July 2022 arXiv papers — page 5

Eleanor D'Arcy, Jonathan A. Tawn

Extreme sea level estimates are fundamental for mitigating against coastal flooding as they provide insight for defence engineering. As the global climate changes, rising sea levels combined with increases in storm intensity and frequency pose an increasing risk to coastline communities. We present a new method for estimating extreme sea levels that accounts

Omar Mustafa

We argue that only exact, comprehensive, and explicit solutions for the fundamental models, the Klein-Gordon (KG) oscillators and the KG-Coulomb, would help to understand the effects of gravitational fields on the dynamics of such quantum mechanical systems. In the current methodical proposal, the effects of the gravitational fields generated by a G\"odel-ty

Yuichiro Onishi, Yoshio Teki, Eiji Shikoh

We report the spin transport properties in a thin film of a naphthyl diamine derivative: N,N'-Bis(naphthalen-1-yl)-N,N'-bis(phenyl)-2,2'-dimethylbenzidine (alpha-NPD). In a palladium(Pd)/alpha-NPD/Ni80Fe20 tri-layer structure sample, a pure spin current is generated in the alpha-NPD layer with the spin pumping driven by ferromagnetic resonance (FMR). The gen

Przemysław Korzeniowski, Szymon Płotka, Robert Brawura-Biskupski-Samaha, Arkadiusz Sitek

Spina Bifida (SB) is a birth defect developed during the early stage of pregnancy in which there is incomplete closing of the spine around the spinal cord. The growing interest in fetoscopic Spina-Bifida repair, which is performed in fetuses who are still in the pregnant uterus, prompts the need for appropriate training. The learning curve for such procedure

Lars Hesselholt

The purpose of this expository paper is to explain how the Fargues-Fontaine curve and its decomposition into a punctured curve and the formal neighborhood of the puncture naturally arise from various forms of topological cyclic homology and maps between them.

Meng-Jun Hu, Haixing Miao, Yong-Sheng Zhang

The historical significance of the Stern-Gerlach experiment lies in its provision of the initial evidence for space quantization. Over time, its sequential form has evolved into an elegant paradigm that effectively illustrates the fundamental principles of quantum theory. To date, the practical implementation of the sequential Stern-Gerlach experiment has no

Takahiro Murashima, Katsumi Hagita, Toshihiro Kawakatsu

Blends of multicyclic and linear polymers under biaxial elongational flow were analyzed using coarse-grained molecular dynamics simulations. The multicyclic/linear blends displayed overshoot in the normal stress difference at the start-up of biaxial elongational flow. This overshoot was steeper for multicyclic/linear blends than for our previously reported m

Arash Rabbani, Hao Gao, Dirk Husmeier

In this study, we have tailored a pixel tracking method for temporal extrapolation of the ventricular segmentation masks in cardiac magnetic resonance images. The pixel tracking process starts from the end-diastolic frame of the heart cycle using the available manually segmented images to predict the end-systolic segmentation mask. The superpixels approach i

Jinglei Shi, Christine Guillemot

We propose in this paper a Quantized Distilled Low-Rank Neural Radiance Field (QDLR-NeRF) representation for the task of light field compression. While existing compression methods encode the set of light field sub-aperture images, our proposed method learns an implicit scene representation in the form of a Neural Radiance Field (NeRF), which also enables vi

Arash Rabbani, Masoud Babaei

In this study, a method has been developed to improve the resolution of histological human placenta images. For this purpose, a paired series of high- and low-resolution images have been collected to train a deep neural network model that can predict image residuals required to improve the resolution of the input images. A modified version of the U-net neura

Debajyoti Bera, Tharrmashastha Sapv

Amplitude filtering is concerned with identifying basis-states in a superposition whose amplitudes are greater than a specified threshold; probability filtering is defined analogously for probabilities. Given the scarcity of qubits, the focus of this work is to design log-space algorithms for them. Both algorithms follow a similar pattern of estimating the a

Jasleen Kaur, Aritra Ghosh, Malay Bandyopadhyay

In this paper, we analyze dissipative diamagnetism, arising due to dissipative cyclotron motion in two dimensions, in the light of the quantum counterpart of energy equipartition theorem. We consider a charged quantum particle moving in a harmonic well, in the presence of a uniform magnetic field, and coupled to a quantum heat bath which is taken to be compo

Shao-Yuan Lo, Wei Wang, Jim Thomas, Jingjing Zheng

Monocular depth estimation (MDE) has attracted intense study due to its low cost and critical functions for robotic tasks such as localization, mapping and obstacle detection. Supervised approaches have led to great success with the advance of deep learning, but they rely on large quantities of ground-truth depth annotations that are expensive to acquire. Un

Sagi Ben-Ami, Yossi Shvartzvald, Eli Waxman, Udi Netzer

The Ultraviolet Transient Astronomy Satellite (ULTRASAT) is a space-borne near UV telescope with an unprecedented large field of view (200 sq. deg.). The mission, led by the Weizmann Institute of Science and the Israel Space Agency in collaboration with DESY (Helmholtz association, Germany) and NASA (USA), is fully funded and expected to be launched to a geo

Ricardo Gallego Torromé

It has been discussed recently how quantum illumination can be used to increase the accuracy of the value range-delay measurement \cite{Zhuang Shapiro 2022} in the domain of SNR compatible with current radar systems. However, the advantage described in [1] requires of a large integration time. In this work it is argued that multiple entangled photon quantum

Narjes Taghadomi, Azam Mani, Ali Bakouei

We investigate the behavior of quantum coherence of the ground states of 2D Heisenberg XY model and 2D Ising model with transverse field on square lattices, by using the method of Quantum Renormalization Group (QRG). We show that the non-analytic behavior of quantum coherence near the critical point, can detect quantum phase transition (QPT) of these models.

Elvira Mayordomo

Effective dimension has proven very useful in geometric measure theory through the point-to-set principle \cite{LuLu18}\ that characterizes Hausdorff dimension by relativized effective dimension. Finite-state dimension is the least demanding effectivization in this context \cite{FSD}\ that among other results can be used to characterize Borel normality \cite

Paweł Wawrzyński, Wojciech Masarczyk, Mateusz Ostaszewski

Effective reinforcement learning requires a proper balance of exploration and exploitation defined by the dispersion of action distribution. However, this balance depends on the task, the current stage of the learning process, and the current environment state. Existing methods that designate the action distribution dispersion require problem-dependent hyper

Jing Jing, Ze-Fang Jiang, C. B. Yang, Ben-Wei Zhang

Using a (3+1)-D hydrodynamic model CLVisc, we study the directed flow ($v_{1}$) of light hadrons produced in Au+Au, Ru+Ru and Zr+Zr collisions at $\sqrt{s_{\textrm{NN}}}=$ 200 GeV. The evolution of tilted energy density, pressure gradient and radial flow along the $x$-direction are systematically investigated. Counter-clockwise tilt of initial fireball is sh

Alberto De Sole, Victor G. Kac, Daniele Valeri

The theory of triples of Poisson brackets and related integrable systems, based on a classical R-matrix R in End_F(g), where g is a finite dimensional associative algebra over a field F viewed as a Lie algebra, was developed by Oevel-Ragnisco and Li-Parmentier [OR89,LP89]. In the present paper we develop an "affine" analogue of this theory by introducing the

Rana D. Parshad, Sureni Wickramsooriya, Kwadwo Antwi-Fordjour, Aniket Banerjee

The literature posits that an introduced predator population, is able to drive it's target pest population extinct, if supplemented with high quality additional food of quantity $\xi > \xi_{critical}$, \cite{SP11, SPV18, SPD17, SPM13}. We show this approach leads to infinite time blow-up of the predator population. We propose an alternate model in which the

Vahid Shirbisheh

We propose a local-to-global strategy for graph machine learning and network analysis by defining certain local features and vector representations of nodes and then using them to learn globally defined metrics and properties of the nodes by means of deep neural networks. By extending the notion of the degree of a node via Breath-First Search, a general fami

Wei Liu, Jingzhi Yan, Pablo Reig, Xiaofeng Wang

We have obtained optical spectroscopy and photometry data during four years after the event. The long-term photometric light-curve and the equivalent widths of the Halpha and He I 6678 lines were used to monitor the state of the Be star disk. The Halpha line profiles show evidence for V/R variability that was accounted for by fitting the Halpha spectral line

Xinpeng Ding, Jingweng Yang, Xiaowei Hu, Xiaomeng Li

Video shadow detection aims to generate consistent shadow predictions among video frames. However, the current approaches suffer from inconsistent shadow predictions across frames, especially when the illumination and background textures change in a video. We make an observation that the inconsistent predictions are caused by the shadow feature inconsistency

Shahul Hameed K, Albin Mathew, Germina K A, Thomas Zaslavsky

A signed graph is a graph with edges marked positive and negative; it is unbalanced if some cycle has negative sign product. We introduce the concept of vector valued switching function in signed graphs, which extends the concept of switching to higher dimensions. Using this concept, we define balancing dimension and strong balancing dimension for a signed g

Fabio A. C. C. Chalub

The Kimura equation is a degenerated partial differential equation of drift-diffusion type used in population genetics. Its solution is required to satisfy not only the equation but a series of conservation laws formulated as integral constraints. In this work, we consider a population of two types evolving without mutation or selection, the so-called neutra

Can Peng, Kun Zhao, Tianren Wang, Meng Li

The continual appearance of new objects in the visual world poses considerable challenges for current deep learning methods in real-world deployments. The challenge of new task learning is often exacerbated by the scarcity of data for the new categories due to rarity or cost. Here we explore the important task of Few-Shot Class-Incremental Learning (FSCIL) a

Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli

Decentralized control systems are widely used in a number of situations and applications. In order for these systems to function properly and achieve their desired goals, information must be propagated between agents, which requires connecting to a network. To reduce opportunities for attacks that may be carried out through the network, we design an event-tr

Moritz Hütten, Daniel Kerszberg

High-energetic gamma rays from astrophysical targets constitute a unique probe for annihilation or decay of heavy particle dark matter (DM). After several decades, diverse null detections have resulted in strong constraints for DM particle masses up to the TeV scale. While the gamma-ray signature is expected to be universal from various targets, uncertaintie

Chen Ye Gan

Popular methods for modeling data both labelled and unlabeled, multiple regression and PCA has been used in research for a vast number of datasets. In this investigation, we attempt to push the limits of these two methods by running a fit on world development data, a set notorious for its complexity and high dimensionality. We assess the robustness and numer

Lucas H. R. de Souza

If a Hausdorff locally compact paracompact space has a coarse structure, then there is a family of well behaved compactifications associated to it. If there are two of these spaces, $X$ and $Y$, with a good coarse equivalence, then there is a correspondence between these families of compactifications of $X$ and $Y$. On the other hand, if a group $G$ has a pr

P. A. Azeef Muhammed, C. S. Preenu

An inverse Clifford semigroup (often referred to as just a Clifford semigroup) is a semilattice of groups. It is an inverse semigroup and in fact, one of the earliest studied classes of semigroups. In this short note, we discuss various structural aspects of a Clifford semigroup from a cross-connection perspective. In particular, given a Clifford semigroup,

Lijing Shao

Searches for empirical clues beyond Einstein's general relativity (GR) are crucial to understand gravitation and spacetime. Radio pulsars have been playing an important role in testing gravity theories since 1970s. Because radio timing of binary pulsars is very sensitive to changes in the orbital dynamics, small deviations from what GR predicts can be captur

Feihong Yang, Yuan Shen

Intersection management with mixed cooperative and non-cooperative vehicles is crucial in next-generation transportation systems. For fully non-cooperative systems, a minimax scheduling framework was established, while it is inefficient in mixed systems as the benefit of cooperation is not exploited. This letter focuses on the efficient scheduling in mixed s

Indranil Biswas, Anoop Singh

We explore algebro-geometric properties of the moduli space of holomorphic Lie algebroid ($ \mathcal{L} $) connections on a compact Riemann surface $X$ of genus $g \,\geq\, 3$. A smooth compactification of the moduli space of $\mathcal{L}$-connections, such that underlying vector bundle is stable, is constructed; the complement of the moduli space inside the

Xiaoqian Wang, Yanfei Kang, Feng Li

Forecast combination is widely recognized as a preferred strategy over forecast selection due to its ability to mitigate the uncertainty associated with identifying a single "best" forecast. Nonetheless, sophisticated combinations are often empirically dominated by simple averaging, which is commonly attributed to the weight estimation error. The issue becom

Yu Han

The Hamiltonian constraint of scalar-tensor theories in the Jordan frame is quantised using three quantisation prescriptions in loop quantum cosmology, from which we obtain three different effective Hamiltonian constraints. The corresponding effective equations of motion derived from these effective Hamiltonian constraints turn out to be drastically differen

Haoran Zhang, Junhui Wang

This paper proposes a novel signed $\beta$-model for directed signed network, which is frequently encountered in application domains but largely neglected in literature. The proposed signed $\beta$-model decomposes a directed signed network as the difference of two unsigned networks and embeds each node with two latent factors for in-status and out-status. T

João Barata

The fast development of quantum technologies over the last decades has offered a glimpse to a future where the quantum properties of multi-particle systems might be more fully understood. In particular, quantum computing might prove crucial to explore many aspects of high energy physics unaccessible to classical methods. In this talk, we will describe how on

Wei Li, Zhiwen Li, Yiqi Liu, Yongping Pan

Online Gaussian processes (GPs), typically used for learning models from time-series data, are more flexible and robust than offline GPs. Both local and sparse approximations of GPs can efficiently learn complex models online. Yet, these approaches assume that all signals are relatively accurate and that all data are available for learning without misleading

Moonzarin Reza, Yuanyuan Zhang, Brian Nord, Jason Poh

Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from a simplified galaxy cluster observation analysis. Using data generated from the Quijote simulation suite

Bukyoung Jhun, Hoyun Choi, Yongsun Lee, Jongshin Lee

Cascading failures (CFs) in electrical power grids propagate nonlocally; After a local disturbance, the second failure may be distant. To study the avalanche dynamics and mitigation strategy of nonlocal CFs, numerical simulation is necessary; however, computational complexity is high. Here, we first propose an avalanche centrality (AC) of each node, a measur

Yoshinobu Fudamoto, Akio K. Inoue, Yuma Sugahara

In the first image of the James Webb Space Telescope (JWST) of SMACS J0723.3-7327, one of the most outstanding features is the emergence of a large number of red spiral galaxies, because such red spiral galaxies are only a few percent in the number fraction among nearby spiral galaxies. While these apparently red galaxies were already detected with the Spitz

Ritwik Mondal, Levente Rózsa

Inertial effects in spin dynamics are theoretically predicted to emerge at ultrashort time scales, but their experimental signatures are often ambiguous. Here, we calculate the spin-wave spectrum in ferromagnets and two-sublattice antiferromagnets in the presence of inertial effects. It is shown how precession and nutation spin waves hybridize with each othe

Marco Ripà

We solve a few open problems related to a peculiar property of the integer tetration ${^{b}a}$, which is the constancy of its congruence speed for any sufficiently large $b=b(a)$. Assuming radix-$10$ (the well-known decimal numeral system), we provide an explicit formula for the congruence speed $V(a) \in \mathbb{N}_0$ of any $a \in \mathbb{N}-\{0\}$ that is

Lê Vǎn Thành

This paper develops Rio's method [C. R. Acad. Sci. Paris S\'{e}r. I Math., 1995] to prove the weak law of large numbers for maximal partial sums of pairwise independent random variables. The method allows us to avoid using the Kolmogorov maximal inequality. As an application, a weak law of large numbers for maximal partial sums of pairwise independent random

Gerardo Urrutia, Fabio De Colle, Claudia Moreno, Michele Zanolin

Gamma-ray bursts (GRBs) are produced during the propagation of ultra-relativistic jets. It is challenging to study the jet close to the central source, due to the high opacity of the medium. In this paper, we present numerical simulations of relativistic jets propagating through a massive, stripped envelope star associated to long GRBs, breaking out of the s

Zhongtian Hu, Lifang Wang, Yangqi Chen, Yushuang Liu

Knowledge-driven dialog system has recently made remarkable breakthroughs. Compared with general dialog systems, superior knowledge-driven dialog systems can generate more informative and knowledgeable responses with pre-provided knowledge. However, in practical applications, the dialog system cannot be provided with corresponding knowledge in advance becaus

Sajjan Sheoran, Deepika Gill, Ankita Phutela, Saswata Bhattacharya

The new two-dimensional materials, MoSi$_2$N$_4$ and WSi$_2$N$_4$ are experimentally synthesized successfully and various similar structures are predicted theoretically. Here, we report the electronic properties with a special focus on the band splitting in WA$_2$Z$_4$ (A=Si, Ge; Z=N, P, As), using state-of-the-art density functional theory and many-body per

Sébastien Alvarez, Martin Leguil, Davi Obata, Bruno Santiago

We show that within a $C^1$-neighbourhood $\mathcal{U}$ of the set of volume preserving Anosov diffeomorphisms on the three-torus $\mathbb{T}^3$ which are strongly partially hyperbolic with expanding center, any $f\in\mathcal{U}\cap\operatorname{Diff}^2(\mathbb{T}^3)$ satisfies the dichotomy: either the strong stable and unstable bundles $E^s$ and $E^u$ of $

Wei Gao, Qiuping Jiang, Ronggang Wang, Siwei Ma

Consistent quality oriented rate control in video coding has attracted much more attention. However, the existing efforts only focus on decreasing variations between every two adjacent frames, but neglect coding trade-off problem between intra and inter frames. In this paper, we deal with it from a new perspective, where intra frame quantization parameter (I

Yang Li, Shifeng Xiong

Computer simulation models are widely used to study complex physical systems. A related fundamental topic is the inverse problem, also called calibration, which aims at learning about the values of parameters in the model based on observations. In most real applications, the parameters have specific physical meanings, and we call them physical parameters. To

Yuanan Diao

A long standing conjecture states that the ropelength of any alternating knot is at least proportional to its crossing number. In this paper we prove that this conjecture is true. That is, there exists a constant $b_0>0$ such that $R(K)\ge b_0Cr(K)$ for any alternating knot $K$, where $R(K)$ is the ropelength of $K$ and $Cr(K)$ is the crossing number of $K$.

Mitali Bafna, Jun-Ting Hsieh, Pravesh K. Kothari, Jeff Xu

We give efficient algorithms for finding power-sum decomposition of an input polynomial $P(x)= \sum_{i\leq m} p_i(x)^d$ with component $p_i$s. The case of linear $p_i$s is equivalent to the well-studied tensor decomposition problem while the quadratic case occurs naturally in studying identifiability of non-spherical Gaussian mixtures from low-order moments.

Pavel Galashin, Thomas Lam, Minh-Tâm Quang Trinh, Nathan Williams

We solve two open problems in Coxeter-Catalan combinatorics. First, we introduce a family of rational noncrossing objects for any finite Coxeter group, using the combinatorics of distinguished subwords. Second, we give a type-uniform proof that these noncrossing Catalan objects are counted by the rational Coxeter-Catalan number, using the character theory of

Chris Kiehl, Daniel Wagner, Ting-Wei Hsu, Svenja Knappe

Rabi measurements in atomic vapor cells are of current interest in a range of microwave imaging and sensing experiments, but are increasingly in a parameter space outside of theoretical studies of coherence defined by spin-exchange collisions. Here, we study the coherence of Rabi oscillations in vapor cells by employing continuous non-destructive readout of

Lizhao Liu, Shangxin Huang, Zhuangwei Zhuang, Ran Yang

Deep Metric Learning (DML) serves to learn an embedding function to project semantically similar data into nearby embedding space and plays a vital role in many applications, such as image retrieval and face recognition. However, the performance of DML methods often highly depends on sampling methods to choose effective data from the embedding space in the t

Yitian Wang, Jun Lin, Liu Zhang, Tianhao Wang

Existing intelligent driving technology often has a problem in balancing smooth driving and fast obstacle avoidance, especially when the vehicle is in a non-structural environment, and is prone to instability in emergency situations. Therefore, this study proposed an autonomous obstacle avoidance control strategy that can effectively guarantee vehicle stabil

Tom Bohman, Jakob Hofstad

We show that the independence number of $ G_{n,p}$ is concentrated on two values if $ n^{-2/3+ \epsilon} < p \le 1$. This result is roughly best possible as an argument of Sah and Sawhney shows that the independence number is not, in general, concentrated on 2 values for $ p = o \left( (\log(n)/n)^{2/3} \right)$. The extent of concentration of the independen

Donghao Qiao, Farhana Zulkernine

Cooperative perception allows a Connected Autonomous Vehicle (CAV) to interact with the other CAVs in the vicinity to enhance perception of surrounding objects to increase safety and reliability. It can compensate for the limitations of the conventional vehicular perception such as blind spots, low resolution, and weather effects. An effective feature fusion

Bin-Bin Liu, Xu-Tao Zeng, Cong Chen, Ziyu Chen

The study of higher-order and real topological states as well as the material realization have become a research forefront of topological condensed matter physics in recent years. Twisted bilayer graphene (tbG) is proved to have higher-order and real topology. However whether this conclusion can be extended to other two-dimensional twisted bilayer carbon mat

Youfei Yu, Jiacong Du, Min Zhang, Zhenke Wu

Propensity scores are commonly used to reduce the confounding bias in non-randomized observational studies for estimating the average treatment effect. An important assumption underlying this approach is that all confounders that are associated with both the treatment and the outcome of interest are measured and included in the propensity score model. In the

Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang

We propose a method for estimating the 6DoF pose of a rigid object with an available 3D model from a single RGB image. Unlike classical correspondence-based methods which predict 3D object coordinates at pixels of the input image, the proposed method predicts 3D object coordinates at 3D query points sampled in the camera frustum. The move from pixels to 3D p

Hengyuan Wei, Zhenghua Huang, Hui Fu, Ming Xiong

Jets are one of the most common eruptive events in the solar atmosphere, and they are believed to be important in the context of coronal heating and solar wind acceleration. We present an observational study on a sequence of jets with the data acquired with the Solar Dynamics Observatory (SDO) and the Interface Region Imaging Spectrograph (IRIS). This sequen

Santo Fortunato, M. E. J. Newman

A fundamental technical challenge in the analysis of network data is the automated discovery of communities - groups of nodes that are strongly connected or that share similar features or roles. In this commentary we review progress in the field over the last 20 years.

Haram Park, Carlos Kayembe Nkuba, Seunghoon Woo, Heejo Lee

Bluetooth Basic Rate/Enhanced Data Rate (BR/EDR) is a wireless technology used in billions of devices. Recently, several Bluetooth fuzzing studies have been conducted to detect vulnerabilities in Bluetooth devices, but they fall short of effectively generating malformed packets. In this paper, we propose L2FUZZ, a stateful fuzzer to detect vulnerabilities in

Bhupesh Bishnoi

We have presented a consistent electronic transport framework for the two-dimensional extended Holstein's organic molecular-crystal based upon complete quantum-mechanical treatment through the non-equilibrium Green's function (NEGF) formalism and corresponding one-to-one semi-classical framework based upon Boltzmann transport theory for the narrow-bandwidth

Sayef Azad Sakin, Alex Bigelow, R. Tohid, Connor Scully-Allison

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace

Fanyou Wu, Yang Liu, Rado Gazo, Benes Bedrich

In the Amazon KDD Cup 2022, we aim to apply natural language processing methods to improve the quality of search results that can significantly enhance user experience and engagement with search engines for e-commerce. We discuss our practical solution for this competition, ranking 6th in task one, 2nd in task two, and 2nd in task 3. The code is available at

Rafael Alves Batista, Julia Becker Tjus, Julien Dörner, Andrej Dundovic

The landscape of high- and ultra-high-energy astrophysics has changed in the last decade, largely due to the inflow of data collected by large-scale cosmic-ray, gamma-ray, and neutrino observatories. At the dawn of the multimessenger era, the interpretation of these observations within a consistent framework is important to elucidate the open questions in th

Charlie Hoy

Gravitational wave models are used to infer the properties of black holes in merging binaries from the observed gravitational wave signals through Bayesian inference. Although we have access to a large collection of signal models that are sufficiently accurate to infer the properties of black holes, for some signals, small discrepancies in the models lead to

Raluca Cobzaru, Roy Welsch, Stan Finkelstein, Kenney Ng

Causal inference from observational data often rests on the unverifiable assumption of no unmeasured confounding. Recently, Tchetgen Tchetgen and colleagues have introduced proximal inference to leverage negative control outcomes and exposures as proxies to adjust for bias from unmeasured confounding. However, some of the key assumptions that proximal infere

Yoshiko Kanada-En'yo

The isotopic systematics of Sn isotopes in the range A=116--124 were investigated by combining the nuclear structure and reaction calculations for the analysis of Sn(p,p) reactions at 295 MeV. The Sn(p,p) reactions were calculated employing relativistic impulse approximation (RIA) with theoretical densities obtained for the Sn isotopes from relativistic Hart

Stephen Sorokanich

We prove existence results for a system of partial differential equations describing the approximate condensate wavefunction and pair-excitation kernel of a dilute (T=0) Bose gas in the stationary setting, in the presence of a trapping potential and repulsive pairwise atomic interactions. Notably, the Hartree-type equation for the condensate in this system c

Ayush Kumar, Ashish Kumar, Aakanksha Prasad, Michael Burch

This paper proposes an open source visual analytics tool consisting of several views and perspectives on eye movement data collected during code reading tasks when writing computer programs. Hence the focus of this work is on code and program comprehension. The source code is shown as a visual stimulus. It can be inspected in combination with overlaid scanpa

Yu. A. Nagovitsyn, V. G. Ivanov

In addition to the Gnevyshev-Ohl rule (GOR), the relation of the odd cycle with the subsequent even one in the 22-year Hale solar cycle was found. It is shown that 3 years before the 11-year minimum $m$, the value of the relative sunspot number SN in an odd cycle is closely related to the value of the maximum in the next even cycle (correlation coefficient $

F. Carotenuto, S. Corbel, A. Tzioumis

The properties of the disk/jet coupling in quiescent black hole low mass X-ray binaries (BH LMXBs) are still largely unknown. In this paper we present the first quasi-simultaneous radio and X-ray detection in quiescence of the BH LMXB MAXI J1348$-$630, which is known to display a hybrid disk/jet connection that depends on the accretion rate. We performed dee

M. Ablikim, M. N. Achasov, P. Adlarson, M. Albrecht

Using data samples collected with the BESIII detector operating at the BEPCII storage ring, we measure the cross sections of the $e^{+}e^{-}\rightarrow\pi^{+}\pi^{-}D^{+}D^{-}$ process at center-of-mass energies from 4.190 to 4.946 GeV with a partial reconstruction method. Two resonance structures are seen and the resonance parameters are determined from a f

Nazanin Moradinasab, Yash Sharma, Laura S. Shankman, Gary K. Owens

Two major causes of death in the United States and worldwide are stroke and myocardial infarction. The underlying cause of both is thrombi released from ruptured or eroded unstable atherosclerotic plaques that occlude vessels in the heart (myocardial infarction) or the brain (stroke). Clinical studies show that plaque composition plays a more important role

B. G. Palm, F. M. Bayer, R. Machado, M. I. Pettersson

The presence of outliers (anomalous values) in synthetic aperture radar (SAR) data and the misspecification in statistical image models may result in inaccurate inferences. To avoid such issues, the Rayleigh regression model based on a robust estimation process is proposed as a more realistic approach to model this type of data. This paper aims at obtaining

Majd Hawasly, Jonathan Sadeghi, Morris Antonello, Stefano V. Albrecht

Achieving safe and robust autonomy is the key bottleneck on the path towards broader adoption of autonomous vehicles technology. This motivates going beyond extrinsic metrics such as miles between disengagement, and calls for approaches that embody safety by design. In this paper, we address some aspects of this challenge, with emphasis on issues of motion p

B. G. Palm, F. M. Bayer, R. J. Cintra

This paper proposes the beta binomial autoregressive moving average model (BBARMA) for modeling quantized amplitude data and bounded count data. The BBARMA model estimates the conditional mean of a beta binomial distributed variable observed over the time by a dynamic structure including: (i) autoregressive and moving average terms; (ii) a set of regressors;

Yulong Cao, Danfei Xu, Xinshuo Weng, Zhuoqing Mao

Trajectory prediction using deep neural networks (DNNs) is an essential component of autonomous driving (AD) systems. However, these methods are vulnerable to adversarial attacks, leading to serious consequences such as collisions. In this work, we identify two key ingredients to defend trajectory prediction models against adversarial attacks including (1) d

Giorgos Anastasiou, Ignacio J. Araya, Andrés Argandoña, Rodrigo Olea

We find a covariant expression for the universal part of the holographic entanglement entropy which is valid for CFTs dual to generic higher curvature gravities in up to five bulk dimensions. We use this functional to compute universal coefficients of stress-tensor correlators in three-dimensional CFTs dual to Cubic Curvature Gravity. Using gauge/gravity dua

Amir Siraj, Abraham Loeb, Tim Gallaudet

The earliest confirmed interstellar object, `Oumuamua, was discovered in the Solar System by Pan-STARRS in 2017, allowing for a calibration of the abundance of interstellar objects of its size $\sim 100\;$ m. This was followed by the discovery of Borisov, which allowed for a similar calibration of its size $\sim 0.4 - 1 \mathrm{\; km}$. One would expect a mu

Shashikant Kumar, Phanish Suryanarayana

We study the bending of rectangular atomic monolayers along different directions from first principles. Specifically, choosing the phosphorene, GeS, TiS$_3$, and As$_2$S$_3$ monolayers as representative examples, we perform Kohn-Sham density functional theory calculations to determine the variation in transverse flexoelectric coefficient and bending modulus

Qihao Liu, Yi Zhang, Song Bai, Alan Yuille

Occlusion poses a great threat to monocular multi-person 3D human pose estimation due to large variability in terms of the shape, appearance, and position of occluders. While existing methods try to handle occlusion with pose priors/constraints, data augmentation, or implicit reasoning, they still fail to generalize to unseen poses or occlusion cases and may

Deborah Rönchen, Michael Döring, Ulf-G. Meißner, Chao-Wei Shen

The J\"ulich-Bonn dynamical coupled-channel approach is extended to include $K\Sigma$ photoproduction off the proton. Differential cross section and (double) polarization data for $K^+\Sigma^0$ and $K^0\Sigma^+$ are analysed simultaneously with the pion- and photon-induced production of $\pi N$, $\eta N$, $K\Lambda$, and $K\Sigma$ final states, totaling more

Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt

We consider online imitation learning (OIL), where the task is to find a policy that imitates the behavior of an expert via active interaction with the environment. We aim to bridge the gap between the theory and practice of policy optimization algorithms for OIL by analyzing one of the most popular OIL algorithms, DAGGER. Specifically, if the class of polic

R. J. Cintra, S. Duffner, C. Garcia, A. Leite

In this paper, we present an approach for minimizing the computational complexity of trained Convolutional Neural Networks (ConvNet). The idea is to approximate all elements of a given ConvNet and replace the original convolutional filters and parameters (pooling and bias coefficients; and activation function) with efficient approximations capable of extreme

Sahar Allahkaram, Francisco A. Monteiro, Ioannis Chatzigeorgiou

A present challenge in wireless communications is the assurance of ultra-reliable and low-latency communication (URLLC). While the reliability aspect is well known to be improved by channel coding with long codewords, this usually implies using interleavers, which introduce undesirable delay. Using short codewords is a needed change to minimizing the decodin

Simon Bilik, Tomas Zemcik, Lukas Kratochvila, Dominik Ricanek

Wide use and availability of the machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditional industrial domain, new application appears also in biology and agriculture, where we could speak about the detection of infections, parasites and weeds, but also about automated

N. Bárcenas, J. Torres Orozco

It is known that there exist singular Poisson structures in $4$-manifolds, whose symplectic foliation is given by singular fibrations over surfaces. In this work, we describe the effect of the monodromy of the fibration on the Poisson cohomology groups.

Javier Renedo, Luis Rouco, Aurelio Garcia-Cerrada, Lukas Sigrist

Multi-terminal high-voltage Direct Current technology based on Voltage-Source Converter stations (VSC-MTDC) is expected to be one of the most important contributors to the future of electric power systems. In fact, among other features, it has already been shown how this technology can contribute to improve transient stability in power systems by the use of

Marco Cirant

We show in this paper that maximal $L^q$-regularity for time-dependent viscous Hamilton-Jacobi equations with unbounded right-hand side and superquadratic $\gamma$-growth in the gradient holds in the full range $ q > (N+2)\frac{\gamma-1}\gamma$. Our approach is based on new $\frac{\gamma-2}{\gamma-1}$-H\"older estimates, which are consequence of the decay at

Tao Li, Haozhe Lei, Quanyan Zhu

Meta reinforcement learning (meta RL), as a combination of meta-learning ideas and reinforcement learning (RL), enables the agent to adapt to different tasks using a few samples. However, this sampling-based adaptation also makes meta RL vulnerable to adversarial attacks. By manipulating the reward feedback from sampling processes in meta RL, an attacker can

Massimo Ladisa, Pietro Santorelli

We investigate rare semileptonic $B \to K^\ast\ell^+\ell^-$ by looking at the long distance contributions. Our analysis is limited to the very small values of physical accessible range of invariant mass of the leptonic couple $q^2$. We show that the light quarks loop has to be accounted for, along with the charming penguin contribution, in order to accuratel

Qixin Yu, Dieter Horns

High energy gamma-rays propagating in external magnetic fields may convert into axion-like particles (ALPs). In this case, the observed gamma-ray spectra are modified by the resulting energy-dependent conversion probability. In this study, we use the energy spectra of 20 extra-galactic gamma-ray sources recorded during 10 years of \textit{Fermi}-LAT observat

Ghaith Hiary, Megan Paasche

An interesting episode in the history of the prime number theorem concerns a formula proposed by Legendre for counting the primes below a given bound. We point out that arithmetic bias likely played an important role in arriving at that formula and in its subsequent widespread, decades-long recognition. We also show that the Legendre constant 1.08366 satisfi

Jaehyeok Jin, Kenneth S. Schweizer, Gregory A. Voth

Coarse-grained (CG) models facilitate an efficient exploration of complex systems by reducing the unnecessary degrees of freedom of the fine-grained (FG) system while recapitulating major structural correlations. Unlike structural properties, assessing dynamic properties in CG modeling is often unfeasible due to the accelerated dynamics of the CG models, whi