arXiv papers from March 2022

Denis González-Caniulef, Ilaria Caiazzo, Jeremy Heyl

We present a systematic study of the unbinned, photon-by-photon likelihood technique which can be used as an alternative method to analyse phase-dependent, X-ray spectro-polarimetric observations obtained with IXPE and other photo-electric polarimeters. We apply the unbinned technique to models of the luminous X-ray pulsar Hercules X-1, for which we produce

Armin Norouzi, Saeid Shahpouri, David Gordon, Alexander Winkler

Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine. In this work machine learning is applied in two methods. In the first application, ML is used to identify a model for implementation in model predictive control optimization problems.

Yuxiao Chen, Jip Kim, James Anderson

Distributionally robust optimization (DRO) is a powerful tool for decision making under uncertainty. It is particularly appealing because of its ability to leverage existing data. However, many practical problems call for decision-making with some auxiliary information, and DRO in the context of conditional distribution is not straightforward. We propose a c

Volodymyr Vovchenko, Volker Koch

We develop a framework to relate proton number cumulants measured in heavy-ion collisions within a momentum space acceptance to the susceptibilities of baryon number, assuming that particles are emitted from a fireball with uniform distribution of temperature and baryochemical potential, superimposed on a hydrodynamic flow velocity profile. The rapidity acce

Jorge Andrés Ibáñez Huertas, Carlos Isaac Zainea Maya

The prediction of the behavior of the disease, the level of affectation in a population and the ways to control it are the most important aspects studied by epidemiology using tools such as historical data and mathematical models. So, our objective is (1) to provide a tool capable of analyzing epidemiological phenomena starting from the most common social in

Jeffrey Carlson, Chen He

We completely characterize the pairs of connected Lie groups $G > K$ such that $\mathrm{rank}(G) - \mathrm{rank}(K) = 1$ and the left action of $K$ on $G/K$ is equivariantly formal. The analysis requires us to correct and extend an existing partial classification of homogeneous quotients $G/K$ with the rational homotopy type of a product of an odd- and an ev

Wei Yang, Balakumar Sundaralingam, Chris Paxton, Iretiayo Akinola

Human-robot handover is a fundamental yet challenging task in human-robot interaction and collaboration. Recently, remarkable progressions have been made in human-to-robot handovers of unknown objects by using learning-based grasp generators. However, how to responsively generate smooth motions to take an object from a human is still an open question. Specif

Xuegang Chen, Qiuchen Wu, Le Zhang, Yifei Hao

The inverse spinel ferrimagnetic NiCo$_2$O$_4$ possesses high magnetic Curie temperature $T_C$, high spin polarization, and strain-tunable magnetic anisotropy. Understanding the thickness scaling limit of these intriguing magnetic properties in NiCo$_2$O$_4$ thin films is critical for their implementation in nanoscale spintronic applications. In this work, w

Walter Zimmer, Marcus Grabler, Alois Knoll

This work aims to address the challenges in domain adaptation of 3D object detection using infrastructure LiDARs. We design a model DASE-ProPillars that can detect vehicles in infrastructure-based LiDARs in real-time. Our model uses PointPillars as the baseline model with additional modules to improve the 3D detection performance. To prove the effectiveness

V. A. Dzuba, V. V. Flambaum, M. T. Murphy, D. A. Berke

Sensitivity of the frequencies of twenty two atomic transitions to the variation of the fine structure constant $\alpha$ is calculated. The findings are to be used in search for possible variation of $\alpha$ across our Galaxy using high quality spectroscopic data for stars similar to our Sun.

Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi

In many machine learning tasks, input features with varying degrees of predictive capability are acquired at varying costs. In order to optimize the performance-cost trade-off, one would select features to observe a priori. However, given the changing context with previous observations, the subset of predictive features to select may change dynamically. Ther

Francesco Buccheri, Reinhold Egger, Alessandro De Martino

We study the low-energy single-electron transport across a junction of two magnetic Weyl semimetals, in which the anisotropy axes are tilted one respect to the other. Using a two-band model with a potential step, we compute the transmission factor for normal and Klein tunneling and the refraction properties of the interface as a function of the tilt angle. W

Xiangxu Yu, Zhengzhong Tu, Neil Birkbeck, Yilin Wang

In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased. However, relatively little research has been done on the automatic quality prediction of gaming videos, especially on those that fall in the category of "User-Generated-Content" (UGC). Sin

Mitchell Black, Mrdjan Jankovic, Abhishek Sharma, Dimitra Panagou

In this paper, we introduce a class of future-focused control barrier functions (ff-CBF) aimed at improving traditionally myopic CBF based control design and study their efficacy in the context of an unsignaled four-way intersection crossing problem for collections of both communicating and non-communicating autonomous vehicles. Our novel ff-CBF encodes that

Wen-Han Hwang, Jakub Stoklosa, Lu-Fang Chen

Site occupancy models are routinely used to estimate the probability of species presence from either abundance or presence-absence data collected across sites with repeated sampling occasions. In the last two decades, a broad class of occupancy models has been developed, but little attention has been given to examining the effects of heterogeneity in paramet

Sijie Zhu, Zhe Lin, Scott Cohen, Jason Kuen

Compositing-aware object search aims to find the most compatible objects for compositing given a background image and a query bounding box. Previous works focus on learning compatibility between the foreground object and background, but fail to learn other important factors from large-scale data, i.e. geometry and lighting. To move a step further, this paper

Raluca Rufu, Robin M. Canup

The origin of the Uranian satellite system remains uncertain. The four major satellites have nearly circular, co-planar orbits and the ratio of the satellite system and planetary mass resembles Jupiter's satellite system, suggesting the Uranian system was similarly formed within a disk produced by gas co-accretion. However, Uranus is a retrograde rotator wit

Kieran Finn, Viola Gattus, Sotirios Karamitsos, Apostolos Pilaftsis

For more than half a century, covariant and differential geometric methods have been playing a central role in the development of Quantum Field Theory (QFT). After a brief historic overview of the major scientific achievements using these methods, we will focus on the covariant and differential geometric formalism originally proposed by Vilkovisky and DeWitt

Neelay Junnarkar, He Yin, Fangda Gu, Murat Arcak

We propose a parameterization of a nonlinear dynamic controller based on the recurrent equilibrium network, a generalization of the recurrent neural network. We derive constraints on the parameterization under which the controller guarantees exponential stability of a partially observed dynamical system with sector bounded nonlinearities. Finally, we present

Enrique Pinero-Fuentes, Salvador Canas-Moreno, Antonio Rios-Navarro, Daniel Cascado-Caballero

In this work, an all-in-one neuromorphic controller system with reduced latency and power consumption for a robotic arm is presented. Biological muscle movement consists of stretching and shrinking fibres via spike-commanded signals that come from motor neurons, which in turn are connected to a central pattern generator neural structure. In addition, biologi

Subhankar Banerjee, Chung Shue Chen, Marceau Coupechoux, Abhishek Sinha

Non-orthogonal multiple access (NOMA) is a technology proposed for next generation cellular networks because of its high spectral efficiency and enhanced user connectivity. However, in the literature the optimal joint power and sub-carrier allocation for NOMA has been proposed for single cell only. Consequently, a global optimal algorithm for the joint power

Rodrigo R. Cuzinatto, Rajendra P. Gupta, Pedro J. Pompeia

A scalar-tensor theory of gravity is considered wherein the gravitational coupling $G$ and the speed of light $c$ are admitted as space-time functions and combine to form the definition of the scalar field $\phi$. The varying $c$ participates in the definition of the variation of the matter part of the action; it is related to the effective stress-energy ten

Petr Slovak, Alissa N. Antle, Nikki Theofanopoulou, Claudia Daudén Roquet

There is a growing interest in HCI to envision, design, and evaluate technology-enabled interventions that support users' emotion regulation. This interest stems in part from increased recognition that the ability to regulate emotions is critical to mental health, and that a lack of effective emotion regulation is a transdiagnostic factor for mental illness.

Leszek Pecyna, Siyuan Dong, Shan Luo

Manipulation of deformable objects is a challenging task for a robot. It will be problematic to use a single sensory input to track the behaviour of such objects: vision can be subjected to occlusions, whereas tactile inputs cannot capture the global information that is useful for the task. In this paper, we study the problem of using vision and tactile inpu

Hernán Ferrari, Carlos J. Zapata-Rodríguez, Mauro Cuevas

Manipulation of subwavelength objects by engineering the electromagnetic waves in the environment medium is pivotal for several particle handling techniques. In this letter, we theoretically demonstrate the possibility of engineering a compact and tunable plasmon-based terahertz tweezer using a graphene monolayer that is deposited on a high-index substrate.

Zhehui Liang, Sergei Treil

We study the inverse problem for the Hankel operators in the general case. Following the work of G\'erard--Grellier, the spectral data is obtained from the pair of Hankel operators $\Gamma$ and $\Gamma S$, where $S$ is the shift operator. The theory of complex symmetric operators provides a convenient language for the description of the spectral data. We int

Askold Khovanskii, Ivan Limonchenko, Leonid Monin

In this paper we develop a theory of volume polynomials of generalized virtual polytopes based on the study of topology of affine subspace arrangements in a real Euclidean space. We apply this theory to obtain a topological version of the BKK Theorem, the Stanley-Reisner and Pukhlikov-Khovanskii type descriptions for cohomology rings of generalized quasitori

Nitin Kumar, Rui Zhang, Steven A. Redford, Juan J. de Pablo

Active materials are those in which individual, uncoordinated local stresses drive the material out of equilibrium on a global scale. Examples of such assemblies can be seen across scales from schools of fish to the cellular cytoskeleton and underpin many important biological processes. Synthetic experiments that recapitulate the essential features of such a

Shahadat H. Sohel, Ramchandra Kotecha, Imran S Khan, Karen N. Heinselman

${\beta}$-Ga${_2}$O${_3}$ based semiconductor devices are expected to have significantly improved high-power and high-temperature performance due to its ultra-wide bandgap of close to 5 eV. However, the high-temperature operation of these ultra-wide-bandgap devices is usually limited by the relatively low 1-2 eV built-in potential at the Schottky barrier wit

Ziang Niu, Yuwen Gu, Wei Li

The method of instrumental variables provides a fundamental and practical tool for causal inference in many empirical studies where unmeasured confounding between the treatments and the outcome is present. Modern data such as the genetical genomics data from these studies are often high-dimensional. The high-dimensional linear instrumental-variables regressi

Akalanka Galappaththi, Sarah Nadi, Christoph Treude

Stack Overflow has become an essential technical resource for developers. However, given the vast amount of knowledge available on Stack Overflow, finding the right information that is relevant for a given task is still challenging, especially when a developer is looking for a solution that applies to their specific requirements or technology stack. Clearly

Nosrtollah Jafari

The effect of the linear-fractional transformations on the parallel lines in the spacetime has been studied. Fock-Lorentz transformations maps a line to a line, from which one can obtain the combinations rule for the velocities in the Fock-Lorentz transformations. Rigidity is defined as a consequences of holding parallelism under the transformations. The Foc

Yiming Lin, Sharad Mehrotra

Missing values widely exist in real-world data sets, and failure to clean the missing data may result in the poor quality of answers to queries. \yiming{Traditionally, missing value imputation has been studied as an offline process as part of preparing data for analysis.} This paper studies query-time missing value imputation and proposes QUIP, which only im

Nikitha Rao, Jason Tsay, Martin Hirzel, Vincent J. Hellendoorn

A central function of code review is to increase understanding; helping reviewers understand a code change aids in knowledge transfer and finding bugs. Comments in code largely serve a similar purpose, helping future readers understand the program. It is thus natural to study what happens when these two forms of understanding collide. We ask: what documentat

Walter Zimmer, Emec Ercelik, Xingcheng Zhou, Xavier Jair Diaz Ortiz

The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection methods, datasets, and challenges. We describe novel data augmentation methods, sampling strategies, activation functions, attention mechanisms, and regularization methods. Furthermore, we list recently introduced normalization methods, learning rate schedules and loss

Tewodros Amdeberhan, George E. Andrews, Cristina Ballantine

Franklin's identity generalizes Euler's identity and states that the number of partitions of $n$ with $j$ different parts divisible by $r$ equals the number of partitions of $n$ with $j$ repeated parts. In this article, we give a refinement of Franklin's identity when $j=1$. We prove Franklin's identity when $j=1$, $r=2$ for partitions with fixed perimeter,

Qiuyun Lu, Qiwei Xu, Jia Meng, Zuo Tong How

The global need for clean water requires sustainable technology for purifying contaminated water. Highly efficient solar-driven photodegradation is a sustainable strategy for wastewater treatment. In this work, we demonstrate that the photodegradation efficiency of micropollutants in water can be improved by ~2-24 times by leveraging polymeric microlenses (M

Sarah A. Horvath, Gregory G. Howes, Andrew J. McCubbin

The field-particle correlation technique utilizes single-point measurements to uncover signatures of various particle energization mechanisms in turbulent space plasmas. The signature of Landau damping by electrons has been found in both simulations and observations from Earth's magnetosheath using this technique, but instrumental limitations of spacecraft s

Giuseppe Castiglione, Gavin Ding, Masoud Hashemi, Christopher Srinivasa

Adversarial robustness is one of the essential safety criteria for guaranteeing the reliability of machine learning models. While various adversarial robustness testing approaches were introduced in the last decade, we note that most of them are incompatible with non-differentiable models such as tree ensembles. Since tree ensembles are widely used in indust

Zihui Xue, Radu Marculescu

Deep multimodal learning has achieved great progress in recent years. However, current fusion approaches are static in nature, i.e., they process and fuse multimodal inputs with identical computation, without accounting for diverse computational demands of different multimodal data. In this work, we propose dynamic multimodal fusion (DynMM), a new approach t

Jean-Mathieu Teissier, Wolf-Christian Müller

In this chapter, we aim at presenting the basic techniques necessary to go beyond the widely accepted paradigm of second-order numerics. We specifically focus on finite-volume schemes for hyperbolic conservation laws occuring in fluid approximations such as the equations of ideal magnetohydrodynamics or the Euler equations of gas dynamics. For the sake of cl

Yuanhanqing Huang, Jianghai Hu

In stochastic Nash equilibrium problems (SNEPs), it is natural for players to be uncertain about their complex environments and have multi-dimensional unknown parameters in their models. Among various SNEPs, this paper focuses on locally coupled network games where the objective of each rational player is subject to the aggregate influence of its neighbors.

Eion Blanchard, Philipp Hieronymi

We consider Presburger arithmetic extended by the sine function, call this extension sine-Presburger arithmetic ($\sin$-PA), and systematically study decision problems for sets of sentences in $\sin$-PA. In particular, we detail a decision algorithm for existential $\sin$-PA sentences under assumption of Schanuel's conjecture. This procedure reduces decision

Timothy Andeen, Julia Gonski, James Hirschauer, James Hoff

Calorimeters will provide critical measurements at future collider detectors. As the traditional challenge of high dynamic range, high precision, and high readout rates for signal amplitudes is compounded by increasing granularity and precision timing the readout systems will become increasingly complex. This white paper reviews the challenges and opportunit

Sijie Zhu, Mubarak Shah, Chen Chen

The dominant CNN-based methods for cross-view image geo-localization rely on polar transform and fail to model global correlation. We propose a pure transformer-based approach (TransGeo) to address these limitations from a different perspective. TransGeo takes full advantage of the strengths of transformer related to global information modeling and explicit

K. Aditya Mohan, Kyle M. Champley, Albert W. Reed, Steven M. Glenn

For material identification, characterization, and quantification, it is useful to estimate system-independent material properties that do not depend on the detailed specifications of the X-ray computed tomography (CT) system such as spectral response. System independent rho-e and Z-e (SIRZ) refers to a suite of methods for estimating the system independent

Selahattin Serdar Helli, Andac Hamamci

Automatic teeth segmentation in panoramic x-ray images is an important research subject of the image analysis in dentistry. In this study, we propose a post-processing stage to obtain a segmentation map in which the objects in the image are separated, and apply this technique to tooth instance segmentation with U-Net network. The post-processing consists of

Jean Rouat, Ramin Pichevar, Stéphane Loiselle

Source separation and speech recognition are very difficult in the context of noisy and corrupted speech. Most conventional techniques need huge databases to estimate speech (or noise) density probabilities to perform separation or recognition. We discuss the potential of perceptive speech analysis and processing in combination with biologically plausible ne

József Balogh, Felix Christian Clemen, Bernard Lidický, Sergey Norin

Denote by $q_n(G)$ the smallest eigenvalue of the signless Laplacian matrix of an $n$-vertex graph $G$. Brandt conjectured in 1997 that for regular triangle-free graphs $q_n(G) \leq \frac{4n}{25}$. We prove a stronger result: If $G$ is a triangle-free graph then $q_n(G) \leq \frac{15n}{94}< \frac{4n}{25}$. Brandt's conjecture is a subproblem of two famous co

Laura Weiler, Tina N. Mihm, James J. Shepherd

We introduce a straightforward Gaussian process regression (GPR) model for the transition structure factor of metal periodic coupled cluster singles and doubles (CCSD) calculations. This is inspired by the method introduced by Liao and Gr\"uneis for interpolating over the transition structure factor to obtain a finite size correction for CCSD [J. Chem. Phys.

Tom Lee, Ji Qi, Chaitanya A. Gadre, Huaixun Huyan

Oxide solid electrolytes (OSEs) have the potential to achieve improved safety and energy density for lithium-ion batteries, but their high grain-boundary (GB) resistance is a general bottleneck. In the most well studied perovskite OSE, Li3xLa2/3-xTiO3 (LLTO), the ionic conductivity of GBs is about three orders of magnitude lower than that of the bulk. In con

E. Elizalde, F. Izaurieta, C. Riveros, G. Salgado

This article studies the effects of an arbitrary dark matter spin tensor on the propagation of gravitational wave amplitude in the context of Einstein-Cartan theory. We choose to work with an arbitrary spin tensor because, given our ignorance of the nature of dark matter, it is sensible not to make further hypotheses on its spin and not to assume any particu

Leonardo P. C. da Cruz, Joan Torregrosa

We solve the center-focus problem in a class of piecewise quadratic polynomial differential systems with an invariant straight line. The separation curve is also a straight line which is not invariant. We provide families having at the origin a weak-foci of maximal order. In the continuous class, the cyclicity problem is also solved, being $3$ such maximal n

Jacky Chow, Muhammed Hatem

The current imaging gold standard for detecting paradoxical diaphragm motion and diagnosing hemidiaphragm paralysis is to perform the fluoroscopic sniff test. The images are visually examined by an experienced radiologist, and if one hemidiaphragm ascends while the other descends, then it is described as paradoxical motion, which is highly suggestive of hemi

Shangqi Gao, Xiahai Zhuang

Modeling statistics of image priors is useful for image super-resolution, but little attention has been paid from the massive works of deep learning-based methods. In this work, we propose a Bayesian image restoration framework, where natural image statistics are modeled with the combination of smoothness and sparsity priors. Concretely, firstly we consider

Daniel Dudt, Rory Conlin, Dario Panici, Egemen Kolemen

The DESC stellarator optimization code takes advantage of advanced numerical methods to search the full parameter space much faster than conventional tools. Only a single equilibrium solution is needed at each optimization step thanks to automatic differentiation, which efficiently provides exact derivative information. A Gauss-Newton trust-region optimizati

Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding

The principle of Maximal Coding Rate Reduction (MCR$^2$) has recently been proposed as a training objective for learning discriminative low-dimensional structures intrinsic to high-dimensional data to allow for more robust training than standard approaches, such as cross-entropy minimization. However, despite the advantages that have been shown for MCR$^2$ t

Nico Naus, Freek Verbeek, Marc Schoolderman, Binoy Ravindran

Automatic exploit generation is a relatively new area of research. Work in this area aims to automate the manual and labor intensive task of finding exploits in software. In this paper we present a novel program logic to support automatic exploit generation. We develop a program logic called Reachability Logic, which formally defines the relation between rea

Matthew Setzler, Elizabeth Coda, Jeremiah Rounds, Michael Vann

Due to the Internet of Things (IoT) proliferation, Radio Frequency (RF) channels are increasingly congested with new kinds of devices, which carry unique and diverse communication needs. This poses complex challenges in modern digital communications, and calls for the development of technological innovations that (i) optimize capacity (bitrate) in limited ba

Sergio Hernández-Cuenca, Veronika E. Hubeny, Massimiliano Rota

The holographic entropy cone characterizes the relations between entanglement entropies for a spatial partitioning of the boundary spacetime of a holographic CFT in any state describing a classical bulk geometry. We argue that the holographic entropy cone, for an arbitrary number of parties, can be reconstructed from more fundamental data determined solely b

Andrea Arnold

Estimating and quantifying uncertainty in unknown system parameters from limited data remains a challenging inverse problem in a variety of real-world applications. While many approaches focus on estimating constant parameters, a subset of these problems includes time-varying parameters with unknown evolution models that often cannot be directly observed. Th

Shirantha Welikala, Hai Lin, Panos J. Antsaklis

We consider the problem of on-line evaluation of critical characteristic parameters such as the L_2-gain (L2G), input feedforward passivity index (IFP) and output feedback passivity index (OFP) of non-linear systems using their input-output data. Typically, having an accurate measure of such "system indices" enables the application of systematic control desi

Octavio Arizmendi, Takahiro Hasebe, Franz Lehner

The present paper introduces a modified version of cyclic-monotone independence which originally arose in the context of random matrices, and also introduces its natural analogy called cyclic-Boolean independence. We investigate formulas for convolutions, limit theorems for sums of independent random variables, and also classify infinitely divisible distribu

Shriram Srinivasan, Kaarthik Sundar, Vitaliy Gyrya, Anatoly Zlotnik

We formulate a steady-state network flow problem for non-ideal gas that relates injection rates and nodal pressures in the network to flows in pipes. For this problem, we present and prove a theorem on uniqueness of generalized solution for a broad class of non-ideal pressure-density relations that satisfy a monotonicity property. Further, we develop a Newto

Tony Jin, David G. Martin

We introduce and study a new model consisting of a single classical random walker undergoing continuous monitoring at rate $\gamma$ on a discrete lattice. Although such a continuous measurement cannot affect physical observables, it has a non-trivial effect on the probability distribution of the random walker. At small $\gamma$, we show analytically that the

Kurt L Polzin, Yuri V Lvov

High-frequency wave propagation in near-inertial wave shear has been considered fundamental in setting the spectral character of the oceanic internal wave continuum and for transporting energy to wave-breaking. We compare idealized ray tracing numerical results with metrics derived using a wave turbulence derivation for the kinetic equation and a path integr

Zahraa Sh. Aaraji, Hawraa H. Abbas

Alzheimer's disease (AD) is one of the most common public health issues the world is facing today. This disease has a high prevalence primarily in the elderly accompanying memory loss and cognitive decline. AD detection is a challenging task which many authors have developed numerous computerized automatic diagnosis systems utilizing neuroimaging and other c

Muhammad Ammar Malik, Alexander S. Lundervold, Tom Michoel

Imaging genetic studies aim to find associations between genetic variants and imaging quantitative traits. Traditional genome-wide association studies (GWAS) are based on univariate statistical tests, but when multiple traits are analyzed together they suffer from a multiple-testing problem and from not taking into account correlations among the traits. An a

Dmitry Fuchs, Alexandre Kirillov

Let $\lambda$ be a partition of an integer $n$ and ${\mathbb F}_q$ be a finite field of order $q$. Let $P_\lambda(q)$ be the number of strictly upper triangular $n\times n$ matrices of the Jordan type $\lambda$. It is known that the polynomial $P_\lambda$ has a tendency to be divisible by high powers of $q$ and $Q=q-1$, and we put $P_\lambda(q)=q^{d(\lambda)

Dimuthu Wannipurage, Suresh Marru, Marlon Pierce

Jupyter Notebooks are an enormously popular tool for creating and narrating computational research projects. They also have enormous potential for creating reproducible scientific research artifacts. Capturing the complete state of a notebook has additional benefits; for instance, the notebook execution may be split between local and remote resources, where

Samik Sadhu, Hynek Hermansky

How important are different temporal speech modulations for speech recognition? We answer this question from two complementary perspectives. Firstly, we quantify the amount of phonetic \textit{information} in the modulation spectrum of speech by computing the mutual information between temporal modulations with frame-wise phoneme labels. Looking from another

Stanisław M. Dubiel, Jan Żukrowski

A very simple method for determining the center (isomer) shift, CS, of a M\"ossbauer spectrum is outlined. Its applicability is demonstrated on two examples viz. pyrite and a ternary sigma-phase Fe-Cr-Ni compound. Sets of the spectra recorded in the temperature interval of 78-295 K for the former, and 5-293 K for the latter were analyzed with the simple and

Ahmed Mohammed Cherif, Kaddour Zegga, Gherici Beldjilali

In this note, we find a necessary condition on odd-dimensional Riemannian manifolds under which both of Sasakian structure and the generalised Ricci soliton equation are satisfied, and we give some examples.

Bing Zhang, Yuya Jeremy Ong, Taiga Nakamura

Many machine learning (ML) models are integrated within the context of a larger system as part of a key component for decision making processes. Concretely, predictive models are often employed in estimating the parameters for the input values that are utilized for optimization models as isolated processes. Traditionally, the predictive models are built firs

Marcel de Korte, Jaebok Kim, Aki Kunikoshi, Adaeze Adigwe

Cross-lingual synthesis can be defined as the task of letting a speaker generate fluent synthetic speech in another language. This is a challenging task, and resulting speech can suffer from reduced naturalness, accented speech, and/or loss of essential voice characteristics. Previous research shows that many models appear to have insufficient generalization

A. R. C. Buarque, W. S. Dias, F. A. B. F. de Moura, M. L. Lyra

Rogue waves are rapid and unpredictable events of exceptional amplitude reported in various fields, such as oceanography and optics, with much of the interest being targeted towards their physical origins and likelihood of occurrence. Here, we use the all-round framework of discrete-time quantum walks to study the onset of those events due to a random phase

Luke Snow, Shashwat Jain, Vikram Krishnamurthy

In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and violation of the sure thing principle. We consider human-machine interaction involving a quantum decision maker (human) and a controller (machine). Given a sequence of human decis

Georgios Dosidis, João P. G. Ramos

In dimension $n=1$ we obtain $L^{p_1}(\mathbb R) \times\dots\times L^{p_m}(\mathbb R)$ to $L^p(\mathbb R)$ boundedness for the multilinear spherical maximal function in the largest possible open set of indices and we provide counterexamples that indicate the optimality of our results.

Ceyhun Onur, Arda Yurdakul

Remote voting has become more critical in recent years, especially after the Covid-19 outbreak. Blockchain technology and its benefits like decentralization, security, and transparency have encouraged remote voting systems to use blockchains. Analysis of existing solutions reveals that anonymity, robustness, and scalability are common problems in blockchain-

Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each o

Gargi Mukherjee

Let $\overline{p}(n)$ denote the overpartition function. In this paper, our primary goal is to study the asymptotic behavior of the finite differences of the logarithm of the overpartition function, i.e., $(-1)^{r-1}\Delta^r \log \p(n)$, by studying the inequality of the following form $$\log \Bigl(1+\dfrac{C(r)}{n^{r-1/2}}-\dfrac{C_1(r)}{n^{r}}\Bigr)<(-1)^{

Harshvardhan P. Joshi, Mihail L. Sichitiu, Maria Kihl

Numerous protocols for geocast have been proposed in literature. It has been shown that explicit route setup approaches perform poorly with VANETs due to limited route lifetime and frequent network fragmentation. The broadcast based approaches have considerable redundancy and add significantly to the overhead of the protocol. A completely distributed and rob

Leena Singh, Ranjan Singh, Weili Zhang

We report extensive enhancement in the refractive index of artificially designed metamaterials by exploiting the deep subwavelength coupling in a free-standing, thin-film metal-dielectric-metal checkboard structure. A record high refractive index of 77.02+43.22i is obtained at terahertz frequencies. The detailed investigations reveal that the enhancement of

Sergio Correia, Stephan Luck

This paper discusses how to successfully digitize large-scale historical micro-data by augmenting optical character recognition (OCR) engines with pre- and post-processing methods. Although OCR software has improved dramatically in recent years due to improvements in machine learning, off-the-shelf OCR applications still present high error rates which limit

Robert F. B. Weigel, Michael Schmiedeberg

We introduce a Phase Field Crystal (PFC) model for particles with n-fold rotational symmetry in two dimensions. Our approach is based on a free energy functional that depends on the reduced one-particle density, the strength of the orientation, and the direction of the orientation, where all these order parameters depend on the position. The functional is co

Ludvig Lindstrom, Sebin Gracy, Sindri Magnusson, Henrik Sandberg

The paper studies the problem of leakage localization in water distribution networks. For the case of a single pipe that suffers from a single leak, by taking recourse to pressure and flow measurements, and assuming those are noiseless, we provide a closed-form expression for leak localization, leak exponent and leak constant. For the aforementioned setting,

Parvin Malekzadeh, Mohammad Salimibeni, Ming Hou, Arash Mohammadi

Recent studies in neuroscience suggest that Successor Representation (SR)-based models provide adaptation to changes in the goal locations or reward function faster than model-free algorithms, together with lower computational cost compared to that of model-based algorithms. However, it is not known how such representation might help animals to manage uncert

Ian E. Fellows, Wolfgang Hladik, Jeffrey W. Eaton, Andrew C. Voetsch

Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for False Recency Rate (FRR) and Mean Duration of Recent Infection (MDRI) after applying recent infection testing algorithm (RI

Tejas Sudharshan Mathai, Sungwon Lee, Thomas C. Shen, Zhiyong Lu

Purpose: Identification of abdominal Lymph Nodes (LN) that are suspicious for metastasis in T2 Magnetic Resonance Imaging (MRI) scans is critical for staging of lymphoproliferative diseases. Prior work on LN detection has been limited to specific anatomical regions of the body (pelvis, rectum) in single MR slices. Therefore, the development of a universal ap

Nikolaos G. Fytas, Alexandros Vasilopoulos, Erol Vatansever, Anastasios Malakis

We investigate aspects of universality in the two-dimensional (2D) spin-$1$ Baxter-Wu model in a crystal field $\Delta$ using a parallel version of the multicanonical algorithm employed at constant temperature $T$. A detailed finite-size scaling analysis in the continuous regime of the $\Delta-T$ phase diagram of the model indicates that the transition belon

Manuel Alberto M. Ferreira

In the infinite servers queue with Poisson arrivals real life practical applications, the busy period and the busy cycle probabilistic study is of main importance. But it is a very difficult task. In this text, we show that by solving a Riccati equation induced by this queue transient probabilities monotony study as time functions, we obtain a collection of

L. Blanco, F. Jiménez, J. de Lucas, C. Sardón

A Lie system is a non-autonomous system of first-order ordinary differential equations whose general solution can be written via an autonomous function, a so-called (nonlinear) superposition rule of a finite number of particular solutions and some parameters to be related to initial conditions. Even if the superposition rules for some Lie systems are known,

Florian Ecker, Daniel Grumiller, Robert McNees

We introduce a family of 2D dilaton gravity models with state-dependent constant curvature so that dS$_2$ emerges as an excitation of AdS$_2$. Curiously, the strong coupling region corresponds to the asymptotic region geometrically. Apart from these key differences, many features resemble the Almheiri--Polchinski model. We discuss perturbative and non-pertur

Michail Akritidis, Nikolaos G. Fytas, Martin Weigel

We study the scaling of the average cluster size and percolation strength of geometrical clusters for the two-dimensional Ising model. By means of Monte Carlo simulations and a finite-size scaling analysis we discuss the appearance of corrections to scaling for different definitions of cluster sets. We find that including all percolating clusters, or excludi

Yinglun Zhu, Robert Nowak

The goal of active learning is to achieve the same accuracy achievable by passive learning, while using much fewer labels. Exponential savings in terms of label complexity have been proved in very special cases, but fundamental lower bounds show that such improvements are impossible in general. This suggests a need to explore alternative goals for active lea

Argyro Mainou, Nikolaos G. Fytas, Martin Weigel

We investigate the application of graph-cut methods for the study of the critical behaviour of the two-dimensional random-field Ising model. We focus on exact ground-state calculations, crossing the phase boundary of the model at zero temperature and varying the disorder strength. For this purpose we employ two different minimum-cut--maximum-flow algorithms,

Yu. A. Pusep, M. D. Teodoro, V. Laurindo, E. R. Cardozo de Oliveira

The diffusion of photo-generated holes is studied in a high-mobility mesoscopic GaAs\ channel where electrons exhibit hydrodynamic properties. It is shown that the injection of holes into such an electron system leads to the formation of a hydrodynamic three-component mixture consisted of electrons and photo-generated heavy and light holes. The obtained resu

Glen McGee, Ander Wilson, Brent A Coull, Thomas F Webster

A key goal of environmental health research is to assess the risk posed by mixtures of pollutants. As epidemiologic studies of mixtures can be expensive to conduct, it behooves researchers to incorporate prior knowledge about mixtures into their analyses. This work extends the Bayesian multiple index model (BMIM), which assumes the exposure-response function

Peter Boyle, Dennis Bollweg, Richard Brower, Norman Christ

The search for new physics requires a joint experimental and theoretical effort. Lattice QCD is already an essential tool for obtaining precise model-free theoretical predictions of the hadronic processes underlying many key experimental searches, such as those involving heavy flavor physics, the anomalous magnetic moment of the muon, nucleon-neutrino scatte

Wei Ren, Eleftherios Vlahakis, Nikolaos Athanasopoulos, Raphael M. Jungers

This paper studies optimal scheduling and resource allocation under allowable over-scheduling. Formulating an optimisation problem where over-scheduling is embedded, we derive an optimal solution that can be implemented by means of a new additive increase multiplicative decrease (AIMD) algorithm. After describing the AIMD-like scheduling mechanism as a switc