May 2022 arXiv papers — page 155

Rene Marczinzik

We show that for a Dynkin quiver $Q$ of type $E_7$ with a specific orientation, the path algebra $KQ$ has no slope function of the form $μ=\fracθ{\dim}$ that defines a total stability condition. This gives a counterexample to a conjecture of Reineke.

Hanneke Wiersema

In this short paper we generalise a result of Diamond--Sasaki connecting geometric modularity of algebraic weights to geometric modularity of non-algebraic weights and vice versa. In particular, we show that geometric modularity of non-algebraic weights implies geometric modularity of multiple algebraic weights, which is easy to see. More significantly, we s

Tobias Gburrek, Christoph Boeddeker, Thilo von Neumann, Tobias Cord-Landwehr

We propose a system that transcribes the conversation of a typical meeting scenario that is captured by a set of initially unsynchronized microphone arrays at unknown positions. It consists of subsystems for signal synchronization, including both sampling rate and sampling time offset estimation, diarization based on speaker and microphone array position est

Valerie Domcke, Keisuke Harigaya, Kyohei Mukaida

We consider the transfer of a U(1) charge density between Bose-Einstein condensates of complex scalar fields coupled to a thermal bath, focusing on the case of a homogeneous Affleck-Dine field transmitting the charge stored in its angular motion to an axion field. We demonstrate that in the absence of additional symmetries this charge transfer, aided by cosm

Federico Simonetta

This Thesis discusses the development of technologies for the automatic resynthesis of music recordings using digital synthesizers. First, the main issue is identified in the understanding of how Music Information Processing (MIP) methods can take into consideration the influence of the acoustic context on the music performance. For this, a novel conceptual

Giorgio Galanti, Marco Roncadelli

We offer a pedagogical introduction to axion-like particles (ALPs) as far as their relevance for high-energy astrophysics is concerned, from a few MeV to 1000 TeV. This review is self-contained, in such a way to be understandable even to non-specialists. Among other things, we discuss two strong hints at a specific ALP that emerge from two very different ast

M. Kemal Döner, André Großardt

Experiments witnessing the entanglement between two particles interacting only via the gravitational field have been proposed as a test whether gravity must be quantized. In the language of quantum information, a non-quantum gravitational force would be modeled by local operations with classical communication (LOCC), which cannot generate entanglement in an

Björn Erik Skovdal, Samuel D. Slöetjes, Merlin Pohlit, Henry Stopfel

We provide experimental and numerical evidence for thermal excitations within and among magnetic mesospins, forming artificial spin ice structures. At low temperatures, a decrease in magnetization and increase in susceptibility is observed with increasing temperature, interpreted as an onset of thermal fluctuations of the magnetic texture within the mesospin

Dwaipayan Roy, Zeljko Carevic, Philipp Mayr

In this paper, we investigate the retrievability of datasets and publications in a real-life Digital Library (DL). The measure of retrievability was originally developed to quantify the influence that a retrieval system has on the access to information. Retrievability can also enable DL engineers to evaluate their search engine to determine the ease with whi

Julian Chaidez, Oliver Edtmair

We construct the Ruelle invariant of a volume preserving flow and a symplectic cocycle in any dimension and prove several properties. In the special case of the linearized Reeb flow on the boundary of a convex domain $X$ in $\mathbb{R}^{2n}$, we prove that the Ruelle invariant $\text{Ru}(X)$, the period of the systole $c(X)$ and the volume $\text{vol}{X}$ sa

Ilias Chrysovergis, Manos Kamarianakis, Mike Kentros, Dimitris Angelis

We present a Convolutional Neural Network (CNN) suitable to assess unconstrained surgical cuttings, trained on a dataset created with a data augmentation technique.

Patrick Huembeli, Giuseppe Carleo, Antonio Mezzacapo

The optimal use of quantum and classical computational techniques together is important to address problems that cannot be easily solved by quantum computations alone. This is the case of the ground state problem for quantum many-body systems. We show here that probabilistic generative models can work in conjunction with quantum algorithms to design hybrid q

Jingyi Wang, Erin Kara, Matteo Lucchini, Adam Ingram

We perform the first systematic search of all NICER archival observations of black hole (and candidate) low-mass X-ray binaries for signatures of reverberation. Reverberation lags result from the light travel time difference between the direct coronal emission and the reflected disk component, and therefore their properties are a useful probe of the disk-cor

Manos Kamarianakis, Ilias Chrysovergis, Mike Kentros, George Papagiannakis

We introduce a novel method that describes the functionality and characteristics of an efficient VR recorder with replay capabilities, implemented in a modern game engine, publicly available for free.

Pouria Khodabandeh, Vahid Kayvanfar, Majid Rafiee, Frank Werner

One of the recently proposed strategies in health systems is providing services to patients at home, improving the service quality, besides reducing the health system costs. In the real world, some services, such as biological tests or blood sampling, force the nurses to start or end his/her route from/at the laboratory instead of the depot, changing the who

Lorenzo Ferreri, Gianmaria Verzini

We consider a weighted eigenvalue problem for the Dirichlet laplacian in a smooth bounded domain $Ω\subset \mathbb{R}^N$, where the bang-bang weight equals a positive constant $\overline{m}$ on a ball $B\subsetΩ$ and a negative constant $-\underline{m}$ on $Ω\setminus B$. The corresponding positive principal eigenvalue provides a threshold to detect persiste

Xiaohong Li, Xiang Wang, Kai Wang, Shiguo Lian

Generating synchronized and natural lip movement with speech is one of the most important tasks in creating realistic virtual characters. In this paper, we present a combined deep neural network of one-dimensional convolutions and LSTM to generate vertex displacement of a 3D template face model from variable-length speech input. The motion of the lower part

Joachim Krieger, Shengquan Xiang

We prove the semi-global controllability and stabilization of the $(1+1)$-dimensional wave maps equation with spatial domain $\mathbb{S}^1$ and target $\mathbb{S}^k$. First we show that damping stabilizes the system when the energy is strictly below the threshold $2π$, where harmonic maps appear as obstruction for global stabilization. Then, we adapt an iter

Manos Kamarianakis, Antonis Protopsaltis, Michail Tamiolakis, George Papagiannakis

We present a novel integration of a real-time continuous tearing algorithm for 3D meshes in VR, suitable for devices of low CPU/GPU specifications, along with a suitable particle decomposition that allows soft-body deformations on both the original and the torn model.

Emil Häglund, Johanna Björklund

Programmatic advertising consists in automated auctioning of digital ad space. Every time a user requests a web page, placeholders on the page are populated with ads from the highest-bidding advertisers. The bids are typically based on information about the user, and to an increasing extent, on information about the surrounding media context. The growing int

Olena S. Iadlovska, Kamal Thapa, Mojtaba Rajabi, Sergij V. Shiyanovskii

Unique electro-optical properties of the oblique helicoidal cholesteric (ChOH) stem from its heliconical director structure. An applied electric field preserves the single harmonic modulation of the director while tuning the ChOH period and the corresponding Bragg peak wavelength within a broad spectral range. We use the response of ChOH to the electric fiel

Minghui Yang, Peng Wu, Jing Liu, Hui Feng

Under the semi-supervised framework, we propose an end-to-end memory-based segmentation network (MemSeg) to detect surface defects on industrial products. Considering the small intra-class variance of products in the same production line, from the perspective of differences and commonalities, MemSeg introduces artificially simulated abnormal samples and memo

Yuansheng Wang, Wangbin Sun, Kun Xu, Zulun Zhu

Graph contrastive learning (GCL), as a popular approach to graph self-supervised learning, has recently achieved a non-negligible effect. To achieve superior performance, the majority of existing GCL methods elaborate on graph data augmentation to construct appropriate contrastive pairs. However, existing methods place more emphasis on the complex graph data

Erik van Heumen, Xuanbo Feng, Silvia Cassanelli, Linda Neubrand

Unlocking the mystery of the strange metal state has become the focal point of high T$_{c}$ research, not because of its importance for superconductivity, but because it appears to represent a truly novel phase of matter dubbed `quantum supreme matter'. Detected originally through high magnetic field, transport experiments, signatures of this phase have

Mauricio Mendez-Ruiz, Francisco Lopez-Tiro, Jonathan El-Beze, Vincent Estrade

Deep learning has shown great promise in diverse areas of computer vision, such as image classification, object detection and semantic segmentation, among many others. However, as it has been repeatedly demonstrated, deep learning methods trained on a dataset do not generalize well to datasets from other domains or even to similar datasets, due to data distr

Ashutosh Tewari, Antonio R. Paiva

Identifying and mitigating safety risks is paramount in a number of industries. In addition to guidelines and best practices, many industries already have safety management systems (SMSs) designed to monitor and reinforce good safety behaviors. The analytic capabilities to analyze the data acquired through such systems, however, are still lacking in terms of

Zichao Xiao, Rang Liu, Ming Li, Yang Liu

Symbol-level precoding (SLP), which converts the harmful multi-user interference (MUI) into beneficial signals, can significantly improve symbol-error-rate (SER) performance in multi-user communication systems. While enjoying symbolic gain, however, the complicated non-linear symbol-by-symbol precoder design suffers high computational complexity exponential

Annette Zippelius, Matthias Fuchs

A theory for the non-local stress in liquids captures the crossover from viscous to elastic correlations upon supercooling. It explains the emergence of long-ranged stress fields in glass which originate from the coupling of shear stress to transverse deformations. The Goldstone mode in colloidal glass is shown to be diffusive.

Nicolò Petri

In this contribution we review the ideas and results presented in the articles arXiv:2002.01764 and arXiv:2110.08276 where the decay of AdS vacua into bubbles of nothing is studied. We firstly consider AdS vacua in General Relativity with a cosmological constant and in arbitrary dimensions. In this context we study a class of gravitational instantons general

Côme Neyrand, Sophie Pinchinat

Dynamic Epistemic Logic (DEL) is a logic that models information change in a multi-agent setting through the use of action models with pre- and post-conditions. In a recent work, DEL has been extended to first-order epistemic logic (DFOEL), with a proof that the resulting Epistemic Planning Problem is decidable, as long as action models pre- and post-conditi

Jeanine Treffers-Daller and, Ozlem Çetinoğlu

In this paper we describe the process of collection, transcription, and annotation of recordings of spontaneous speech samples from Turkish-German bilinguals, and the compilation of a corpus called TuGeBiC. Participants in the study were adult Turkish-German bilinguals living in Germany or Turkey at the time of recording in the first half of the 1990s. The d

Sagar Garg, Stephan Rasp, Nils Thuerey

WeatherBench is a benchmark dataset for medium-range weather forecasting of geopotential, temperature and precipitation, consisting of preprocessed data, predefined evaluation metrics and a number of baseline models. WeatherBench Probability extends this to probabilistic forecasting by adding a set of established probabilistic verification metrics (continuou

Takashi Kagaya, Qing Liu, Hiroyoshi Mitake

This paper is concerned with a general class of fully nonlinear parabolic equations with monotone nonlocal terms. We investigate the quasiconvexity preserving property of positive, spatially coercive viscosity solutions. We prove that if the initial value is quasiconvex, the viscosity solution to the Cauchy problem stays quasiconvex in space for all time. Ou

Tobias Dornheim, Jan Vorberger, Zhandos Moldabekov, Panagiotis Tolias

We present extensive new \emph{ab initio} path integral Monte Carlo (PIMC) results for the spin-resolved density response of the uniform electron gas (UEG) at warm dense matter conditions. This allows us to unambiguously assess the accuracy of previous theoretical approximations, thereby providing valuable new insights for the future development of dielectri

Huan Gao, Jichang Guo, Guoli Wang, Qian Zhang

The performance of nighttime semantic segmentation is restricted by the poor illumination and a lack of pixel-wise annotation, which severely limit its application in autonomous driving. Existing works, e.g., using the twilight as the intermediate target domain to perform the adaptation from daytime to nighttime, may fail to cope with the inherent difference

E. Harriet Åhlgren, Alexander Markevich, Sophie Scharinger, Bernhard Fickl

Some of the materials are more affected by oxidation than others. To elucidate the oxidation-induced degradation mechanisms in transition metal chalcogenides, the chemical effects in single layer MoS$_2$ and MoTe$_2$ were studied in situ in an electron microscope under controlled low-pressure oxygen environments at room temperature.Oxidation is the main caus

Sangwook Baek, Yongsup Park, Youngo Park, Jungmin Lee

Convolutional neural network (CNN) based image enhancement methods such as super-resolution and detail enhancement have achieved remarkable performances. However, amounts of operations including convolution and parameters within the networks cost high computing power and need huge memory resource, which limits the applications with on-device requirements. Li

C. Angelo Guevara

Crawford's et al. (2021) article on estimation of discrete choice models with unobserved or latent consideration sets, presents a unified framework to address the problem in practice by using "sufficient sets", defined as a combination of past observed choices. The proposed approach is sustained in a re-interpretation of a consistency result by M

Zimeng Zhao, Binghui Zuo, Wei Xie, Yangang Wang

Physical contact provides additional constraints for hand-object state reconstruction as well as a basis for further understanding of interaction affordances. Estimating these severely occluded regions from monocular images presents a considerable challenge. Existing methods optimize the hand-object contact driven by distance threshold or prior from contact-

Marvin Weidner

The aim of this article is to prove that diffusion processes in $\mathbb{R}^d$ with a drift can be approximated by suitable Markov chains on $n^{-1}\mathbb{Z}^d$. Moreover, we investigate sufficient conditions on the conductances which guarantee convergence of the associated Markov chains to such Markov processes. Analogous questions are answered for a large

Tohru Koma

We study superconducting lattice fermions coupled to classical gauge fields. Namely, without the gauge fields, the lattice fermions show superconducting long-range order. In the previous paper, the existence of the long-range order was proved by the present author. This paper is the continuing part of the previous one. More precisely, the interactions betwee

Pawel Ladosz, Lilian Weng, Minwoo Kim, Hyondong Oh

This paper reviews exploration techniques in deep reinforcement learning. Exploration techniques are of primary importance when solving sparse reward problems. In sparse reward problems, the reward is rare, which means that the agent will not find the reward often by acting randomly. In such a scenario, it is challenging for reinforcement learning to learn r

Shuai Zhao, Linchao Zhu, Xiaohan Wang, Yi Yang

Recently, large-scale pre-training methods like CLIP have made great progress in multi-modal research such as text-video retrieval. In CLIP, transformers are vital for modeling complex multi-modal relations. However, in the vision transformer of CLIP, the essential visual tokenization process, which produces discrete visual token sequences, generates many ho

Rubio, F. J., Drikvandi, R

In many applications of survival data analysis, the individuals are treated in different medical centres or belong to different clusters defined by geographical or administrative regions. The analysis of such data requires accounting for between-cluster variability. Ignoring such variability would impose unrealistic assumptions in the analysis and could affe

Emma J. Gerritse, Faegheh Hasibi, Arjen P. de Vries

Pre-trained language models such as BERT have been a key ingredient to achieve state-of-the-art results on a variety of tasks in natural language processing and, more recently, also in information retrieval.Recent research even claims that BERT is able to capture factual knowledge about entity relations and properties, the information that is commonly obtain

Jesse Hoey, Gabrielle Chan

Any decision, such as one about who to hire, involves two components. First, a rational component, i.e., they have a good education, they speak clearly. Second, an affective component, based on observables such as visual features of race and gender, and possibly biased by stereotypes. Here we propose a method for measuring the affective, socially biased, com

Eric Bertin

We consider the problem of diffusion with stochastic resetting in a population of random walks where the diffusion coefficient is not constant, but behaves as a power-law of the average resetting rate of the population. Resetting occurs only beyond a threshold distance from the origin. This problem is motivated by physical realizations like soft matter under

Eduardo Noboro Tominaga, Onel Luiz Alcaraz López, Richard Demo Souza, Hirley Alves

The Fifth Generation (5G) of wireless networks introduced native support for Machine-Type Communication (MTC), which is a key enabler for the Internet of Things (IoT) revolution. Current 5G standards are not yet capable of fully satisfying the requirements of critical MTC (cMTC) and massive MTC (mMTC) use cases. This is the main reason why industry and acade

Shojiro Kimura, Shusaku Imajo, Masaki Gen, Tsutomu Momoi

In this study, we have performed the magnetocaloric effect and the specific heat measurements of chromium spinel oxide HgCr$_2$O$_4$, wherein the magnetic Cr$^{3+}$ ions form a highly frustrated pyrochlore lattice with significant spin-lattice coupling. In addition to the known magnetic-field-induced phases, our thermodynamic measurements detect a novel quan

Walter Morales-Alvarez, Novel Certad, Hadj. Hamma Tadjine, Cristina Olaverri-Monreal

In conditional automation, a response from the driver is expected when a take over request is issued due to unexpected events, emergencies, or reaching the operational design domain boundaries. Cooperation between the automated driving system and the driver can help to guarantee a safe and pleasant transfer if the driver is guided through a haptic guidance s

Beatriz Hernandez-Molinero, Raul Jimenez, Carlos Pena-Garay

Cosmic background neutrinos ($C_νB)$ helicity composition is different for Dirac or Majorana neutrinos making detectors based on $C_νB$ capture sensitive to the nature of neutrinos. We calculate, for the first time, the helicity changes of neutrinos crossing dark matter fields, to quantitatively calculate this effect on the capture rate. We show that a fract

Yang Li, Quan Pan, Erik Cambria

Recent adversarial attack developments have made reinforcement learning more vulnerable, and different approaches exist to deploy attacks against it, where the key is how to choose the right timing of the attack. Some work tries to design an attack evaluation function to select critical points that will be attacked if the value is greater than a certain thre

Alistair Plum, Tharindu Ranasinghe, Spencer Jones, Constantin Orasan

Extracting biographical information from online documents is a popular research topic among the information extraction (IE) community. Various natural language processing (NLP) techniques such as text classification, text summarisation and relation extraction are commonly used to achieve this. Among these techniques, RE is the most common since it can be dir

Marvin Zammit, Antonios Liapis, Georgios N. Yannakakis

This paper argues that generative art driven by conformance to a visual and/or semantic corpus lacks the necessary criteria to be considered creative. Among several issues identified in the literature, we focus on the fact that generative adversarial networks (GANs) that create a single image, in a vacuum, lack a concept of novelty regarding how their produc

Joel Dahne, Javier Gómez-Serrano

In this paper we prove the existence of a periodic highest, cusped, traveling wave solution for the Burgers-Hilbert equation $f_{t} + f f_{x} = H[f]$ and give its asymptotic behaviour at $0$. The proof combines careful asymptotic analysis and a computer-assisted approach.

Abhishek Deshpande

Reaction networks can display a wide array of dynamics. However, it is possible for different reaction networks to display the same dynamics. This phenomenon is called dynamical equivalence and makes network identification a hard problem to solve. We show that to find a strongly endotactic, endotactic, consistent, or conservative realization that is dynamica

Hiroaki Shinkawa, Nicolas Chauvet, Guillaume Bachelier, André Röhm

We all have preferences when multiple choices are available. If we insist on satisfying our preferences only, we may suffer a loss due to conflicts with other people's identical selections. Such a case applies when the choice cannot be divided into multiple pieces due to the intrinsic nature of the resources. Former studies, such as the top trading cycle

Hoang Kim Nguyen, Taichi Uemura

We introduce $\infty$-type theories as an $\infty$-categorical generalization of the categorical definition of type theories introduced by the second named author. We establish analogous results to the previous work including the construction of initial models of $\infty$-type theories, the construction of internal languages of models of $\infty$-type theori

Naoto Dainobu

Let $K$ be an unramified extension of $\mathbb{Q}_2$ and $μ_{2^n}$ the group of $2^n$-th root of unity for a fixed integer $n\geqslant 2$. In this paper, we give an explicit formula for the $μ_{2^n}$-valued Hilbert symbol over $K_n := K(μ_{2^n})$ using the theory of $(φ, Γ)$-modules.

James Noble, Julian Mackay, Tobias Wrigstad

Rust successfully applies ownership types to control memory allocation. This restricts the programs' topologies to the point where doubly-linked lists cannot be programmed in Safe Rust. We sketch how more flexible "local" ownership could be added to Rust, permitting multiple mutable references to objects, provided each reference is bounded by the

Alper T. Erdogan

We introduce a new information maximization (infomax) approach for the blind source separation problem. The proposed framework provides an information-theoretic perspective for determinant maximization-based structured matrix factorization methods such as nonnegative and polytopic matrix factorization. For this purpose, we use an alternative joint entropy me

Georg Bergner, Juan Camilo Lopez, Stefano Piemonte, Ivan Soler Calero

In this work we investigate the infrared behaviour of a Yang-Mills theory coupled to a massless fermion in the adjoint representation of the gauge group SU(2). This model has many interesting properties, corresponding to the $\mathcal{N}=2$ Super-Yang-Mills theory without scalars and in the recent years there has been an increasing interest toward understand

Nikolay Bazhenov, Dariusz Kalociński

Shapiro's notations for natural numbers, and the associated desideratum of acceptability - the property of a notation that all recursive functions are computable in it - is well-known in philosophy of computing. Computable structure theory, however, although capable of fully reconstructing Shapiro's approach, seems to be off philosophers' radar.

M. A. Kuntman, A. Kuntman, E. Kuntman

In polarization optics unitary and non-unitary operations can be carried out by the Jones matrix. $\mathbf{Z}$ matrix is the $4\times 4$ analogue of the Jones matrix and the Mueller matrix of a nondepolarizing optical medium can be written as $\mathbf{M}=\mathbf{Z}\mathbf{Z}^*$. Jones matrix acts on the two component complex Jones vector, while the $\mathbf{

Matteo Lucchini, Fabio Medeghini, Yingxuan Wu, Federico Vismarra

The advent of ultrafast laser science offers the unique opportunity to combine Floquet engineering with extreme time resolution, further pushing the optical control of matter into the petahertz domain. However, what is the shortest driving pulse for which Floquet states can be realised remains an unsolved matter, thus limiting the application of Floquet theo

James Noble, David Streader, Isaac Oscar Gariano, Miniruwani Samarakoon

Formal methods for software correctness are critical to the future of software engineering - and so must be an essential part of software engineering education. Unfortunately, formal methods are often resisted by students due to perceived difficulty, mathematicity, and practical irrelevance. We redeveloped our software correctness course by taking a programm

Stefano Berrone, Claudio Canuto, Moreno Pintore

We consider the discretization of elliptic boundary-value problems by variational physics-informed neural networks (VPINNs), in which test functions are continuous, piecewise linear functions on a triangulation of the domain. We define an a posteriori error estimator, made of a residual-type term, a loss-function term, and data oscillation terms. We prove th

Xiaoxia Li, Qili Li, Tongzhou Ji, Ruige Yan

Scanning tunneling microscopy is a powerful tool to build artificial atomic structures even not exist in nature but possess exotic properties. We here constructed Lieb lattices with different lattice constants by real atoms, i.e., Fe atoms on Ag(111) and probed their electronic properties. We find a surprising long-range effective electron wavefunction overl

Du Cheng, Patrick Felke, Frederik Gosewehr, Yixin Peng

In this paper a vulnerability in the Z-Wave protocol specification, especially in the S0 Z-Wave protocol is presented. Devices supporting this standard can be blocked (denial of service) through continuous S0 NonceGet requests. This way a whole network can be blocked if the attacked devices are Z-Wave network controller. This also effects S2 network controll

Hong-Han Lien, Chung-Wei Hsu, Tian-Sheuan Chang

Spiking neural networks (SNNs) that enable low-power design on edge devices have recently attracted significant research. However, the temporal characteristic of SNNs causes high latency, high bandwidth and high energy consumption for the hardware. In this work, we propose a binary weight spiking model with IF-based Batch Normalization for small time steps a

Hsu-Tung Shih, Tian-Sheuan Chang

The large amount of memory bandwidth between local buffer and external DRAM has become the speedup bottleneck of CNN hardware accelerators, especially for activation maps. To reduce memory bandwidth, we propose to learn pruning unimportant blocks dynamically with zero block regularization of activation maps (Zebra). This strategy has low computational overhe

Hong-Han Lien, Tian-Sheuan Chang

Spiking neural networks (SNNs), which are inspired by the human brain, have recently gained popularity due to their relatively simple and low-power hardware for transmitting binary spikes and highly sparse activation maps. However, because SNNs contain extra time dimension information, the SNN accelerator will require more buffers and take longer to infer, e

Dun-Hao Yang, Tian-Sheuan Chang

Increasingly, convolution neural network (CNN) based super resolution models have been proposed for better reconstruction results, but their large model size and complicated structure inhibit their real-time hardware implementation. Current hardware designs are limited to a plain network and suffer from lower quality and high memory bandwidth requirements. T

Zhiqing Guo, Gaobo Yang, Dengyong Zhang, Ming Xia

For image forensics, convolutional neural networks (CNNs) tend to learn content features rather than subtle manipulation traces, which limits forensic performance. Existing methods predominantly solve the above challenges by following a general pipeline, that is, subtracting the original pixel value from the predicted pixel value to make CNNs pay attention t

Pietro Cataldi, Leonardo Lamanna, Claudia Bertei, Federica Arena

Edible electronics will facilitate point-of-care testing through safe and cheap devices that are digested or degraded in the body or environment after performing a specific function. Its thrive depends on creating a library of materials that are the basic building blocks for eatable technologies. Edible electrical conductors fabricated with green methods tha

Mina Marmpena, Fernando Garcia, Angelica Lim, Nikolas Hemion

In social robotics, endowing humanoid robots with the ability to generate bodily expressions of affect can improve human-robot interaction and collaboration, since humans attribute, and perhaps subconsciously anticipate, such traces to perceive an agent as engaging, trustworthy, and socially present. Robotic emotional body language needs to be believable, nu

Paolo Liberatore

A superredundant clause is a clause that is redundant in the resolution closure of a formula. The converse concept of superirredundancy ensures membership of the clause in all minimal CNF formulae that are equivalent to the given one. This allows for building formulae where some clauses are fixed when minimizing size. An example are proofs of complexity hard

Zhili Chen, Zian Qian, Sukai Wang, Qifeng Chen

We present a novel octree-based multi-level framework for large-scale point cloud compression, which can organize sparse and unstructured point clouds in a memory-efficient way. In this framework, we propose a new entropy model that explores the hierarchical dependency in an octree using the context of siblings' children, ancestors, and neighbors to enco

Zhiqing Guo, Gaobo Yang, Jiyou Chen, Xingming Sun

Residual-domain feature is very useful for Deepfake detection because it suppresses irrelevant content features and preserves key manipulation traces. However, inappropriate residual prediction will bring side effects on detection accuracy. In addition, residual-domain features are easily affected by image operations such as compression. Most existing works

Florian Peters, Doris Neuberger, Oliver Reinhardt, Adelinde Uhrmacher

In macroeconomics, an emerging discussion of alternative monetary systems addresses the dimensions of systemic risk in advanced financial systems. Monetary regime changes with the aim of achieving a more sustainable financial system have already been discussed in several European parliaments and were the subject of a referendum in Switzerland. However, their

Erik Aurell, Jean Barbier, Aurelien Decelle, Roberto Mulet

This is a review to appear as a contribution to the edited volume "Spin Glass Theory & Far Beyond - Replica Symmetry Breaking after 40 Years", World Scientific. It showcases a selection of contributions from the spin glass community at large to high-dimensional statistics, by focusing on three important graph-based models and methodologies having dee

Pooja Basera, Saswata Bhattacharya

Chalcogenide perovskites have received considerable interest in photovoltaic research community owing to their stability (thermal and aqueous), non-toxicity and lead free composition. However, to date a theoretical study mainly focusing on the excitonic and polaronic properties are not explored rigorously, due to its huge computational demand. Herein, we cap

Befekadu G. Gebraselase, Bjarne E. Helvik, Yuming Jiang

Bitcoin is the first and the most extensive decentralized electronic cryptocurrency system that uses blockchain technology. It uses a peer-to-peer (P2P) network to operate without a central authority and propagate system information such as transactions or blockchain updates. The communication between participating nodes is highly relying on the underlying n

Daniele Dell'Erba, Sven Schewe

Calude et al. have recently shown that parity games can be solved in quasi-polynomial time, a landmark result that has led to a number of approaches with quasi-polynomial complexity. Jurdinski and Lasic have further improved the precise complexity of parity games, especially when the number of priorities is low (logarithmic in the number of positions). Both

Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang

In this paper, we investigate an online prediction strategy named as Discounted-Normal-Predictor (Kapralov and Panigrahy, 2010) for smoothed online convex optimization (SOCO), in which the learner needs to minimize not only the hitting cost but also the switching cost. In the setting of learning with expert advice, Daniely and Mansour (2019) demonstrate that

Emmanuel Fricain, Andreas Hartmann, Ross William T., Dan Timotin

In this paper, we obtain estimates for the solutions to the classical B{é}zout equation that are analogous to Carleson's solution to the corona theorem for the bounded analytic functions on the open unit disk. As an application, we extend some results of Luo and obtain a corona theorem for the multipliers of a class of de Branges--Rovnyak spaces.

Dorel Fetcu

We compute the Laplacian of the squared norm of the second fundamental form of a surface in Sol_3 and then use this Simons type formula to obtain some gap results for compact constant mean curvature surfaces of this space.

Maxime Clenet, François Massol, Jamal Najim

Lotka-Volterra (LV) equations play a key role in the mathematical modeling of various ecological, biological and chemical systems. When the number of species (or, depending on the viewpoint, chemical components) becomes large, basic but fundamental questions such as computing the number of surviving species still lack theoretical answers. In this paper, we c

Emmanuel Coffie, Xuerong Mao, Frank Proske

Fractional Brownian motion with the Hurst parameter $H<\frac{1}{2}$ is used widely, for instance, to describe a &#39;rough&#39; stochastic volatility process in finance. In this paper, we examine an Ait-Sahalia-type interest rate model driven by a fractional Brownian motion with $H<\frac{1}{2}$ and establish theoretical properties such as an existence-and-un

E. Ya. Paryev

We study the near-threshold $J/ψ$ meson production on protons and nuclei by considering incoherent direct non-resonant $K^-p \to {J/ψ}Λ$ and two-step resonant ${K^-}p \to P_{cs}(4459)^0 \to {J/ψ}Λ$ charmonium production processes. We calculate the absolute excitation functions, energy and momentum distributions for the non-resonant, resonant and for the comb

Alaa Dbeyssi, Bertold Froelich, Maria Carmen Mora Espi, Frank Maas

The feasibility of shielding axial magnetic fields up to 1.4~T, using a Bi-2212 hollow cylinder, is investigated at a temperature of 4.2~K. The residual magnetic flux density along the axis of the tube is measured at external fields of 1~T and 1.4~T. The shielding factor, defined as the ratio between the applied and the residual magnetic flux densities at th

O. Bychkova, E. Garutti, E. Popova, A. Stifutkin

A dedicated single-cell SiPM structure is designed and measured to investigate the radiation damage effects on the gain and breakdown voltage of SiPMs exposed to a reactor neutron fluence up to $Φ$ = 5e13 cm$^{-2}$. The cell has a pitch of 15 $μ$m. Results of the measurements and analysis of the IV-curves are presented. Impact of the self-heating effect was

Masaki Matsuno

A twisting system is one of the major tools to study graded algebras, however, it is often difficult to construct a (non-algebraic) twisting system if a graded algebra is given by generators and relations. In this paper, we show that a twisted algebra of a geometric algebra is determined by a certain automorphism of its point variety. As an application, we c

Christophe Charlier, Jonatan Lenells

We obtain large $n$ asymptotics for the $m$-point moment generating function of the disk counting statistics of the Mittag-Leffler ensemble. We focus on the critical regime where all disk boundaries are merging at speed $n^{-\smash{\frac{1}{2}}}$, either in the bulk or at the edge. As corollaries, we obtain two central limit theorems and precise large $n$ as

Smolentsev N. K., Podkur P. N

In this paper, Meyer wavelets with an arbitrary integer scaling factor $N>2$ are defined using wavelets with multiple scaling factors $MN>2$. Expressions for frequency functions of wavelets and corresponding filters are obtained.

Hermann Kroll, Jan Pirklbauer, Florian Plötzky, Wolf-Tilo Balke

Information extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on domain-specific training data. On the other hand, unsupervised and open extraction methods usually produce not-canonicalized ex

Pralhad M. Shinde

In this paper, we define the adjacency matrix of a semigraph. We give the conditions for a matrix to be semigraphical and give an algorithm to construct a semigraph from the semigraphical matrices. We derive lower and upper bounds for largest eigenvalues. We study the eigenvalues of adjacency matrix of two types of star semigraphs.

Jinkun Zhang, Yuezhou Liu, Edmund Yeh

Collaborative edge computing (CEC) is an emerging paradigm where heterogeneous edge devices (stakeholders) collaborate to fulfill computation tasks, such as model training or video processing, by sharing communication and computation resources. Nevertheless, the optimal data/result routing and computation offloading strategy in CEC with arbitrary topology st

Sama Arjika, Zouhaïr Mouayn

In this short paper, we establish connection formulae for trivariate $q$-polynomials.

Branko Gumhalter, Dino Novko, Hrvoje Petek

We explore the possibility of existence of plasmonically generated electronic Floquet bands at metal surfaces by studying the gauge transformed electron-surface plasmon interaction in the prepumped plasmonic coherent state environment. These bands may promote non-Einsteinian electron emission from metal surfaces exposed to primary interactions with strong el