September 2022 arXiv papers — page 5

Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon

In supervised learning - for instance in image classification - modern massive datasets are commonly labeled by a crowd of workers. The obtained labels in this crowdsourcing setting are then aggregated for training, generally leveraging a per-worker trust score. Yet, such workers oriented approaches discard the tasks' ambiguity. Ambiguous tasks might fool ex

Jogesh Chandra Dash, Debdeep Sarkar

In this paper, we propose a closely spaced multi-antenna system with \textit{passive} self-interference cancellation (\textit{p}-SIC) of $\approx 90$ dB between the transmitter and receiver antenna for full-duplex application. The \textit{p}-SIC is achieved by field confinement near individual antennae using shorted metallic vias and the application of U-sha

Tomas Chobola, Anton Theileis, Jan Taucher, Tingying Peng

We present a model for non-blind image deconvolution that incorporates the classic iterative method into a deep learning application. Instead of using large over-parameterised generative networks to create sharp picture representations, we build our network based on the iterative Landweber deconvolution algorithm, which is integrated with trainable convoluti

Rohit Menon, Tobias Zaenker, Nils Dengler, Maren Bennewitz

Active perception for fruit mapping and harvesting is a difficult task since occlusions occur frequently and the location as well as size of fruits change over time. State-of-the-art viewpoint planning approaches utilize computationally expensive ray casting operations to find good viewpoints aiming at maximizing information gain and covering the fruits in t

Bob Oliver

For a finite abelian $p$-group $A$ and a subgroup $\Gamma\le\text{Aut}(A)$, we say that the pair $(\Gamma,A)$ is fusion realizable if there is a saturated fusion system $\mathcal{F}$ over a finite $p$-group $S\ge A$ such that $C_S(A)=A$, $\textrm{Aut}_{\mathcal{F}}(A)=\Gamma$ as subgroups of $\text{Aut}(A)$, and $A$ is not normal in $\mathcal{F}$. In this pa

Asliddin Khudoyberdiev, Zabardast Narzikulov, B. Tanatar

In this paper, we study Bose-Einstein condensation of Rydberg-dressed atoms considering finite range interactions. We use Hartree-Fock-Bogoliubov approximation based on Mean-Field approach. Moreover, within this approximation modified by the finite-range character of the two-body interaction we shall obtain analytical expressions for thermodynamic quantities

Javier Huertas-Tato, Alejandro Martin, David Camacho

Authors writing documents imprint identifying information within their texts: vocabulary, registry, punctuation, misspellings, or even emoji usage. Previous works use hand-crafted features or classification tasks to train their authorship models, leading to poor performance on out-of-domain authors. Using stylometric representations is more suitable, but thi

Amílcar Branquinho, Ana Foulquié-Moreno, Assil Fradi, Manuel Mañas

We consider matrix orthogonal polynomials related to Jacobi type matrices of weights that can be defined in terms of a given matrix Pearson equation. Stating a Riemann-Hilbert problem we can derive first and second order differential relations that these matrix orthogonal polynomials and the second kind functions associated to them verify. For the correspond

Fenglong You

Given a smooth log Calabi--Yau pair $(X,D)$, we use the intrinsic mirror symmetry construction to define the mirror proper Landau--Ginzburg potential and show that it is a generating function of two-point relative Gromov--Witten invariants of $(X,D)$. We compute certain relative invariants with several negative contact orders, and then apply the relative mir

Antoine Barrier, Aurélien Garivier, Gilles Stoltz

We lay the foundations of a non-parametric theory of best-arm identification in multi-armed bandits with a fixed budget T. We consider general, possibly non-parametric, models D for distributions over the arms; an overarching example is the model D = P(0,1) of all probability distributions over [0,1]. We propose upper bounds on the average log-probability of

Alexander Mai

We explore Arnold's $J^+$-invariant of immersions -- planar smooth closed curves with non-vanishing derivative, at most double points and only transverse intersections -- and computation methods like Viro's sum, among others. Only basic undergraduate mathematics is needed to understand the contents of this introductory paper and everything we need that is ab

Hanan Salam, Oya Celiktutan, Hatice Gunes, Mohamed Chetouani

An integral part of seamless human-human communication is engagement, the process by which two or more participants establish, maintain, and end their perceived connection. Therefore, to develop successful human-centered human-machine interaction applications, automatic engagement inference is one of the tasks required to achieve engaging interactions betwee

Luca Traini, Vittorio Cortellessa, Daniele Di Pompeo, Michele Tucci

Microbenchmarking is a widely used form of performance testing in Java software. A microbenchmark repeatedly executes a small chunk of code while collecting measurements related to its performance. Due to Java Virtual Machine optimizations, microbenchmarks are usually subject to severe performance fluctuations in the first phase of their execution (also know

Jing Liang, Li Niu, Penghao Wu, Fengjun Guo

Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another color space to magnify the domain discrepa

Juan Ungredda, Michael Pearce, Juergen Branke

Bayesian optimization is a powerful collection of methods for optimizing stochastic expensive black box functions. One key component of a Bayesian optimization algorithm is the acquisition function that determines which solution should be evaluated in every iteration. A popular and very effective choice is the Knowledge Gradient acquisition function, however

Nathan Satchell, P. Quarterman, J. A. Borchers, Gavin Burnell

Studies of ferromagnet-superconductor hybrid systems have uncovered magnetic interactions between the competing electronic orderings. The electromagnetic (EM) proximity effect predicts the formation of a spontaneous vector potential inside a superconductor placed in proximity to a ferromagnet. In this work, we use a Nb superconducting layer and Ni ferromagne

Arne N. Johanson, Andreas Oschlies, Wilhelm Hasselbring, Wilhelm Hasselbring

To successfully manage marine fisheries using an ecosystem-based approach, long-term predictions of fish stock development considering changing environmental conditions are necessary. Such predictions can be provided by end-to-end ecosystem models, which couple existing physical and biogeochemical ocean models with newly developed spatially-explicit fish sto

Yu Wang

In this paper, we exhibit a formula relating punctured Gromov-Witten invariants used by Gross and Siebert to 2-point relative/logarithmic Gromov-Witten invariants with one point-constraint for any smooth log Calabi-Yau pair $(W,D)$. Denote by $N_{a,b}$ the number of rational curves in $W$ meeting $D$ in two points, one with contact order $a$ and one with con

Christian A. Philipps, Gerhard Gompper, Roland G. Winkler

The conformational and dynamical properties of isolated flexible active polar linear polymers (APLPs) are studied analytically. The APLPs are modeled as Gaussian bead-spring linear chains augmented by tangential active forces, both in a discrete and continuous representations. The polar forces lead to linear non-Hermitian equations of motion, which are solve

Li-Shing Lin, Kento Yasuda, Kenta Ishimoto, Yuto Hosaka

Using Onsager's variational principle, we derive dynamical equations for a nonequilibrium active system with odd elasticity. The elimination of the extra variable that is coupled to the nonequilibrium driving force leads to the nonreciprocal set of equations for the material coordinates. The obtained nonreciprocal equations manifest the physical origin of th

Denis Coquenet

Handwritten text recognition has been widely studied in the last decades for its numerous applications. Nowadays, the state-of-the-art approach consists in a three-step process. The document is segmented into text lines, which are then ordered and recognized. However, this three-step approach has many drawbacks. The three steps are treated independently wher

Jean-Baptiste Casteras, Léonard Monsaingeon

In this paper we establish a rigorous gradient flow structure for one-dimensional Kimura equations with respect to some Wasserstein-Shahshahani optimal transport geometry. This is achieved by first conditioning the underlying stochastic process to non-fixation in order to get rid of singularities on the boundaries, and then studying the conditioned $Q$-proce

Katrijn Everaert, Tilmann Sander, Rainer Körber, Norbert Loewa

Many characterization techniques for magnetic nanoparticles depend on the usage of external fields. This is not the case in Thermal Noise Magnetometry (TNM), where thermal fluctuations in the magnetic signal of magnetic nanoparticle ensembles are measured without any external excitation. This can provide valuable information about the fundamental dynamical p

Marina S. Butuzova, Alexander B. Pushkarev

The magnetic field plays a significant role in the phenomenon of highly collimated jets of active galactic nuclei (AGN). Relativistic effects prevent the direct reconstruction of the magnetic field direction as transverse to electric vectors on radio maps. We determined the topology of the B-field by modeling the transverse distributions of the total and lin

Markus Kunze, Marianna Porfido, Abdelaziz Rhandi

We prove global Sobolev regularity and pointwise upper bounds for the gradient of transition densities associated with second order differential operators in $\mathbb{R}^d$ with unbounded diffusion, drift and potential terms.

Nils Berglund, Rita Nader

We consider slowly time-dependent singular stochastic partial differential equations on the two-dimensional torus, driven by weak space-time white noise, and renormalised in the Wick sense. Our main results are concentration results on sample paths near stable equilibrium branches of the equation without noise, measured in appropriate Besov and H\"older norm

Álvaro Martínez-Sánchez, Esteban López, Soledad Le Clainche, Adrián Lozano-Durán

The aim of this work is to analyse the formation mechanisms of large-scale coherent structures in the flow around a wall-mounted square cylinder, due to their impact on pollutant transport within cities. To this end, we assess causal relations between the modes of a reduced-order model obtained by applying proper-orthogonal decomposition to high-fidelity-sim

Parul Jain, Siddhi Swarupa Jena, Subhash Mahapatra

We study various holographic pure and mixed state entanglement measures in the confined/deconfined phases of a bottom-up AdS/QCD model in the presence of a background magnetic field. We analyse the entanglement entropy, entanglement wedge cross-section, mutual information, and entanglement negativity and investigate how a background magnetic field leaves its

Houling Ji, Zhaoting Geng, Weiren Cheng, Zhuoyu Yu

We present and theoretically investigate a dispersion engineered GaP-OI microresonator containing a partially-etched gap of 250 nm x 410 nm in a 600 nm x 2990 nm waveguide. This gap enables a 3.25 {\mu}m wide anomalous dispersion spectral span covering both the near-infrared and the mid-infrared spectra. This anomalous dispersion is manifested by two mechani

Nadir Matringe, Justin Trias

Let $R$ be an algebraically closed field and $\ell$ be its characteristic. Let $G$ be a locally profinite group having a compact open subgroup of invertible pro-order in $R$. Take $N$ a closed subgroup of $G$ exhausted by compact subgroups of invertible pro-orders in $R$ and fix a smooth character $\theta$ of $N$. For $\pi$ an irreducible smooth $R$-represen

Felix Kreuk, Gabriel Synnaeve, Adam Polyak, Uriel Singer

We tackle the problem of generating audio samples conditioned on descriptive text captions. In this work, we propose AaudioGen, an auto-regressive generative model that generates audio samples conditioned on text inputs. AudioGen operates on a learnt discrete audio representation. The task of text-to-audio generation poses multiple challenges. Due to the way

Xiuzhen Guo, Longfei Shangguan, Yuan He, Jia Zhang

Backscatter communication holds potential for ubiquitous and low-cost connectivity among low-power IoT devices. To avoid interference between the carrier signal and the backscatter signal, recent works propose a frequency-shifting technique to separate these two signals in the frequency domain. Such proposals, however, have to occupy the precious wireless sp

Justine Tarrant, Geoff Beck

Circumbinary accretion disks have been examined, theoretically, for supermassive and intermediate mass black holes, however, disks for black hole masses in the LIGO regime are poorly understood. Assuming these binaries possess such a disk initially, the question we want to answer is: are they dissipated by outflows or accretion prior to inspiral? To study th

Matthias Rambausek, Joachim Schöberl

The present work is concerned with the issue of spurious coupling effects that are pervasive in fully coupled magneto-mechanical finite element simulations involving very soft non-magnetic or air-like media. We first address the characterization of the spurious magneto-mechanical effects and their intuitive interpretation based on energy considerations. Then

Xiuzhen Guo, Longfei Shangguan, Yuan He, Nan Jing

The radio range of backscatter systems continues growing as new wireless communication primitives are continuously invented. Nevertheless, both the bit error rate and the packet loss rate of backscatter signals increase rapidly with the radio range, thereby necessitating the cooperation between the access point and the backscatter tags through a feedback loo

Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian

In this paper, the situation in which a receiver has to execute a task from a quantized version of the information source of interest is considered. The task is modeled by the minimization problem of a general goal function $f(x;g)$ for which the decision $x$ has to be taken from a quantized version of the parameters $g$. This problem is relevant in many app

Renaud Gueroult, Jean-Marcel Rax, Nathaniel J. Fisch

Wave propagation properties in a medium are fundamentally affected when this medium is moving instead of at rest. In isotropic dielectric media rotation has two noteworthy contributions: one is a mechanically induced circular birefringence which materialises as a rotation of the polarisation, the other is image rotation which corresponds to a rotation of the

Ariel Neufeld, Julian Sester

We present a novel $Q$-learning algorithm tailored to solve distributionally robust Markov decision problems where the corresponding ambiguity set of transition probabilities for the underlying Markov decision process is a Wasserstein ball around a (possibly estimated) reference measure. We prove convergence of the presented algorithm and provide several exa

ATLAS Collaboration

A generic search for resonances is performed with events containing a $Z$ boson with transverse momentum greater than 100 GeV, decaying into $e^+e^-$ or $\mu^+\mu^-$. The analysed data collected with the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider correspond to an integrated luminosity of 139 f

Zeinab Algadhi, Omar Mustafa

We consider non-relativistic position-dependent mass (PDM) Schrodinger particles moving in an elastic medium with space-like screw dislocation. Within the cylindrical coordinates, we study and report the effects of screw dislocation as well as PDM settings on the energy levels of some PDM-quantum mechanical systems. In so doing, we use a power-law type posit

Y. T. Liu, Y. H. Zhao, Y. Zhong, J. H. Zhang

For particles in an anharmonic potential, classical mechanics asserts that there is a renormalization of the bare frequency of the oscillatory motion, and statistical mechanics claims that the anharmonicity causes a correction to the heat capacity of an ideal gas composed of particles in the anharmonic potential. When the frequency and the heat capacity are

Shinsuke Kawai, Jinsu Kim

We study the formation of primordial black holes and the generation of gravitational waves in a class of cosmological models that are direct supersymmetric analogs of the observationally favored nonminimally coupled Higgs inflation model. It is known that this type of model naturally includes multiple scalar fields which may be regarded as the inflaton. For

Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill

Lewis signaling games are a class of simple communication games for simulating the emergence of language. In these games, two agents must agree on a communication protocol in order to solve a cooperative task. Previous work has shown that agents trained to play this game with reinforcement learning tend to develop languages that display undesirable propertie

Juan Carlos Naranjo, Irene Spelta

The aim of this paper to prove that the ramified Prym map restricted to the locus of coverings of quintic plane curves ramified in 2 points is generically injective.

Zhengyang Hu, Guanzhang Liu, Qi Xie, Jiang Xue

Channel state information (CSI) plays a critical role in achieving the potential benefits of massive multiple input multiple output (MIMO) systems. In frequency division duplex (FDD) massive MIMO systems, the base station (BS) relies on sustained and accurate CSI feedback from the users. However, due to the large number of antennas and users being served in

Enrico Ser-Giacomi, Ricardo Martinez-Garcia, Stephanie Dutkiewicz, Michael J. Follows

Marine plankton play a crucial role in carbon storage, oxygen production, global climate, and ecosystem function. Planktonic ecosystems are embedded in a Lagrangian patches of water that are continuously moving, stretching, and diluting. These processes drive inhomegeneities on a range of scales, with implications for the integrated ecosystem properties, but

Kazu Ghalamkari, Mahito Sugiyama, Yoshinobu Kawahara

We present an alternative approach to decompose non-negative tensors, called many-body approximation. Traditional decomposition methods assume low-rankness in the representation, resulting in difficulties in global optimization and target rank selection. We avoid these problems by energy-based modeling of tensors, where a tensor and its mode correspond to a

Yunxi Tang, Jiajun An, Xiangyu Chu, Shengzhi Wang

Falling cat problem is well-known where cats show their super aerial reorientation capability and can land safely. For their robotic counterparts, a similar falling quadruped robot problem, has not been fully addressed, although achieving safe landing as the cats has been increasingly investigated. Unlike imposing the burden on landing control, we approach t

Shan-Liang Zhang, Hongxi Xing, Ben-Wei Zhang

We carry out a detailed study of medium modifications on $Z^0$/$\gamma$+hadron correlations as well as jet substructures in association with $Z^0/\gamma$ in Pb+Pb collisions with $\sqrt{s_{NN}}=5.02$ TeV at the LHC. We utilize the Linear Boltzmann transport (LBT) model to simulate the jet-medium interactions and medium response, and an extended cluster hadro

Misun Min, Michael Brazell, Ananias Tomboulides, Matthew Churchfield

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer (ABL) flows that are of direct relevance to wind energy production. The first is NekRS, a high-order, unstructured-grid, spectral element code. The second, AMR-Wind, is a blo

Weiguo Wang, Xiaolong Zheng, Yuan He, Xiuzhen Guo

Cross-Technology Communication (CTC) is an emerging technology to support direct communication between wireless devices that follow different standards. In spite of the many different proposals from the community to enable CTC, the performance aspect of CTC is an equally important problem but has seldom been studied before. We find this problem is extremely

Laura Silletti, Ammar Bin Wahid, Esmerando Escoto, Prannay Balla

Post-compression methods for ultrafast laser pulses typically face challenging limitations including saturation effects and temporal pulse break-up when large compression factors and broad bandwidths are targeted. To overcome these limitations, we exploit direct dispersion control in a gas-filled multi-pass cell, enabling for the first time single-stage post

Weiguo Wang, Jinming Li, Meng Jin, Yuan He

Acoustic signal acts as an essential input to many systems. However, the pure acoustic signal is very difficult to extract, especially in noisy environments. Existing beamforming systems are able to extract the signal transmitted from certain directions. However, since microphones are centrally deployed, these systems have limited coverage and low spatial re

Guanlin Dang, Shiwei Liu, Tongbiao Guo, Junyi Duan

This paper introduces open-source computational fluid dynamics software named open computational fluid dynamic code for scientific computation with graphics processing unit (GPU) system (OpenCFD-SCU), developed by the authors for direct numerical simulation (DNS) of compressible wall-bounded turbulence. This software is based on the finite difference method

Michalis Piponidis, Panayiotis Aristodemou, Theocharis Theocharides

While Unmanned Aerial Vehicles (UAVs) are increasingly deployed in several missions, their inability of reliable and consistent autonomous landing poses a major setback for deploying such systems truly autonomously. In this paper we present an autonomous UAV landing system for landing on a moving platform. In contrast to existing attempts, the proposed syste

Robert Millar, Jinglai Li, Hui Li

In many real-world engineering systems, the performance or reliability of the system is characterised by a scalar parameter. The distribution of this performance parameter is important in many uncertainty quantification problems, ranging from risk management to utility optimisation. In practice, this distribution usually cannot be derived analytically and ha

Pavle Pandžić, Ana Prlić, Vladimír Souček, Vít Tuček

Let $G$ be a connected simply connected noncompact exceptional simple Lie group of Hermitian type. In this paper, we work with the Dirac inequality which is a very useful tool for the classification of unitary highest weight modules.

Giulia Ventagli

Although general relativity passes all precision tests to date, there are several reasons to go beyond the current model of gravitation and search for new fundamental physics. This means looking for new, so far undetected, fields. Scalars are the easiest fields to consider and they are ubiquitous in both extensions of the Standard Model and in alternative th

Weiguo Wang, Jinming Li, Yuan He, Xiuzhen Guo

More and more home appliances are now connected to the Internet, thus enabling various smart home applications. However, a critical problem that may impede the further development of smart home is overlooked: Small appliances account for the majority of home appliances, but they receive little attention and most of them are cut off from the Internet. To fill

Ziqiang Zhang, Sanyuan Chen, Long Zhou, Yu Wu

How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this paper, we propose a cross-modal Speech and Language Model (SpeechLM) to explicitly align speech and text pre-training with a pre-defined unified discrete representation. Specifical

Berivan Isik, Francesco Pase, Deniz Gunduz, Tsachy Weissman

One main challenge in federated learning is the large communication cost of exchanging weight updates from clients to the server at each round. While prior work has made great progress in compressing the weight updates through gradient compression methods, we propose a radically different approach that does not update the weights at all. Instead, our method

CALICE Collaboration

The CALICE collaboration is developing highly granular electromagnetic and hadronic calorimeters for detectors at future energy frontier electron-positron colliders. After successful tests of a physics prototype, a technological prototype of the Analog Hadron Calorimeter has been built, based on a design and construction techniques scalable to a collider det

Johannes Piotrowski, Dominik Windey, Jayadev Vijayan, Carlos Gonzalez-Ballestero

The quantum ground state of a massive mechanical system is a steppingstone for investigating macroscopic quantum states and building high fidelity sensors. With the recent achievement of ground-state cooling of a single motional mode, levitated nanoparticles have entered the quantum domain. To overcome detrimental cross-coupling and decoherence effects, quan

Weiguo Wang, Jinming Li, Yuan He, Yunhao Liu

Sound recognition is an important and popular function of smart devices. The location of sound is basic information associated with the acoustic source. Apart from sound recognition, whether the acoustic sources can be localized largely affects the capability and quality of the smart device's interactive functions. In this work, we study the problem of concu

Pavle Pandžić, Ana Prlić, Vladimír Souček, Vít Tuček

Let $G$ be a connected simply connected noncompact classical simple Lie group of Hermitian type. Then $G$ has unitary highest weight representations. The proof of the classification of unitary highest weight representations of $G$ given by Enright, Howe and Wallach is based on the Dirac inequality of Parthasarathy, Jantzen's formula and Howe's theory of dual

Rita Ramos, Bruno Martins, Desmond Elliott, Yova Kementchedjhieva

Recent advances in image captioning have focused on scaling the data and model size, substantially increasing the cost of pre-training and finetuning. As an alternative to large models, we present SmallCap, which generates a caption conditioned on an input image and related captions retrieved from a datastore. Our model is lightweight and fast to train, as t

Xin Na, Xiuzhen Guo, Yuan He, Rui Xi

iBeacon protocol is widely deployed to provide location-based services. By receiving its BLE advertisements, nearby devices can estimate the proximity to the iBeacon or calculate indoor positions. However, the open nature of these advertisements brings vulnerability to impersonation attacks. Such attacks could lead to spam, unreliable positioning, and even s

Breeshey Roskams-Hieter, Jude Wells, Sara Wade

Missing data persists as a major barrier to data analysis across numerous applications. Recently, deep generative models have been used for imputation of missing data, motivated by their ability to capture highly non-linear and complex relationships in the data. In this work, we investigate the ability of deep models, namely variational autoencoders (VAEs),

Daniel Jarne Ornia, Licio Romao, Lewis Hammond, Manuel Mazo

Policy robustness in Reinforcement Learning may not be desirable at any cost: the alterations caused by robustness requirements from otherwise optimal policies should be explainable, quantifiable and formally verifiable. In this work we study how policies can be maximally robust to arbitrary observational noise by analysing how they are altered by this noise

Vikash Pandey

Most materials exhibit creep memory under the action of a constant load. The memory behavior is governed by Andrade's creep law, which also has an inherent connection with the Omori-Utsu law of earthquake aftershocks. Both empirical laws lack a deterministic interpretation. Coincidentally, the Andrade law is similar to the time-varying part of the creep comp

Jennifer Chakravarty, Oliver Johnson, Robert Piechocki

One key metric for physical layer security is the secrecy capacity. This is the maximum rate that a system can transmit with perfect secrecy. For a Multiple Input Multiple Output (MIMO) system (a newer technology for 5G, 6G and beyond) the secrecy capacity is not fully understood. For a Gaussian MIMO channel, the secrecy capacity is a non-convex optimisation

Binyi Wu, Bernd Waschneck, Christian Georg Mayr

It has been proven that, compared to using 32-bit floating-point numbers in the training phase, Deep Convolutional Neural Networks (DCNNs) can operate with low precision during inference, thereby saving memory space and power consumption. However, quantizing networks is always accompanied by an accuracy decrease. Here, we propose a method, double-stage Squee

Giovanni Covi, Maarten de Hoop, Mikko Salo

We study an inverse problem for fractional elasticity. In analogy to the classical problem of linear elasticity, we consider the unique recovery of the Lam\'e parameters associated to a linear, isotropic fractional elasticity operator from fractional Dirichlet-to-Neumann data. In our analysis we make use of a fractional matrix Schr\"odinger equation via a ge

Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang

Retrosynthetic planning aims to devise a complete multi-step synthetic route from starting materials to a target molecule. Current strategies use a decoupled approach of single-step retrosynthesis models and search algorithms, taking only the product as the input to predict the reactants for each planning step and ignoring valuable context information along

Tae Soo Kim, Geonwoon Jang, Sanghyup Lee, Thijs Kooi

As deep networks require large amounts of accurately labeled training data, a strategy to collect sufficiently large and accurate annotations is as important as innovations in recognition methods. This is especially true for building Computer Aided Detection (CAD) systems for chest X-rays where domain expertise of radiologists is required to annotate the pre

Viktor Thorén

Spin polarization and entanglement are utilized by the BESIII experiment to learn more about the production and decay properties of hyperon-antihyperon pairs in a series of recent analyses of its unprecedented datasets at the $J/\psi$ and $\psi'$ resonances. This has lead to the observation of significant transverse polarisation in decays of $J/\psi$ or $\ps

Bing Yao, Chao Yang, Xia Liu, Fei Ma

We, for anti-quantum computing, will discuss various number-based strings, such as number-based super-strings, parameterized strings, set-based strings, graph-based strings, integer-partitioned and integer-decomposed strings, Hanzi-based strings, as well as algebraic operations based on number-based strings. Moreover, we introduce number-based string-colorin

Brahim Adnane, Younes Moqine, Abdelhadi Belouad, El Bouâzzaoui Choubabi

In this study, we use the concept of $l_1$-norm coherence to characterize the entanglement of a two--qutrit Heisenberg XXZ model for subject to a uniform magnetic field and z--axis Dzyaloshinskii--Moriya interaction with Herring-Flicker coupling. We show the temperature, magnetic field, DM interaction, and distance of Herring-Flicker coupling all can control

Antonella Castellina

The scientific achievements of the Pierre Auger Collaboration cover diverse and complementary fields of research. The search for the origin of ultra-high energy cosmic rays (UHECRs) is based on the measurement of the energy spectrum and mass composition of the primaries, on studies of multi-messengers, and on extensive anisotropy searches. With the collected

J. F. Du Plessis, W. A. Horowitz

Previously an equation of state for the relativistic hydrodynamics encountered in heavy-ion collisions at the LHC and RHIC has been calculated using lattice gauge theory methods. This leads to a prediction of very low viscosity, due to the calculated trace anomaly. Finite system corrections to this trace anomaly could challenge this calculation, since the la

Thanasis Zoumpekas, Maria Salamó, Anna Puig

Early stopping techniques can be utilized to decrease the time cost, however currently the ultimate goal of early stopping techniques is closely related to the accuracy upgrade or the ability of the neural network to generalize better on unseen data without being large or complex in structure and not directly with its efficiency. Time efficiency is a critica

Younes Moqine, Brahim Adnane, Abdelhadi Belouad, Soufiane Belhouideg

This study investigates the local quantum uncertainty (LQU) of a two--qubit Heisenberg XY chain with different directions of Dzyaloshinskii--Moriya (DM) interactions. The DM interaction parameters and coupling coefficient $J$ are demonstrated to be beneficial in managing correlation. The DM interaction's x--axis parameter has more influence on correlation th

Suhui Jeong, Pyo-Woong Son

Accurate positioning, navigation, and timing (PNT) performance are prerequisites for several technologies today. In a marine environment, it is difficult to visually identify one's position accurately, leading to safety concerns. Currently, PNT information is provided mainly from Global Navigation Satellite Systems (GNSS); however, it is vulnerable to radio

Siddhartha Banerjee, Vasilis Gkatzelis, Safwan Hossain, Billy Jin

We design online algorithms for the fair allocation of public goods to a set of $N$ agents over a sequence of $T$ rounds and focus on improving their performance using predictions. In the basic model, a public good arrives in each round, the algorithm learns every agent's value for the good, and must irrevocably decide the amount of investment in the good wi

Zhigang Su, Dawei Zhou, Nannan Wangu, Decheng Li

Growing leakage and misuse of visual information raise security and privacy concerns, which promotes the development of information protection. Existing adversarial perturbations-based methods mainly focus on the de-identification against deep learning models. However, the inherent visual information of the data has not been well protected. In this work, ins

Valerian H. Hall-Chen, Julius Damba, Felix I. Parra, Quinn T. Pratt

We use the beam model of Doppler backscattering (DBS), which was previously derived from beam tracing and the reciprocity theorem, to shed light on mismatch attenuation. This attenuation of the backscattered signal occurs when the wavevector of the probe beam's electric field is not in the plane perpendicular to the magnetic field. Correcting for this effect

Qiongqiong Pan, Jiang Zeng

Noticing that some recent variations of descent polynomials are special cases of Carlitz and Scoville's four-variable polynomials, which enumerate permutations by the parity of descent and ascent positions, we prove a $q$-analogue of Carlitz-Scoville's generating function by counting the inversion number and a type B analogue by enumerating the signed permut

Khalil Mrini, Harpreet Singh, Franck Dernoncourt, Seunghyun Yoon

Current medical question answering systems have difficulty processing long, detailed and informally worded questions submitted by patients, called Consumer Health Questions (CHQs). To address this issue, we introduce a medical question understanding and answering system with knowledge grounding and semantic self-supervision. Our system is a pipeline that fir

Thomas Bläsius, Marcus Wilhelm

A common technique to speed up shortest path queries in graphs is to use a bidirectional search, i.e., performing a forward search from the start and a backward search from the destination until a common vertex on a shortest path is found. In practice, this has a tremendous impact on the performance on some real-world networks, while it only seems to save a

Jithu Paul, Yizhar Or, Oleg Gendelman

Swimming micro-organisms such as flagellated bacteria and sperm cells have fascinating locomotion capabilities. Inspired by their natural motion, there is an ongoing effort to develop artificial robotic nano-swimmers for potential in-body biomedical applications. A leading method for actuation of nano-swimmers is by applying a time-varying external magnetic

Pacôme Delva, Zuheir Altamimi, Alejandro Blazquez, Mathis Blossfeld

Improving and homogenizing time and space reference systems on Earth and, more directly, realizing the Terrestrial Reference Frame (TRF) with an accuracy of 1mm and a long-term stability of 0.1mm/year are relevant for many scientific and societal endeavors. The knowledge of the TRF is fundamental for Earth and navigation sciences. For instance, quantifying s

Sunghun Kim, Joonho Bang, Chan-young Lim, Seung Yong Lee

Purely quantum electron systems exhibit intriguing correlated electronic phases by virtue of quantum fluctuations in addition to electron-electron interactions. To realize such quantum electron systems, a key ingredient is dense electrons decoupled from other degrees of freedom. Here, we report the discovery of a pure quantum electron liquid, which spreads u

Qiuchen Yu, Ruohua Zhou

This letter proposes a new wake word detection system based on Res2Net. As a variant of ResNet, Res2Net was first applied to objection detection. Res2Net realizes multiple feature scales by increasing possible receptive fields. This multiple scaling mechanism significantly improves the detection ability of wake words with different durations. Compared with t

Qinyu Wu, Zhenqing Jia, Wenxin Wang, Zhixing Ling

In recent years, the performance of Scientifc Complementary Metal Oxide Semiconductor (sCMOS) sensors has been improved signifcantly. Compared with CCD sensors, sCMOS sensors have various advantages, making them potentially better devices for optical and X-ray detection, especially in time-domain astronomy. After a series of tests of sCMOS sensors, we propos

Ethan Berger, Zhong-Peng Lv, Hannu-Pekka Komsa

MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via co

A. N. M. Sajedul Alam, Junaid Bin Kibria, Arnob Kumar Dey, Zawad Alam

Manual approvals are still used by banks and other NGOs to approve loans. It takes time and is prone to mistakes because it is controlled by a bank employee. Several fields of machine learning mining technologies have been utilized to enhance various areas of credit rating forecast. A major goal of this research is to look at current sentiment analysis techn

Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He

Collaborative Metric Learning (CML) has recently emerged as a popular method in recommendation systems (RS), closing the gap between metric learning and Collaborative Filtering. Following the convention of RS, existing methods exploit unique user representation in their model design. This paper focuses on a challenging scenario where a user has multiple cate

Jan Paszkiewicz, Alexej Grudiev, Walter Wuensch

A novel quantity for predicting the high-gradient performance of radio frequency accelerating structures is presented. The quantity is motivated, derived and compared with earlier high-gradient limits and experiments. This new method models a nascent RF breakdown as a current-carrying antenna and calculates the coupling of the antenna to an RF power source.

Justas Brazauskas, Matt Danish, Vadim Safronov, Rohit Verma

The report describes the digital architecture developed for the West Cambridge Digital Twin, particularly focussed on real-time sensor data collection and analysis with a privacy framework allowing occupants of the buildings to be first-class participants in the system. The implementation has some notable characteristics. In particular 'push' technology is u

Arthur C. Cardoso, Jinghan Dong, Haichen Zhou, Siddarth K. Joshi

We demonstrate a novel MIR methane sensor shifting measurement wavelength to SWIR (1.55$\mu$m) by using non-linear interferometry. The technique exploits the interference effects seen in three-wave mixing when pump, signal, and idler modes make a double pass through a nonlinear crystal. The method allows sensing at wavelengths where detectors are poor ($>$3$