66,555 research outputs found

    Terahertz-infrared spectroscopy of wafer-scale films of single-walled carbon nanotubes treated by plasma

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    Funding Information: The authors acknowledge Mogorychnaya A.V. for assistance with spectroscopic experiments. The research was supported by the Russian Science Foundation , grant RSF21-72-20050 (spectroscopic measurments and analysis of carbon nanotubes films). D.S.K. and A.G.N. acknowledge Russian Foundation of Basic Research project No. 20-03-00804 (synthesis, characterization and plasma treatment of carbon nanotubes). A.P.T. acknowledges the EDUFI Fellowship (No. TM-19-11079) from the Finnish National Agency for Education and the Magnus Ehrnrooth Foundation (the Finnish Society of Sciences and Letters ) for personal financial support. Publisher Copyright: © 2021 Elsevier LtdWe investigated terahertz-infrared electrodynamic properties of wafer-scale films composed of plasma-treated single-walled carbon nanotubes (SWCNTs) and films comprising SWCNTs grown with different lengths. The spectra of complex conductance of the films were measured at frequencies 5–20 000 cm−1 and in the temperature interval 5–300 K. Terahertz spectral response of films of pristine SWCNTs is well described with the Drude conductivity model and a plasmon resonance located at ≈100 cm−1. Stepwise treatment of the films with oxygen plasma led to a gradual suppression of the Drude spectral weight from the low-frequency side. For films with the nanotubes shorter than 1 μm, i.e., close to electrons mean free path and localization length, scattering of charge carriers at the nanotubes edges is shown to additionally contribute to the carriers scattering rate and to the damping of plasmon resonance. The temperature coefficient of ac resistance (ac TCR) in both kinds of films is found to strongly increase in amplitude during cooling and frequency decrease. The values of ac TCR increase in films with longer time of plasma treatment and nanotubes with shorter length but reach saturation in films with exposure time longer than ≈100 s or composed from SWCNTs shorter than 1 μm.Peer reviewe

    Environmental aging study on EPDM damping pads for high speed railways

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    Grado en Ingeniería en Tecnologías Industriale

    Differentially private partitioned variational inference

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    Learning a privacy-preserving model from sensitive data which are distributed across multiple devices is an increasingly important problem. The problem is often formulated in the federated learning context, with the aim of learning a single global model while keeping the data distributed. Moreover, Bayesian learning is a popular approach for modelling, since it naturally supports reliable uncertainty estimates. However, Bayesian learning is generally intractable even with centralised non-private data and so approximation techniques such as variational inference are a necessity. Variational inference has recently been extended to the non-private federated learning setting via the partitioned variational inference algorithm. For privacy protection, the current gold standard is called differential privacy. Differential privacy guarantees privacy in a strong, mathematically clearly defined sense. In this paper, we present differentially private partitioned variational inference, the first general framework for learning a variational approximation to a Bayesian posterior distribution in the federated learning setting while minimising the number of communication rounds and providing differential privacy guarantees for data subjects. We propose three alternative implementations in the general framework, one based on perturbing local optimisation runs done by individual parties, and two based on perturbing updates to the global model (one using a version of federated averaging, the second one adding virtual parties to the protocol), and compare their properties both theoretically and empirically.Comment: Published in TMLR 04/2023: https://openreview.net/forum?id=55Bcghgic

    Satellite Image Based Cross-view Localization for Autonomous Vehicle

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    Existing spatial localization techniques for autonomous vehicles mostly use a pre-built 3D-HD map, often constructed using a survey-grade 3D mapping vehicle, which is not only expensive but also laborious. This paper shows that by using an off-the-shelf high-definition satellite image as a ready-to-use map, we are able to achieve cross-view vehicle localization up to a satisfactory accuracy, providing a cheaper and more practical way for localization. While the utilization of satellite imagery for cross-view localization is an established concept, the conventional methodology focuses primarily on image retrieval. This paper introduces a novel approach to cross-view localization that departs from the conventional image retrieval method. Specifically, our method develops (1) a Geometric-align Feature Extractor (GaFE) that leverages measured 3D points to bridge the geometric gap between ground and overhead views, (2) a Pose Aware Branch (PAB) adopting a triplet loss to encourage pose-aware feature extraction, and (3) a Recursive Pose Refine Branch (RPRB) using the Levenberg-Marquardt (LM) algorithm to align the initial pose towards the true vehicle pose iteratively. Our method is validated on KITTI and Ford Multi-AV Seasonal datasets as ground view and Google Maps as the satellite view. The results demonstrate the superiority of our method in cross-view localization with median spatial and angular errors within 11 meter and 11^\circ, respectively.Comment: Accepted by ICRA202

    MAS: A versatile Landau-fluid eigenvalue code for plasma stability analysis in general geometry

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    We have developed a new global eigenvalue code, Multiscale Analysis for plasma Stabilities (MAS), for studying plasma problems with wave toroidal mode number n and frequency omega in a broad range of interest in general tokamak geometry, based on a five-field Landau-fluid description of thermal plasmas. Beyond keeping the necessary plasma fluid response, we further retain the important kinetic effects including diamagnetic drift, ion finite Larmor radius, finite parallel electric field, ion and electron Landau resonances in a self-consistent and non-perturbative manner without sacrificing the attractive efficiency in computation. The physical capabilities of the code are evaluated and examined in the aspects of both theory and simulation. In theory, the comprehensive Landau-fluid model implemented in MAS can be reduced to the well-known ideal MHD model, electrostatic ion-fluid model, and drift-kinetic model in various limits, which clearly delineates the physics validity regime. In simulation, MAS has been well benchmarked with theory and other gyrokinetic and kinetic-MHD hybrid codes in a manner of adopting the unified physical and numerical framework, which covers the kinetic Alfven wave, ion sound wave, low-n kink, high-n ion temperature gradient mode and kinetic ballooning mode. Moreover, MAS is successfully applied to model the Alfven eigenmode (AE) activities in DIII-D discharge #159243, which faithfully captures the frequency sweeping of RSAE, the tunneling damping of TAE, as well as the polarization characteristics of KBAE and BAAE being consistent with former gyrokinetic theory and simulation. With respect to the key progress contributed to the community, MAS has the advantage of combining rich physics ingredients, realistic global geometry and high computation efficiency together for plasma stability analysis in linear regime.Comment: 40 pages, 21 figure

    Vision- and tactile-based continuous multimodal intention and attention recognition for safer physical human-robot interaction

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    Employing skin-like tactile sensors on robots enhances both the safety and usability of collaborative robots by adding the capability to detect human contact. Unfortunately, simple binary tactile sensors alone cannot determine the context of the human contact -- whether it is a deliberate interaction or an unintended collision that requires safety manoeuvres. Many published methods classify discrete interactions using more advanced tactile sensors or by analysing joint torques. Instead, we propose to augment the intention recognition capabilities of simple binary tactile sensors by adding a robot-mounted camera for human posture analysis. Different interaction characteristics, including touch location, human pose, and gaze direction, are used to train a supervised machine learning algorithm to classify whether a touch is intentional or not with an F1-score of 86%. We demonstrate that multimodal intention recognition is significantly more accurate than monomodal analyses with the collaborative robot Baxter. Furthermore, our method can also continuously monitor interactions that fluidly change between intentional or unintentional by gauging the user's attention through gaze. If a user stops paying attention mid-task, the proposed intention and attention recognition algorithm can activate safety features to prevent unsafe interactions. We also employ a feature reduction technique that reduces the number of inputs to five to achieve a more generalized low-dimensional classifier. This simplification both reduces the amount of training data required and improves real-world classification accuracy. It also renders the method potentially agnostic to the robot and touch sensor architectures while achieving a high degree of task adaptability.Comment: 11 pages, 8 figures, preprint under revie

    Joint Activity Detection, Channel Estimation, and Data Decoding for Grant-free Massive Random Access

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    In the massive machine-type communication (mMTC) scenario, a large number of devices with sporadic traffic need to access the network on limited radio resources. While grant-free random access has emerged as a promising mechanism for massive access, its potential has not been fully unleashed. In particular, the common sparsity pattern in the received pilot and data signal has been ignored in most existing studies, and auxiliary information of channel decoding has not been utilized for user activity detection. This paper endeavors to develop advanced receivers in a holistic manner for joint activity detection, channel estimation, and data decoding. In particular, a turbo receiver based on the bilinear generalized approximate message passing (BiG-AMP) algorithm is developed. In this receiver, all the received symbols will be utilized to jointly estimate the channel state, user activity, and soft data symbols, which effectively exploits the common sparsity pattern. Meanwhile, the extrinsic information from the channel decoder will assist the joint channel estimation and data detection. To reduce the complexity, a low-cost side information-aided receiver is also proposed, where the channel decoder provides side information to update the estimates on whether a user is active or not. Simulation results show that the turbo receiver is able to reduce the activity detection, channel estimation, and data decoding errors effectively, while the side information-aided receiver notably outperforms the conventional method with a relatively low complexity

    The Effect of Flagella Stiffness on the Locomotion of a Multi-Flagellated Robot at Low Reynolds Environment

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    Microorganisms such as algae and bacteria move in a viscous environment with extremely low Reynolds (ReRe), where the viscous drag dominates the inertial forces. They have adapted to this environment by developing specialized features such as whole-body deformations and flexible structures such as flagella (with various shapes, sizes, and numbers) that break the symmetry during the motion. In this study, we hypothesize that the changes in the flexibility of the flagella during a cycle of movement impact locomotion dynamics of flagellated locomotion. To test our hypothesis, we developed an autonomous, self-propelled robot with four flexible, multi-segmented flagella actuated together by a single DC motor. The stiffness of the flagella during the locomotion is controlled via a cable-driven mechanism attached to the center of the robot. Experimental assessments of the robot's swimming demonstrate that increasing the flexibility of the flagella during recovery stroke and reducing the flexibility during power stroke improves the swimming performance of the robot. Our results give insight into how these microorganisms manipulate their biological features to propel themselves in low viscous media and are of great interest to biomedical and research applications

    A hybrid quantum algorithm to detect conical intersections

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    Conical intersections are topologically protected crossings between the potential energy surfaces of a molecular Hamiltonian, known to play an important role in chemical processes such as photoisomerization and non-radiative relaxation. They are characterized by a non-zero Berry phase, which is a topological invariant defined on a closed path in atomic coordinate space, taking the value π\pi when the path encircles the intersection manifold. In this work, we show that for real molecular Hamiltonians, the Berry phase can be obtained by tracing a local optimum of a variational ansatz along the chosen path and estimating the overlap between the initial and final state with a control-free Hadamard test. Moreover, by discretizing the path into NN points, we can use NN single Newton-Raphson steps to update our state non-variationally. Finally, since the Berry phase can only take two discrete values (0 or π\pi), our procedure succeeds even for a cumulative error bounded by a constant; this allows us to bound the total sampling cost and to readily verify the success of the procedure. We demonstrate numerically the application of our algorithm on small toy models of the formaldimine molecule (\ce{H2C=NH}).Comment: 15 + 10 pages, 4 figure

    Dyadic Greens function for a topological insulator stratified sphere

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    We construct the dyadic Greens functions (DGFs) for a topological insulator (TI) stratified sphere within the framework of axion electrodynamics. For these DGFs, the additional expansion coefficients are included to account for the axion coupling effect. With the application of these DGFs, we derive the formulation of light scattering from a dipole near a TI stratified sphere. In our numerical studies, we give three types of configurations (a metal-coated TI sphere, a metal-TI-metal-coated TI sphere and an alternating metal-TI stratified sphere) to investigate how the topological magneto-electric (TME) response of the TI sphere (shells) influences on the multipolar plasmonic resonance of the metal shells. For these types, the results show that the TME effect causes some modifications of the decay rate spectrum for an emitting dipole near a TI stratified sphere. For the multipolar resonances of the metal shells, it is observed that the TME-induced red-shifts for the bonding and lower order antibonding modes are found but those for the higher order antibonding modes are insignificant. In addition, for a metal-coated TI sphere, we take into account the effects of losses in the TI core of which the dielectric function is chosen to be the form of the bulk or five quintuple layers (5QL) slab and then the some modifications of the TME-induced decay rate spectrum are obviously suppressed. These phenomenological characteristics provide useful guidance to probing the TME effect via molecular fluorescence experiments
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