August 2022 arXiv papers — page 132

Martin Bichler, Maximilian Fichtl, Matthias Oberlechner

Auctions are modeled as Bayesian games with continuous type and action spaces. Determining equilibria in auction games is computationally hard in general and no exact solution theory is known. We introduce an algorithmic framework in which we discretize type and action space and then learn distributional strategies via online optimization algorithms. One adv

Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya

In this paper, we propose a novel template matching method with a white balancing adjustment, called N-white balancing, which was proposed for multi-illuminant scenes. To reduce the influence of lighting effects, N-white balancing is applied to images for multi-illumination color constancy, and then a template matching method is carried out by using adjusted

Wentao Shi, Jing Xu, Pan Gao

It is well believed that Transformer performs better in semantic segmentation compared to convolutional neural networks. Nevertheless, the original Vision Transformer may lack of inductive biases of local neighborhoods and possess a high time complexity. Recently, Swin Transformer sets a new record in various vision tasks by using hierarchical architecture a

Asier López-Gordón, Leonardo Colombo, Manuel de León

In this paper, the theory of smooth action-dependent Lagrangian mechanics (also known as contact Lagrangians) is extended to a non-smooth context appropriate for collision problems. In particular, we develop a Herglotz variational principle for non-smooth action-dependent Lagrangians which leads to the preservation of energy and momentum at impacts. By defin

Cayla R. Harvey, Evan Weisman, Chethn Galla, Ryan Danenberg

Optically-levitated dielectric particles can serve as ultra-sensitive detectors of feeble forces and torques, as tools for use in quantum information science, and as a testbed for quantum coherence in macroscopic systems. Knowledge of the structural and optical properties of the particles is important for calibrating the sensitivity of such experiments. Here

Lisa Raithel, Philippe Thomas, Roland Roller, Oliver Sapina

In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content. The data consists of 4,169 binary annotated documents from a German patient forum, where users talk about health issues and get advice from medical doctors. As is common in social media data in this domain, the class labels of the corpus a

Timo Bertram, Johannes Fürnkranz, Martin Müller

In this work, we adapt a training approach inspired by the original AlphaGo system to play the imperfect information game of Reconnaissance Blind Chess. Using only the observations instead of a full description of the game state, we first train a supervised agent on publicly available game records. Next, we increase the performance of the agent through self-

Giuseppe Cavaliere, Sílvia Gonçalves, Morten Ørregaard Nielsen, Edoardo Zanelli

We consider bootstrap inference for estimators which are (asymptotically) biased. We show that, even when the bias term cannot be consistently estimated, valid inference can be obtained by proper implementations of the bootstrap. Specifically, we show that the prepivoting approach of Beran (1987, 1988), originally proposed to deliver higher-order refinements

Theodora Xylakis-Dornbusch, Norbert Christlieb, Karin Lind, Thomas Nordlander

Context. The study of the oldest and most metal-poor stars in our Galaxy promotes our understanding of the Galactic chemical evolution and the beginning of Galaxy and star formation. However, they are notoriously difficult to find, with only five stars at $\mathrm{[Fe/H]<-5.0}$ having been detected to date. Thus, the spectrophotometric data of 219 million so

Aikaterini Karakoulaki, David Head

Fractal structure emerges spontaneously from the chemical cross\-linking of monomers into hydrogels, and has been directly linked to power law visco\-elasticity at the gel transition, as recently demonstrated for isostatic (marginally--rigid) spring networks based on the Sierpinski triangle. Here we generalize the Sierpinski triangle generation rules to prod

Wagner Barreto-Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos, Hernando Ombao

We propose a general class of INteger-valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing time-varying mean and dispersion parameters, which we call time-varying dispersion INGARCH (tv-DINGARCH) models. More specifically, we consider mixed Poisson INGARCH models and allow for dynamic modeling of the dispersion para

Valentin Emberger, Michael Bonholzer, Johannes Müller-Seidlitz, Robert Andritschke

The focal plane of Athena's WFI consists of spectroscopic single photon X-ray detectors that contain arrays of DEPFETs (DEpleted P-channel Field-Effect Transistor) as well as ASICs that are used for steering, readout and analog signal shaping. These components have to be examined regarding the effect of ionizing radiation. A Total Ionizing Dose (TID) test wa

Yanting Feng, Ziyao Song, Fenglan Shao, Jun Song

We apply an equal-velocity quark combination model to systematically study the transverse momentum (p_{T}) spectra of strange hadrons K_{S}^{0}, \phi, \Lambda, \Xi^{-}, \Omega^{-}, \bar{\Lambda}, \bar{\Xi}^{+} and \bar{\Omega}^{+} at mid-rapidity in Au+Au collisions at \sqrt{s_{NN}}= 7.7, 11.5, 19.6, 27, 39, 54.4 GeV. Relative deviation between the model cal

Yilei Jiang, Dongkun Han

Finite-time motion planning with collision avoidance is a challenging issue in multi-agent systems. This paper proposes a novel distributed controller based on a new Lyapunov barrier function which guarantees finite-time stability for multi-agent systems without collisions. First, the problem of finite-time motion planning of multi-agent systems is formulate

Ziping Yu, Hongbo Huang, Weijun Chen, Yongxin Su

In recent years, face detection algorithms based on deep learning have made great progress. These algorithms can be generally divided into two categories, i.e. two-stage detector like Faster R-CNN and one-stage detector like YOLO. Because of the better balance between accuracy and speed, one-stage detectors have been widely used in many applications. In this

Ítalo Romani de Oliveira, José Alexandre T. Guerreiro Fregnani, Gláucia Costa Balvedi, Michael L. Ulrey

Each new concept of operation and equipment generation in aviation becomes more automated, integrated and interconnected. In the case of Unmanned Aircraft Systems (UAS), this evolution allows drastically decreasing aircraft weight and operational cost, but these benefits are also realized in highly automated manned aircraft and ground Air Traffic Control (AT

Severin Reiz, Tobias Neckel, Hans-Joachim Bungartz

Training deep neural networks consumes increasing computational resource shares in many compute centers. Often, a brute force approach to obtain hyperparameter values is employed. Our goal is (1) to enhance this by enabling second-order optimization methods with fewer hyperparameters for large-scale neural networks and (2) to perform a survey of the performa

Ran Damari, Amit Beer, Sharly Fleischer

A new and efficient method for orientation echo spectroscopy is presented and realized experimentally. The excitation scheme utilizes concerted rotational excitations by both ultrashort terahertz and near-IR pulses and its all-optical detection is enabled by Molecular Orientation Induced Second Harmonic method [J.Phys.Chem.A 126, 3732-3738 (2022)]. The metho

Malte C. Schroeder, Ugo Andral, Jean-Pierre Wolf

It was recently demonstrated that laser filamentation was able to generate an optically transparent channel through cloud and fog for free-space optical communications applications. However, no quantitative measurement of the interaction between the laser-induced shockwave and the aerosol particles was carried out so far, leaving the precise nature of the cl

Constantin Schuster, Mathias Wegner, Sebastian Kempf

So far, performance prediction and optimization of microwave SQUID multiplexers has largely been based on simple approximate analytical models and experimental results. This is caused by the complexity of the underlying physics and the intricacy of operation and readout parameters. As a simplified description can never account for all potential effects occur

Gokcen Gokceoglu, Emre Akbas

The prevalent approach in self-supervised image generation is to operate on pixel level representations. While this approach can produce high quality images, it cannot benefit from the simplicity and innate quality of vectorization. Here we present a drawing agent that operates on stroke-level representation of images. At each time step, the agent first asse

Yivan Zhang, Jindong Wang, Xing Xie, Masashi Sugiyama

Machine learning systems may encounter unexpected problems when the data distribution changes in the deployment environment. A major reason is that certain combinations of domains and labels are not observed during training but appear in the test environment. Although various invariance-based algorithms can be applied, we find that the performance gain is of

Lina María Amaya-Mejía, Nicolás Duque-Suárez, Daniel Jaramillo-Ramírez, Carol Martinez

Human safety has always been the main priority when working near an industrial robot. With the rise of Human-Robot Collaborative environments, physical barriers to avoiding collisions have been disappearing, increasing the risk of accidents and the need for solutions that ensure a safe Human-Robot Collaboration. This paper proposes a safety system that imple

Ravi Kumar, Dr. Nayana Vaval

Electronically excited atoms or molecules in an environment are often subject to interatomic/intermolecular Coulombic decay (ICD) and/or electron transfer mediated decay (ETMD) mechanisms. A few of the numerous variables that can impact these non-radiative decay mechanisms include bond distance, the number of nearby atoms or molecules, and the polarisation e

Wentian Lu, Kaijun Xie, Mingbo Liu, Xiaogang Wang

The coordinated alternating current optimal power flow (ACOPF) for coupled transmission-distribution grids has become crucial to handle problems related to high penetration of renewable energy sources (RESs). However, obtaining all system details and solving ACOPF centrally is not feasible because of privacy concerns. Intermittent RESs and uncontrollable loa

Dominic Sanderson, Tatiana Kalgonova

We propose a novel method for training a neural network for image classification to reduce input data dynamically, in order to reduce the costs of training a neural network model. As Deep Learning tasks become more popular, their computational complexity increases, leading to more intricate algorithms and models which have longer runtimes and require more in

Farhad Mehdifar, Charalampos P. Bechlioulis, Dimos V. Dimarogonas

This paper proposes a funnel control method under time-varying hard and soft output constraints. First, an online funnel planning scheme is designed that generates a constraint consistent funnel, which always respects hard (safety) constraints, and soft (performance) constraints are met only when they are not conflicting with the hard constraints. Next, the

Julia Hornauer, Vasileios Belagiannis

In monocular depth estimation, disturbances in the image context, like moving objects or reflecting materials, can easily lead to erroneous predictions. For that reason, uncertainty estimates for each pixel are necessary, in particular for safety-critical applications such as automated driving. We propose a post hoc uncertainty estimation approach for an alr

M. A. Vasiliev

The concepts of compact and projectively-compact spin-local spinor vertices are introduced. Vertices of this type are shown to be space-time spin-local, i.e. their restriction to any finite subset of fields is space-time local. The known spinor spin-local cubic vertices with the minimal number of space-time derivatives are verified to be projectively-compact

Yan Hao Ling, Jonathan Scarlett

We study error exponents for the problem of relaying a message over a tandem of two channels sharing the same transition law, in particular moving beyond the 1-bit setting studied in recent related works. Our main results show that the 1-hop and 2-hop exponents coincide in both of the following settings: (i) the number of messages is fixed, and the channel l

Kunal Shah, Krishan Rajaratnam

Kasabach-Merritt syndrome (KMS) is a rare, life-threatening condition that is characterized by profound thrombocytopenia, hypofibrinogenemia, elevated partial thromboplastin time, and may also be associated with microangiopathic hemolytic anemia. It is well established that this phenomenon is notably associated with the vascular tumors kaposiform hemangioend

Vladimir Kolmogorov

The Gomory-Hu tree, or a cut tree, is a classic data structure that stores minimum $s$-$t$ cuts of an undirected weighted graph for all pairs of nodes $(s,t)$. We propose a new approach for computing the cut tree based on a reduction to the problem that we call {\tt OrderedCuts}. Given a sequence of nodes $s,v_1,\ldots,v_\ell$, its goal is to compute minimum

Raju Krishnamoorthy, Jinbang Yang, Kang Zuo

Let $U$ be a smooth affine curve over a number field $K$ with a compactification $X$ and let $\mathbb L$ be a rank $2$, geometrically irreducible $\bar{\mathbb Q}_\ell$-local system on $U$ with cyclotomic determinant that extends to an integral model, has Frobenius traces all in some fixed number field $E\subset \bar{\mathbb Q}_\ell$, and has bad, infinite r

Jonathan Sanctorum, Jan Sijbers, Jan De Beenhouwer

The design of new x-ray phase contrast imaging setups often relies on Monte Carlo simulations for prospective parameter studies. Monte Carlo simulations are known to be accurate but time consuming, leading to long simulation times, especially when many parameter variations are required. This is certainly the case for imaging methods relying on absorbing mask

Hong-Lan Botterman, Julien Roussel, Thomas Morzadec, Ali Jabbari

We propose a robust principal component analysis (RPCA) framework to recover low-rank and sparse matrices from temporal observations. We develop an online version of the batch temporal algorithm in order to process larger datasets or streaming data. We empirically compare the proposed approaches with different RPCA frameworks and show their effectiveness in

Kangjun Liu, Ke Chen, Kui Jia

Fine-grained visual classification can be addressed by deep representation learning under supervision of manually pre-defined targets (e.g., one-hot or the Hadamard codes). Such target coding schemes are less flexible to model inter-class correlation and are sensitive to sparse and imbalanced data distribution as well. In light of this, this paper introduces

Xin Zhang, Ying-Cong Chen

Deep neural networks suffer from significant performance deterioration when there exists distribution shift between deployment and training. Domain Generalization (DG) aims to safely transfer a model to unseen target domains by only relying on a set of source domains. Although various DG approaches have been proposed, a recent study named DomainBed, reveals

Rajibul Shaikh

The Event Horizon Telescope (EHT) has recently observed the image and shadow of the supermassive compact object Sagittarius A$^*$ (Sgr A$^*$). According to the EHT collaboration, the observed image is consistent with the expected appearance of a Kerr black hole. However, it is well-known that some non-Kerr objects may mimic many of the properties of the Kerr

Xiaoshan Li, Guokuan Shao, Huan Wang

We give simple and unified proofs of weak holomorhpic Morse inequalities on complete manifolds, $q$-convex manifolds, pseudoconvex domains, weakly $1$-complete manifolds and covering manifolds. This paper is essentially based on the asymptotic Bergman kernel functions and the Bochner-Kodaira-Nakano formulas.

A. O. Lopes, G. Muller, A. Neumann

We consider a Riemmaniann compact manifold $M$, the associated Laplacian $\Delta$ and the corresponding Brownian motion $X_t$, $t\geq 0.$ Given a Lipschitz function $V:M\to\mathbb R$ we consider the operator $\frac{1}{2}\Delta+V$, which acts on differentiable functions $f: M\to\mathbb R$ via the operator $$\frac{1}{2} \Delta f(x)+\,V(x)f(x) ,$$ for all $x\in

Diego Fernández-Silvestre, Michael R. R. Good, Eric V. Linder

Quantum particle creation from spacetime horizons, or accelerating boundaries in the dynamical Casimir effect, can have an equilibrium, or thermal, distribution. Using an accelerating boundary in flat spacetime (moving mirror), we investigate the production of thermal energy flux despite non-equilibrium accelerations, the evolution between equilibrium states

Jesse Nyyssölä, Mika Mäntylä, Martín Varela

Software Log anomaly event detection with masked event prediction has various technical approaches with countless configurations and parameters. Our objective is to provide a baseline of settings for similar studies in the future. The models we use are the N-Gram model, which is a classic approach in the field of natural language processing (NLP), and two de

Martin Šmíd, Miloš Kopa

The paper deals with a risk averse dynamic programming problem with infinite horizon. First, the required assumptions are formulated to have the problem well defined. Then the Bellman equation is derived, which may be also seen as a standalone reinforcement learning problem. The fact that the Bellman operator is contraction is proved, guaranteeing convergenc

J. Knorst, A. O. Lopes, G. Muller, A. Neumann

Consider the semi-flow given by the continuous time shift $\Theta_t:\mathcal{D} \to \mathcal{D} $, $t \geq 0$, acting on the $\mathcal{D} $ of \textit{c\`{a}dl\`{a}g} paths $w: [0,\infty) \to S^1$, where $S^1$ is the unitary circle. We equip the space $\mathcal{D} $ with the Skorokhod metric, and we show that the semi-flow is expanding. We also introduce a s

Z. N. Osmanov, S. M. Mahajan

The earthward journey of ultra high energy electrons ($\sim 600$ TeV) produced in the Pulsar atmosphere by Landau damping of magneto-centrifugally excited Langmuir waves (drawing energy form the rotational slowdown) on primary electrons, is charted. It is shown, that just as they escape the light cylinder zone, the ultra-high energy particles, interacting wi

Simon Iteanu, Guillermo A. Mena Marugán

The hybrid and the dressed metric formalisms for the study of primordial perturbations in Loop Quantum Cosmology lead to dynamical equations for the modes of these perturbations that are of a generalized harmonic-oscillator type, with a mass that depends on the background but is the same for all modes. For quantum background states that are peaked on traject

Mohamed Aqalmoun

For a commutative ring $R$ with unit $1\ne 0$ and a multiplicatively closed subset $S$ of $R$, we introduce a new topology on the $S$-prime spectrum $\mathrm{Spec}_SR$ of $R$ called the $S$-flat topology. Our aims is to give an algebraic descriptions of the topological properties like compactness, irreducibility, connectivity and noetherianess with respect t

Lili Du, Dan Li

In our earlier work \cite{DLL}, we have shown the global well-posedness of strong solutions to the three-dimensional primitive equations with the magnetic field (PEM) on a thin domain. The heart of this paper is to provide a rigorous justification of the derivation of the PEM as the small aspect ratio limit of the incompressible three-dimensional scaled magn

Songlin Guo, Wei Wang, Chuanming Wang

The Wiener index of a connected graph is the sum of distances between all unordered pairs of vertices. Sam Spiro [The Wiener index of signed graphs, Appl. Math. Comput., 416(2022)126755] recently introduced the Wiener index for a signed graph and conjectured that the path $P_n$ with alternating signs has the minimum Wiener index among all signed trees with $

Pawel Cieslinski, Jan Dziewior, Lukas Knips, Waldemar Klobus

Detecting entanglement in multipartite quantum states is an inherently probabilistic process, typically with a few measured samples. The level of confidence in entanglement detection quantifies the scheme's validity via the probability that the signal comes from a separable state, offering a meaningful figure of merit for big datasets. Yet, with limited samp

Jakob Schweer, Daniel Steinmeyer, Klemens Hammerer, Michèle Heurs

Coherent quantum noise cancellation (CQNC) can be used in optomechanical sensors to surpass the standard quantum limit (SQL). In this paper, we investigate an optomechanical force sensor that uses the CQNC strategy by cascading the optomechanical system with an all-optical effective negative mass oscillator. Specifically, we analyze matching conditions, loss

Julian Bernhardt, Christian S. Fischer, Philipp Isserstedt

We present results for the volume dependence of baryon number fluctuations in the vicinity of the (conjectured) critical endpoint of QCD. They are extracted from the nonperturbative quark propagator that is obtained as a solution to a set of truncated Dyson--Schwinger equations of ($2 + 1$)-flavor QCD in Landau gauge, which takes the backcoupling of quarks o

Dinesh Nayak, Bishal Chhetri, D. K. K. Vamsi, Swapna Muthusamy

Leprosy (Hansen's disease) is an infectious, neglected tropical disease caused by the Mycobacterium Leprae (M. Leprae). Each year there are approximately 2,02,189 new cases are detected globally. In the year 2017 more than half million people were disabled due to leprosy and almost 50000 new cases are added every year world wide. In leprosy, lepra reactions

Rafał Owarzany, Tomasz Jaron, Krzysztof Kazimierczuk, Przemysław J. Malinowski

Attempts of synthesis of ionic (NH4)(BH3NH2BH2NH2BH3) using metathetical approach resulted in a mixture of the target compound and a partly dehydrogenated molecular NH3BH2NH2BH2NH2BH3 product. The mixed specimen was characterized by NMR and vibrational spectroscopies, and the crystal structure of their cocrystal was solved from powder x-ray diffraction data,

Shijun Liao

The so-called ``small denominator problem'' was a fundamental problem of dynamics, as pointed out by Poincar\'{e}. Small denominators appear most commonly in perturbative theory. The Duffing equation is the simplest example of a non-integrable system exhibiting all problems due to small denominators. In this paper, using the forced Duffing equation as an exa

Alexander Nüßeler, Dario Tamascelli, Andrea Smirne, James Lim

We exploit the properties of chain mapping transformations of bosonic environments to identify a finite collection of modes able to capture the characteristic features, or fingerprint, of the environment. Moreover we show that the countable infinity of residual bath modes can be replaced by a universal Markovian closure, namely a small collection of damped m

Dionysis Theodosis, Iasson Karafyllis, Markos Papageorgiou

The paper introduces novel families of cruise controllers for autonomous vehicles on lane-free ring-roads. The design of the cruise controllers is based on the appropriate selection of a Control Lyapunov Function expressed on measures of the energy of the system with the kinetic energy expressed in ways similar to Newtonian or relativistic mechanics. The der

Dorota Młynarczyk, Pedro Puig, Carmen Armero, Virgilio Gómez-Rubio

To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker, phosphorylated gamma-H2AX protein, is used to evaluate cell damage and is thus suitable for the dose estimation process. In this paper, we present new Bayesian methods that, in co

A. Sakovich, C. Sormani

A Lorentzian manifold endowed with a time function, $\tau$, can be converted into a metric space using the null distance, $\hat{d}_\tau$, defined by Sormani and Vega. We show that if the time function is a proper regular cosmological time function as studied by Andersson, Galloway and Howard, and also by Wald and Yip, or if, more generally, it satisfies the

Battulga Gankhuu

Because the asset value of a private company does not observable except in quarterly reports, the structural model has not been developed for a private company. For this reason, this paper attempt to develop the Merton's structural model for the private company by using the dividend discount model (DDM). In this paper, we obtain closed--form formulas of risk

Tushar Shankar Walunj, Shiksha Singhal, Veeraruna Kavitha, Jayakrishnan Nair

We analyse a non-cooperative strategic game among two ride-hailing platforms, each of which is modeled as a two-sided queueing system, where drivers (with a certain patience level) are assumed to arrive according to a Poisson process at a fixed rate, while the arrival process of passengers is split across the two providers based on QoS considerations. We als

Kensuke Ohtake

Two spatial equilibria, agglomeration and dispersion, in a continuous space core-periphery model are examined to discuss which equilibrium is socially preferred. It is shown that when transport cost is lower than a critical value, the agglomeration equilibrium is preferable in the sense of Scitovszky, while when the transport cost is above the critical value

Yujia Chen, Xiaoxue Ren, Cuiyun Gao, Yun Peng

Developers often need to decide which APIs to use for the functions being implemented. With the ever-growing number of APIs and libraries, it becomes increasingly difficult for developers to find appropriate APIs, indicating the necessity of automatic API usage recommendation. Previous studies adopt statistical models or collaborative filtering methods to mi

Igor Skrypnik, Yevgeniia Yevgenieva

We prove continuity and Harnack's inequality for bounded solutions to the equation $$ {\rm div}\big(|\nabla u|^{p(x)-2}\,\nabla u \big)=0, \quad p(x)= p + L\frac{\log\log\frac{1}{|x-x_{0}|}}{\log\frac{1}{|x-x_{0}|}},\quad L > 0, $$ under the precise non-logarithmic condition on the function $p(x)$.

Abhishek Tiwari, Jyoti Prakash, Alimerdan Rahimov, Christian Hammer

Numerous studies demonstrated that browser fingerprinting is detrimental to users' security and privacy. However, little is known about the effects of browser fingerprinting on Android hybrid apps -- where a stripped-down Chromium browser is integrated into an app. These apps expand the attack surface by employing two-way communication between native apps an

Frank Windmeijer

This paper is concerned with the findings related to the robust first-stage F-statistic in the Monte Carlo analysis of Andrews (2018), who found in a heteroskedastic grouped-data design that even for very large values of the robust F-statistic, the standard 2SLS confidence intervals had large coverage distortions. This finding appears to discredit the robust

Bing Xue, Pasi Koivumaki, Lauri Vaha-Savo, Katsuyuki Haneda

Penetration of cellphones into markets requires their robust operation in time-varying radio environments, especially for millimeter-wave communications. Hands and fingers of a human cause significant changes in the physical environments of cellphones, which influence the communication qualities to a large extent. In this paper, electromagnetic models of rea

Surya Pratap S Deopa, Shatruhan Singh Rajput, Aadarsh Kumar, Shivprasad Patil

The nanomechanical response of a folded single protein, the natural nanomachine responsible for myriad biological processes, provides insight into its function. The conformational flexibility of a folded state, characterized by its viscoelasticity, allows proteins to adopt different shapes to perform their function. Despite efforts, its direct measurement ha

Paolo Stornati, Philipp Krah, Karl Jansen, Debasish Banerjee

Condensed matter physics of gauge theories coupled to fermions can exhibit a rich phase structure, but are nevertheless very difficult to study in Monte Carlo simulations when they are afflicted by a sign problem. As an alternate approach, we use tensor network methods to explore the finite density physics of Abelian gauge theories without dynamical matter.

Nouar AlDahoul, Hezerul Abdul Karim, Shaira Limson Kee, Myles Joshua Toledo Tan

IPIs caused by protozoan and helminth parasites are among the most common infections in humans in LMICs. They are regarded as a severe public health concern, as they cause a wide array of potentially detrimental health conditions. Researchers have been developing pattern recognition techniques for the automatic identification of parasite eggs in microscopic

Benedetta Piroddi

Given $X$ a K3 surface admitting a symplectic automorphism $\tau$ of order 4, we describe the isometry $\tau^*$ on $H^2(X,\mathbb Z)$. Having called $\tilde Z$ and $\tilde Y$ respectively the minimal resolutions of the quotient surfaces $Z=X/\tau^2$ and $Y=X/\tau$, we also describe the maps induced in cohomology by the rational quotient maps $X\rightarrow\ti

Paul Gassiat, Łukasz Mądry

We obtain well-posedness results for a class of ODE with a singular drift and additive fractional noise, whose right-hand-side involves some bounded variation terms depending on the solution. Examples of such equations are reflected equations, where the solution is constrained to remain in a rectangular domain, as well as so-called perturbed equations, where

Vladimir Petrik, Mohammad Nomaan Qureshi, Josef Sivic, Makarand Tapaswi

We aim to teach robots to perform simple object manipulation tasks by watching a single video demonstration. Towards this goal, we propose an optimization approach that outputs a coarse and temporally evolving 3D scene to mimic the action demonstrated in the input video. Similar to previous work, a differentiable renderer ensures perceptual fidelity between

Vladimir Parfenyev

It is well known that an inverse turbulent cascade in a finite ($2 \pi \times 2 \pi$) two-dimensional periodic domain leads to the emergence of a system-sized coherent vortex dipole. We report a numerical hyperviscous study of the spatial vorticity profile inside one of the vortices. The exciting force was shortly correlated in time, random in space, and had

Thomas Le Corre, Ana Busic, Sean Meyn

This paper concerns the application of techniques from optimal transport (OT) to mean field control, in which the probability measures of interest in OT correspond to empirical distributions associated with a large collection of controlled agents. The control objective of interest motivates a one-sided relaxation of OT, in which the first marginal is fixed a

Aleksandr Kim, Guillem Brasó, Aljoša Ošep, Laura Leal-Taixé

Most (3D) multi-object tracking methods rely on appearance-based cues for data association. By contrast, we investigate how far we can get by only encoding geometric relationships between objects in 3D space as cues for data-driven data association. We encode 3D detections as nodes in a graph, where spatial and temporal pairwise relations among objects are e

Tim Frommknecht, Pedro Alves Zipf, Quanfu Fan, Nina Shvetsova

Recently, a number of new Semi-Supervised Learning methods have emerged. As the accuracy for ImageNet and similar datasets increased over time, the performance on tasks beyond the classification of natural images is yet to be explored. Most Semi-Supervised Learning methods rely on a carefully manually designed data augmentation pipeline that is not transfera

Nora Weickgenannt, David Wagner, Enrico Speranza, Dirk H. Rischke

We derive relativistic dissipative spin hydrodynamics from kinetic theory featuring a nonlocal collision term using the method of moments. In this framework, the components of the spin tensor are dynamical variables which obey relaxation-type equations. We find that the corresponding relaxation times are determined by the local part of the collision term, wh

Juncheng Li, Junlin Xie, Linchao Zhu, Long Qian

Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion classification, failing to locate the temporal window corresponding to the emotion. In this paper, we introduce a new task, named Temporal Emotion Localization in videos~(TEL), whic

Ajinkya Gaikwad, Hitendra Kumar, Soumen Maity, Saket Saurabh

In this paper we study a maximization version of the classical Feedback Vertex Set (FVS) problem, namely, the Max Min FVS problem, in the realm of parameterized complexity. In this problem, given an undirected graph $G$, a positive integer $k$, the question is to check whether $G$ has a minimal feedback vertex set of size at least $k$. We obtain following re

Marco Fellous-Asiani, Raphaël Mothe, Léa Bresque, Hippolyte Dourdent

Quantum mechanics allows processes to be superposed, leading to a genuinely quantum lack of causal structure. For example, the process known as the quantum switch applies two operations ${\cal A}$ and ${\cal B}$ in a superposition of the two possible orders, ${\cal A}$ before ${\cal B}$ and ${\cal B}$ before ${\cal A}$. Experimental implementations of the qu

Jan Hartman, Davorin Kopič

In this work, we present a scalable and efficient system for exploring the supply landscape in real-time bidding. The system directs exploration based on the predictive uncertainty of models used for click-through rate prediction and works in a high-throughput, low-latency environment. Through online A/B testing, we demonstrate that exploration with model un

Keming Liu, Xiying Yuan

In this paper, an upper bound on the nullity of signed graphs in terms of the cyclomatic number and the number of pendant vertices is proved, and the corresponding extremal signed graphs are completely characterized.

Mengmeng Xu, Cheng-Yang Fu, Yanghao Li, Bernard Ghanem

The recently released Ego4D dataset and benchmark significantly scales and diversifies the first-person visual perception data. In Ego4D, the Visual Queries 2D Localization task aims to retrieve objects appeared in the past from the recording in the first-person view. This task requires a system to spatially and temporally localize the most recent appearance

Manisha Das Chaity, Masud An Nur Islam Fahim

Unpaired image denoising has achieved promising development over the last few years. Regardless of the performance, methods tend to heavily rely on underlying noise properties or any assumption which is not always practical. Alternatively, if we can ground the problem from a structural perspective rather than noise statistics, we can achieve a more robust so

Cristina Padovani, Margherita Porcelli

We propose an algorithm for computing the projection of a symmetric second-order tensor onto the cone of negative semidefinite symmetric tensors with respect to the inner product defined by an assigned positive definite symmetric fourth-order tensor C. The projection problem is written as a semidefinite programming problem and an algorithm based on a primal-

Mingyuan Gao, Hung Dang, Ee-Chien Chang, Jialin Li

Blockchain systems are designed, built and operated in the presence of failures. There are two dominant failure models, namely crash fault and Byzantine fault. Byzantine fault tolerance (BFT) protocols offer stronger security guarantees, and thus are widely used in blockchain systems. However, their security guarantees come at a dear cost to their performanc

Manuel V. Gnann, Rik W. S. Westdorp, Joris van Winden

We prove well-posedness in $H^{\sigma}(\mathbb{R})$ for any $\sigma \in [0,\infty)$ of a parametrically forced nonlinear Schr\"odinger equation (PFNLS) in one dimension driven by multiplicative Stratonovich noise which has spatially homogeneous statistics. The noise is white in time and correlated in space. We first construct local mild solutions via a fixed

Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng

Recently low-precision deep learning accelerators (DLAs) have become popular due to their advantages in chip area and energy consumption, yet the low-precision quantized models on these DLAs bring in severe accuracy degradation. One way to achieve both high accuracy and efficient inference is to deploy high-precision neural networks on low-precision DLAs, wh

Ming-Hui Yu, Xian-Hui Ge

The Fabbri-Russo model is a generalized model of a two-dimensional dilaton gravity theory with various parameters "$n$" describing various specific gravities. Particularly, the Russo-Susskind-Thorlacius gravity model fits the case $n=1$. In the Fabbri-Russo model, we investigate Page curves and the entanglement island. Islands are considered in eternal and e

Zhaolin Wang, Xidong Mu, Yuanwei Liu, Robert Schober

A general optimization framework is proposed for simultaneously transmitting and reflecting reconfigurable surfaces (STAR-RISs) with coupled phase shifts, which converges to the Karush-Kuhn-Tucker (KKT) optimal solution under some mild conditions. More particularly, the amplitude and phase-shift coefficients of STAR-RISs are optimized alternatively in closed

F. Rico-Villas, E. González-Alfonso, J. Martín-Pintado, V. M. Rivilla

Using high angular resolution ALMA observations ($0.02^{\prime\prime}\approx0.34$ pc), we study the thermal structure and kinematics of the proto super star cluster $13$ in the central region of NGC253 through their continuum and vibrationally excited HC$_3$N emission from $J=24-23$ and $J=26-25$ lines arising from vibrational states up to $v_4=1$. We have c

Tongyue Shi, Siyu Tao, Haining Wang

For a long time, water and hydroelectric power are relatively important resources. Their rational distribution is closely related to regional agriculture, industry, residents, etc. In this paper, we mainly study the problem of allocation scheme for Glen Canyon Dam and Hoover Dam in the Colorado River Basin. Taking into consideration of various factors, we bu

D. Mimoun, A. Cadu, N. Murdoch, A. Sournac

The Mars Microphone is one of the five measurement techniques of SuperCam, an improved version of the ChemCam instrument that has been functioning aboard the Curiosity rover for several years. SuperCam is located on the Rover's Mast Unit, to take advantage of the unique pointing capabilities of the rover's head. In addition to being the first instrument to r

Hendrik Paul Lopuhaä, Valerie Gares, Anne Ruiz-Gazen

We provide a unified approach to S-estimation in balanced linear models with structured covariance matrices. Of main interest are S-estimators for linear mixed effects models, but our approach also includes S-estimators in several other standard multivariate models, such as multiple regression, multivariate regression, and multivariate location and scatter.

D. Savran, J. Isaak, R. Schwengner, R. Massarczyk

[Background] Photon strength functions are an important ingredient in calculations relevant for the nucleosynthesis of heavy elements. The relation to the photoabsorption cross section allows to experimentally constrain photon strength functions by investigating the photo-response of atomic nuclei. [Purpose] We determine the photoresponse of $^{66}$Zn in the

Tapas Singha, Anirban Polley, Mustansir Barma

Integrin is an important transmembrane receptor protein which remodels the actin network and anchors the cell membrane towards the extracellular matrix via mechanochemical pathways. The clustering of specific lipids and lipid-anchored proteins, which is essential for a certain type of endocytosis process, is facilitated at integrin-mediated active regions. T

A. Fraser-McKelvie, L. Cortese

It is generally assumed that galaxies are a bimodal population in both star formation and structure: star-forming galaxies are disks, while passive galaxies host large bulges or are entirely spheroidal. Here, we test this scenario by presenting a full census of the kinematic morphologies of a volume-limited sample of galaxies in the local Universe extracted

Weidong Li, Haifan Yin, Ziao Qin, Yandi Cao

This paper addresses the mobility problem in massive multiple-input multiple-output systems, which leads to significant performance losses in the practical deployment of the fifth generation mobile communication networks. We propose a novel channel prediction method based on multi-dimensional matrix pencil (MDMP), which estimates the path parameters by explo

Sam G. Bishop, John P. Hadden, Faris D. Alzahrani, Reza Hekmati

A device that is able to produce single photons is a fundamental building block for a number of quantum technologies. Significant progress has been made in engineering quantum emission in the solid state, for instance, using semiconductor quantum dots as well as defect sites in bulk and two-dimensional materials. Here we report the discovery of a room-temper