavity within the mean-field theory. Due to the interaction between atoms and light field, the atoms can be self-trapped. This is verified with both variational and numerical methods. We examined the stability of these self-trapped states. For a weakly pumped cavity, they spread during

Sergei I. Blinnikov, Alexander D. Dolgov

An overview is given of the current status of the theory and observations of the acceleration of the expansion of the observable part of the Universe. Contents 1. Historical Introduction 2. Friedmann equations and cosmological acceleration 3. Vacuum energy problem 4. Data in favor of cosmological acceleration 5.Data on supernovae and baryon acoustic oscillat

Jakub Breier, Adrian Baldwin, Helen Balinsky, Yang Liu

Adversarial attacks for machine learning models have become a highly studied topic both in academia and industry. These attacks, along with traditional security threats, can compromise confidentiality, integrity, and availability of organization's assets that are dependent on the usage of machine learning models. While it is not easy to predict the types

Mayur B. Shende, Prashali Chauhan, Prasad Subramanian

The temporal behaviour of X-rays from some AGN and microquasars is thought to arise from the rapid collapse of the hot, inner parts of their accretion discs. The collapse can occur over the radial infall timescale of the inner accretion disc. However, estimates of this timescale are hindered by a lack of knowledge of the operative viscosity in the collisionl

Karthick Shankar, Pengcheng Wang, Ran Xu, Ashraf Mahgoub

With diverse IoT workloads, placing compute and analytics close to where data is collected is becoming increasingly important. We seek to understand what is the performance and the cost implication of running analytics on IoT data at the various available platforms. These workloads can be compute-light, such as outlier detection on sensor data, or compute-in

Esteban Fernández Morales, Cong Zhang, Guanghua Xiao, Chul Moon

With the advanced imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis. This process produces massive imaging data that capture histological details in high resolution. Recent developments in deep-learning methods have enabled us to automatically detect and characterize the tumor r

Tahsin Sejat Saniat, Tahiat Goni, Shaikat M. Galib

Since the dawn of mankind's introduction to powered flights, there have been multiple incidents which can be attributed to aircraft stalls. Most modern-day aircraft are equipped with advanced warning systems to warn the pilots about a potential stall, so that pilots may adopt the necessary recovery measures. But these warnings often have a short window b

Tianjun Gan, Sharon Xuesong Wang, Johanna K. Teske, Shude Mao

HD 21749 is a bright ($V=8.1$ mag) K dwarf at 16 pc known to host an inner terrestrial planet HD 21749c as well as an outer sub-Neptune HD 21749b, both delivered by TESS. Follow-up spectroscopic observations measured the mass of HD 21749b to be $22.7\pm2.2\ M_{\oplus}$ with a density of $7.0^{+1.6}_{-1.3}$ g~cm$^{-3}$, making it one of the densest sub-Neptun

Taekyun Kim, Dae san Kim

The aim of this paper is to introduce truncated degenerate Bell polynomials and numbers and to investigate some of their properties. In more detail, we obtain explicit expressions, identities involving other special polynomials, integral representations, Dobinski-like formula and expressions of the generating function in terms of differential operators and l

Fang Zeng, Shixu Meng

In this paper we consider the inverse electromagnetic scattering for a cavity surrounded by an inhomogeneous medium in three dimensions. The measurements are scattered wave fields measured on some surface inside the cavity, where such scattered wave fields are due to sources emitted on the same surface. We first prove that the measurements uniquely determine

Pratap Roy, K. Banerjee, T. K. Rana, S. Kundu

The isospin dependence of nuclear level density has been investigated by analyzing the spectra of evaporated neutrons from excited $^{116}$Sn and $^{116}$Te nuclei. These nuclei are populated via $p$ + $^{115}$In and $^{4}$He + $^{112}$Sn reactions in the excitation energy range of 18 - 26 MeV. Because of low excitation energy, the neutron spectra are predom

Jin-woo Lee, Jaehoon Oh, Yooju Shin, Jae-Gil Lee

Federated learning has emerged as a new paradigm of collaborative machine learning; however, it has also faced several challenges such as non-independent and identically distributed(IID) data and high communication cost. To this end, we propose a novel framework of IID and communication-aware group federated learning that simultaneously maximizes both accura

Jer Shyuan Ng, Wei Yang Bryan Lim, Sahil Garg, Zehui Xiong

As the amount of data collected for crowdsensing applications increases rapidly due to improved sensing capabilities and the increasing number of Internet of Things (IoT) devices, the cloud server is no longer able to handle the large-scale datasets individually. Given the improved computational capabilities of the edge devices, coded distributed computing h

Shirsh Lata Soni, Manohar Lal Yadav, Radhe Syam Gupta, Pyare lal Verma

In this paper, we present the multi-wavelength study of a high level of solar activity during which a single active region produced multiple flares/CMEs. According to the sunspot observations, the current solar cycle 24 manifest to be less intense in comparison with the previous recent sunspot cycles. In the course of the current sunspot cycle 24, several sm

Anurag Mohanty, Izabela Janowska

Few layer graphene/carbon (FLG/C) composites are prepared directly via the rapid and simple exfoliation of expanded graphite in the presence of carbon based natural precursors (i.e. protein, polysaccharide) in water, followed by carbonization process. Several parameters such as nature of C-precursor, FLG/C ratio and carbonization conditions (gas, temperature

Zhen Chen, Ren-qian Zhang

This paper investigates a multi-product stochastic inventory problem in which a cash-constrained online retailer can adopt order-based loan provided by some Chinese e-commerce platforms to speed up its cash recovery for deferred revenue. We first build deterministic models for the problem and then develop the corresponding stochastic programming models to ma

George Livadiotis, Maher A. Dayeh, Gary P. Zank

The paper presents a new method for deriving turbulent heating of the solar wind using plasma moments and magnetic field data. We develop the method and then apply it to compute the turbulent heating of the solar wind proton plasma at 1AU. The method employs two physical properties of the expanding solar wind plasma, the wave-particle thermodynamic equilibri

Shaoli Huang, Xinchao Wang, Dacheng Tao

Data mixing augmentation has proved effective in training deep models. Recent methods mix labels mainly based on the mixture proportion of image pixels. As the main discriminative information of a fine-grained image usually resides in subtle regions, methods along this line are prone to heavy label noise in fine-grained recognition. We propose in this paper

Tomoki Ishikura, Akishige Yuguchi, Yuki Kitamura, Sung-Gwi Cho

Affective touch offers positive psychological and physiological benefits such as the mitigation of stress and pain. If a robot could realize human-like affective touch, it would open up new application areas, including supporting care work. In this research, we focused on the gentle stroking motion of a robot to evoke the same emotions that human touch would

Qun Wang, Fuhui Zhou, Rose Qingyang Hu, Yi Qian

Energy-efficient design and secure communications are of crucial importance in wireless communication networks. However, the energy efficiency achieved by using physical layer security can be limited by the channel conditions. In order to tackle this problem, an intelligent reflecting surface (IRS) assisted multiple input single output (MISO) network with in

Medhat Elsayed, Melike Erol-Kantarci, Halim Yanikomeroglu

In this paper, we aim at interference mitigation in 5G millimeter-Wave (mm-Wave) communications by employing beamforming and Non-Orthogonal Multiple Access (NOMA) techniques with the aim of improving network's aggregate rate. Despite the potential capacity gains of mm-Wave and NOMA, many technical challenges might hinder that performance gain. In particu

Chenyang Zhao, Timothy Hospedales

In reinforcement learning, domain randomisation is an increasingly popular technique for learning more general policies that are robust to domain-shifts at deployment. However, naively aggregating information from randomised domains may lead to high variance in gradient estimation and unstable learning process. To address this issue, we present a peer-to-pee

Ali Akhavan-Safaei, Mohsen Zayernouri

In this paper, we present an open-source, automated, and multi-faceted computational-statistical platform to obtain synthetic homogeneous isotropic turbulent flow and passive scalar transport. A parallel implementation of the well-known pseudo-spectral method in addition to the comprehensive record of the statistical and small-scale quantities of the turbule

Fei Ye, Huangjie Zheng, Chaoqin Huang, Ya Zhang

Surrogate task based methods have recently shown great promise for unsupervised image anomaly detection. However, there is no guarantee that the surrogate tasks share the consistent optimization direction with anomaly detection. In this paper, we return to a direct objective function for anomaly detection with information theory, which maximizes the distance

Peng Gao

We study real zeros of a family of quadratic Hecke $L$-functions in the Gaussian field to show that more than twenty percent of the members have no zeros on the interval $(0, 1]$.

Serena Dipierro, Xavier Ros-Oton, Joaquim Serra, Enrico Valdinoci

We study solutions to $Lu=f$ in $Ω\subset\mathbb R^n$, being $L$ the generator of any, possibly non-symmetric, stable Lévy process. On the one hand, we study the regularity of solutions to $Lu=f$ in $Ω$, $u=0$ in $Ω^c$, in $C^{1,α}$ domains~$Ω$. We show that solutions $u$ satisfy $u/d^γ\in C^{\varepsilon_\circ}\big(\overlineΩ\big)$, where $d$ is the distance

Jun Wang, Shaoguo Wen, Kaixing Chen, Jianghua Yu

Active learning generally involves querying the most representative samples for human labeling, which has been widely studied in many fields such as image classification and object detection. However, its potential has not been explored in the more complex instance segmentation task that usually has relatively higher annotation cost. In this paper, we propos

Inkyu Shin, Sanghyun Woo, Fei Pan, InSo Kweon

Recently, deep self-training approaches emerged as a powerful solution to the unsupervised domain adaptation. The self-training scheme involves iterative processing of target data; it generates target pseudo labels and retrains the network. However, since only the confident predictions are taken as pseudo labels, existing self-training approaches inevitably

Jingrun Chen, Shi Jin, Liyao Lyu

Objective functions in large-scale machine-learning and artificial intelligence applications often live in high dimensions with strong non-convexity and massive local minima. First-order methods, such as the stochastic gradient method and Adam, are often used to find global minima. Recently, the consensus-based optimization (CBO) method has been introduced a

William H. Oliver, Pascal J. Elahi, Geraint F. Lewis, Chris Power

We build upon Ordering Points To Identify Clustering Structure (OPTICS), a hierarchical clustering algorithm well-known to be a robust data-miner, in order to produce Halo-OPTICS, an algorithm designed for the automatic detection and extraction of all meaningful clusters between any two arbitrary sizes. We then apply Halo-OPTICS to the 3D spatial positions o

Shixu Meng

We propose a sampling type method to image scatterer in an electromagnetic waveguide. The waveguide terminates at one end and the measurements are on the other end and in the far field. The imaging function is based on integrating the measurements and a known function over the measurement surface directly. The design and analysis of such imaging function are

Haiyun Jiang, Qiaoben Bao, Qiao Cheng, Deqing Yang

Relation extraction aims to identify the target relations of entities in texts. Relation extraction is very important for knowledge base construction and text understanding. Traditional binary relation extraction, including supervised, semi-supervised and distant supervised ones, has been extensively studied and significant results are achieved. In recent ye

Jing Wang, Meng Ji

An edge-colored graph $G$ is conflict-free connected if any two of its vertices are connected by a path, which contains a color used on exactly one of its edges. The conflict-free connection number of a connected graph $G$, denoted by $cfc(G)$, is defined as the minimum number of colors that are required in order to make $G$ conflict-free connected. In this

Adnane Boukhouima, El Mehdi Lotfi, Marouane Mahrouf, Silverio Rosa

We investigate the celebrated mathematical SICA model but using fractional differential equations in order to better describe the dynamics of HIV-AIDS infection. The infection process is modelled by a general functional response and the memory effect is described by the Caputo fractional derivative. Stability and instability of equilibrium points are determi

Feisi He, Weimin Pan, Peng Sha, Jiyuan Zhai

Recently, heat treatment between 250 C and 500 C has been attempted to improve quality factor of superconducting radio-frequency cavities at FNAL and KEK. Experiments of such medium temperature (mid-T) bake with furnaces have also been carried out at IHEP. Firstly, eleven 1.3 GHz 1-cell cavities were treated with different temperatures at a small furnace. Th

Alejandro Cabo-Bizet

By applying the Atiyah-Bott-Berline-Vergne equivariant integration formula upon double dimensional integrals, we find a way to compute the matrix integral representations of $4d$ $\mathcal{N}=1$ superconformal indices. The final formula allows us to easily extract analytic results in the large-rank expansion of certain theories. As an example, we compute the

Yuchao Dong, Qingxin Meng, Qi Zhang

This paper aims to explore the relationship between maximum principle and dynamic programming principle for stochastic recursive control problem with random coefficients. Under certain regular conditions for the coefficients, the relationship between the Hamilton system with random coefficients and stochastic Hamilton-Jacobi-Bellman equation is obtained. It

Narendra Singh, Michael Kroells, Chenxi Li, Eric Ching

A generalized physics-based expression for the drag coefficient of spherical particles moving in a fluid is derived. The proposed correlation incorporates essential rarefied physics, low-speed hydrodynamics, and shock-wave physics to accurately model the particle-drag force for a wide range of Mach and Knudsen numbers (and therefore Reynolds number) a partic

George Stoica, Emmanouil Antonios Platanios, Barnabás Póczos

Relation extraction (RE) aims to predict a relation between a subject and an object in a sentence, while knowledge graph link prediction (KGLP) aims to predict a set of objects, O, given a subject and a relation from a knowledge graph. These two problems are closely related as their respective objectives are intertwined: given a sentence containing a subject

Xingdong Tang, Guixiang Xu

Compared with macroscopic conservation law for the solution of the derivative nonlinear Schrödingger equation (DNLS) with small mass in \cite{KlausS:DNLS}, we show the corresponding microscopic conservation laws for the Schwartz solutions of DNLS with small mass. The new ingredient is to make use of the logarithmic perturbation determinant introduced in \cit

Bahar Taskesen, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen

Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algorithms empower us to harness all information hidden in vast amounts of data, they may inadvertently amplify existing biases in the available datasets. This concern has sparked incr

Mohammad Ghaljehei, Mojdeh Khorsand

New resource mix, e.g., renewable resources, are imposing operational complexities to modern power systems by intensifying uncertainty and variability in the system net load. This issue has motivated independent system operators (ISOs), e.g., California ISO (CAISO), to add the flexible ramping product (FRP) to their day-ahead (DA) market models. Such structu

Petr Plechac

This article points out some surprising similarities between a 1944 study by Georgy Udny Yule and modern approaches to authorship attribution.

Emily Jensen, Bassam Bamieh

In this article, we study the linear time-invariant state-feedback controller design problem for distributed systems. We follow the recently developed system level synthesis (SLS) approach and impose locality structure on the resulting closed-loop mappings; the corresponding controller implementation inherits this prescribed structure. In contrast to existin

Fabio Ansaloni, Heorhii Bohuslavskyi, Federico Fedele, Torbjørn Rasmussen

Silicon quantum devices are maturing from academic single- and two-qubit devices to industrially-fabricated dense quantum-dot (QD) arrays, increasing operational complexity and the need for better pulsed-gate and readout techniques. We perform gate-voltage pulsing and gate-based reflectometry measurements on a dense 2$\times$2 array of silicon quantum dots f

Huai-Yu Wang

A fundamental belief is that the formulism of relativistic quantum mechanics equations (RQMEs) should remain in low momentum motion. However, it is found that some formulas from RQMEs were lost in Schr\"odinger equation. For example, a free relativistic particle has positive and negative energy branches. The former includes positive kinetic energy (PKE) and

Shota Ono, Honoka Satomi

Using first principles calculations, the energetic stability of two-dimensional (2D) binary compounds $XY$ is investigated, where $X$ and $Y$ indicate the metallic element from Li to Pb in the periodic table. Here, 1081 compounds in the buckled honeycomb (BHC), buckled square, B2, L1$_0$, and B$_h$ structures are studied. For the compounds that have negative

Mengwei Si, Zehao Lin, Adam Charnas, Peide D. Ye

In this work, we demonstrate scaled back-end-of-line (BEOL) compatible indium oxide (In2O3) transistors by atomic layer deposition (ALD) with channel thickness (Tch) of 1.0-1.5 nm, channel length (Lch) down to 40 nm, and equivalent oxide thickness (EOT) of 2.1 nm, with record high drain current of 2.0 A/mm at VDS of 0.7 V among all oxide semiconductors. Enha

Christian Esparza Lopez, Jorge Gonzalez-Gutierrez, Francisco Solorio-Ordaz, Eric Lauga

We experimentally and theoretically study the dynamics of a low-Reynolds number helical swimmer moving across viscosity gradients. Experimentally, a double-layer viscosity is generated by superposing two miscible fluids with similar densities but different dynamic viscosities. A synthetic helical magnetically-driven swimmer is then made to move across the vi

Dmitrii V. Semenok, Ivan A. Troyan, Alexander G. Kvashnin, Anna G. Ivanova

Polyhydrides offer intriguing perspectives as high-temperature superconductors. Here we report the high-pressure synthesis of a series of lanthanum-yttrium ternary hydrides: cubic hexahydride $(La,Y)H_{6}$ with a critical temperature $T_{C}$ = 237 +/- 5 K and decahydrides $(La,Y)H_{10}$ with a maximum $T_{C}$ ~${253 K}$ and an extrapolated upper critical mag

Yu Hang Jiang, Tong Liu, Zhiya Lou, Jeffrey S. Rosenthal

We consider MCMC algorithms for certain particle systems which include both attractive and repulsive forces, making their convergence analysis challenging. We prove that a version of these algorithms on a bounded state space is uniformly ergodic with an explicit quantitative convergence rate. We also prove that a version on an unbounded state-space is still

Justin Ball, Stephan Brunner

Local gyrokinetic simulations use a field-aligned domain that twists due to the magnetic shear of the background magnetic equilibrium. However, if the magnetic shear is strong and/or the domain is long, the twist can become so extreme that it fails to properly resolve the turbulence. In this work, we derive and implement the "non-twisting flux tube," a local

Salihah Alwadani, Heinz H. Bauschke, Julian P. Revalski, Xianfu Wang

The geometry conjecture, which was posed nearly a quarter of a century ago, states that the fixed point set of the composition of projectors onto nonempty closed convex sets in Hilbert space is actually equal to the intersection of certain translations of the underlying sets. In this paper, we provide a complete resolution of the geometry conjecture. Our pro

Karla A. Alamo-Martínez, Ana L. Chies-Santos, Michael A. Beasley, Rodrigo Flores-Freitas

We analyse the globular cluster (GC) systems of a sample of 15 massive, compact early-type galaxies (ETGs), 13 of which have already been identified as good relic galaxy candidates on the basis of their compact morphologies, old stellar populations and stellar kinematics. These relic galaxy candidates are likely the nearby counterparts of high redshift red n

Vadim Sushko, Edgar Schönfeld, Dan Zhang, Juergen Gall

Despite their recent successes, GAN models for semantic image synthesis still suffer from poor image quality when trained with only adversarial supervision. Historically, additionally employing the VGG-based perceptual loss has helped to overcome this issue, significantly improving the synthesis quality, but at the same time limiting the progress of GAN mode

Sarthak Dash, Gaetano Rossiello, Nandana Mihindukulasooriya, Sugato Bagchi

Noun phrases and Relation phrases in open knowledge graphs are not canonicalized, leading to an explosion of redundant and ambiguous subject-relation-object triples. Existing approaches to solve this problem take a two-step approach. First, they generate embedding representations for both noun and relation phrases, then a clustering algorithm is used to grou

Taro Matsuo, Satoshi Itoh, Yuji Ikeda

We propose a new approach for high-contrast imaging at the diffraction limit using segmented telescopes in a modest observation bandwidth. This concept, named "spectroscopic fourth-order coronagraphy", is based on a fourth-order coronagraph with a focal-plane mask that modulates the complex amplitude of the Airy disk along one direction. While coronagraphs a

Kai Shu, Yichuan Li, Kaize Ding, Huan Liu

The advanced text generation methods have witnessed great success in text summarization, language translation, and synthetic news generation. However, these techniques can be abused to generate disinformation and fake news. To better understand the potential threats of synthetic news, we develop a new generation method FactGen to generate high-quality news c

Biplav Choudhury, Vijay K. Shah, Avik Dayal, Jeffrey H. Reed

Emerging 802.11p vehicle-to-vehicle (V2V) networks rely on periodic Basic Safety Messages (BSMs) to disseminate time-sensitive safety-critical information, such as vehicle position, speed, and heading -- that enables several safety applications and has the potential to improve on-road safety. Due to mobility, lack of global-knowledge and limited communicatio

Mohammadreza Kavianipour, Hamid Mozafari, Mehrnaz Ghamami, Ali Zockaie

Electric vehicles (EVs) are considered as sustainable alternatives to conventional vehicles, as they reduce emission and fossil fuel dependency. A recent study has proposed a charging infrastructure planning tool to support intercity trips for the estimated EV market share (6 percent) in Michigan for 2030. The main goal of this study is to estimate the emiss

Yaniv Eliezer, Geyang Qu, Wenhong Yang, Yujie Wang

A metasurface hologram combines fine spatial resolution and large viewing angles with a planar form factor and compact size. However, it suffers coherent artifacts originating from electromagnetic cross-talk between closely packed meta-atoms and fabrication defects of nanoscale features. Here, we introduce an efficient method to remove all artifacts by fine-

Clement Moreau, Thomas Devogele, Laurent Etienne, Veronika Peralta

Various institutes produce large semantic datasets containing information regarding daily activities and human mobility. The analysis and understanding of such data are crucial for urban planning, socio-psychology, political sciences, and epidemiology. However, none of the typical data mining processes have been customized for the thorough analysis of semant

Mohammad Havaei, Ximeng Mao, Yiping Wang, Qicheng Lao

Synthetic medical image generation has a huge potential for improving healthcare through many applications, from data augmentation for training machine learning systems to preserving patient privacy. Conditional Adversarial Generative Networks (cGANs) use a conditioning factor to generate images and have shown great success in recent years. Intuitively, the