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arXiv 2024年

作者： Liu, Yihao Zhang, Jiaming She, Zhangcong Kheradmand, Amir Armand, Mehran The Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States The Department of Mechanical Engineering Johns Hopkins University BaltimoreMD21218 United States The Department of Neurology Department of Neuroscience Johns Hopkins University BaltimoreMD21218 United States The Department of Mechanical Engineering Department of Computer Science Department of Orthopaedic Surgery Applied Physics Laboratory Johns Hopkins University BaltimoreMD21218 United States

Hand-eye calibration is the problem of solving the transformation from the end-effector of a robot to the sensor attached to it. Commonly employed techniques, such as AXXB or AXZB formulations, rely on regression methods that require collecting pose data from different robot configurations, which can produce low accuracy and repeatability. However, the derived transformation should solely depend on the geometry of the end-effector and the sensor attachment. We propose Geometry-Based End-Effector Calibration (GBEC) that enhances the repeatability and accuracy of the derived transformation compared to traditional hand-eye calibrations. To demonstrate improvements, we apply the approach to two different robot-assisted procedures: Transcranial Magnetic Stimulation (TMS) and femoroplasty. We also discuss the generalizability of GBEC for camera-in-hand and marker-in-hand sensor mounting methods. In the experiments, we perform GBEC between the robot end-effector and an optical tracker's rigid body marker attached to the TMS coil or femoroplasty drill guide. Previous research documents low repeatability and accuracy of the conventional methods for robot-assisted TMS hand-eye calibration. Applying GBEC to repeated calibrations, we obtain transformations with standard deviations of 0.37mm, 0.65mm, and 0.40mm (translation) along x, y, and z axes of the end-effector, respectively. The tool alignment experiments after using GBEC achieve a mean accuracy around 0.2mm in Euclidean distance. When compared to some existing methods, the proposed method relies solely on the geometry of the flange and the pose of the rigid-body marker, making it independent of workspace constraints or robot accuracy, without sacrificing the orthogonality of the rotation matrix. Our results validate the accuracy and applicability of the approach, providing a new and generalizable methodology for obtaining the transformation from the end-effector to a sensor. © 2024, CC BY-NC-ND.

关键词： Calibration

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Structural properties of hyperuniform Voronoi networks

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Physical Review E 2025年第3期111卷 034123-034123页

作者： Eli Newby Wenlong Shi Yang Jiao Reka Albert Salvatore Torquato Department of Physics Pennsylvania State University University Park Pennsylvania 16802 USA Materials Science and Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Physics Princeton University Princeton New Jersey 08544 USA Princeton Institute of Materials Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Disordered hyperuniform many-particle systems are recently discovered exotic states of matter, characterized by the complete suppression of normalized infinite-wavelength density fluctuations, as in perfect crystals, while lacking conventional long-range order, as in liquids and glasses. In this work, we begin a program to quantify the structural properties of nonhyperuniform and hyperuniform networks. In particular, large two-dimensional (2D) Voronoi networks (graphs) containing approximately 10,000 nodes are created from a variety of different point configurations, including the antihyperuniform hyperplane intersection process (HIP), nonhyperuniform Poisson process, nonhyperuniform random sequential addition (RSA) saturated packing, and both non-stealthy and stealthy hyperuniform point processes. We carry out an extensive study of the Voronoi-cell area distribution of each of the networks by determining multiple metrics that characterize the distribution, including their average areas and corresponding variances as well as higher-order cumulants (i.e., skewness γ1 and excess kurtosis γ2). We show that the HIP distribution is far from Gaussian, as evidenced by a high skewness (γ1=3.16) and large positive excess kurtosis (γ2=16.2). The Poisson (with γ1=1.07 and γ2=1.79) and non-stealthy hyperuniform (with γ1=0.257 and γ2=0.0217) distributions are Gaussian-like distributions, since they exhibit a small but positive skewness and excess kurtosis. The RSA (with γ1=0.450 and γ2=−0.0384) and the highest stealthy hyperuniform distributions (with γ1=0.0272 and γ2=−0.0626) are also non-Gaussian because of their low skewness and negative excess kurtosis, which is diametrically opposite of the non-Gaussian behavior of the HIP. The fact that the cell-area distributions of large, finite-sized RSA and stealthy hyperuniform networks (e.g., with N≈10,000 nodes) are narrower, have larger peaks, and smaller tails than a Gaussian distribution implies that in the thermodynamic limit th

关键词： Gaussian distribution

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Evaluation of the Performance of Wearables’ Inertial Sensors for the Diagnosis of Resting Tremor in Parkinson’s Disease

Evaluation of the Performance of Wearables’ Inertial Sensor...

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17th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2024

作者： Polvorinos-Fernández, Carlos Sigcha, Luis de Pablo, Laura Pereira Borzí, Luigi Cardoso, Paulo Costa, Nelson Costa, Susana López, Juan Manuel de Arcas, Guillermo Pavón, Ignacio Mechanical Engineering Department ETSI Industriales Universidad Politécnica de Madrid Spain Group University of Limerick LimerickV94 T9PX Ireland ALGORITMI Research Center School of Engineering University of Minho Guimarães Portugal PolitoBIOMed Lab–Biomedical Engineering Lab Politecnico di Torino Turin10129 Italy ANTHEA Lab–Data Analytics and Technologies for Health Lab Department of Control and Computer Engineering Politecnico di Torino Turin10129 Italy Physical Electronics Electrical Engineering and Applied Physics Department ETS de Ingeniería y Sistemas de Telecomunicación Universidad Politécnica de Madrid Spain

Currently, objective monitoring of resting tremor in Parkinson’s disease (PD) involves wearable devices and machine learning. Smartwatches may present an affordable method for remote and unintrusive tremor monitoring. However, the development of optimized systems is necessary to perform accurate monitoring in free-living settings. In this study, the potential of inertial sensors to detect resting tremors is evaluated. A smartwatch was placed on the wrist of six subjects with PD during the execution of MDS-UPDRS motor tasks. Data were collected over eight weeks from triaxial accelerometer and gyroscope simultaneously and used to implement machine learning algorithms to detect resting tremor. The best performance (accuracy 97.0% in tremor detection) was achieved using accelerometer data analysed with a Random Forest classifier, while the gyroscope showed lower performance (93.0%). The results indicates that the use of the accelerometer in commercial smartwatches can offer effective results for detecting resting tremors, while reducing computational workload. These results show opportunities for the development of robust free-living tremor monitoring systems using commodity devices and algorithms using a single sensor. © 2024 by SCITEPRESS–Science and Technology Publications, Lda.

关键词： Gyroscopes

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Longitudinal, Multimodal Tracking Reveals Lasting Neurovascular Impact of Individual Microinfarcts

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Advanced Science 2025年第0期12卷 e2417003页

作者： Jin, Yifu He, Fei Rathore, Haad Sun, Yingchu Zhang, Jia-ao Li, Xinyu Yin, Rongkang Zhu, Hanlin Xie, Chong Luan, Lan Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Neuroengineering Initiative Rice University HoustonTX77005 United States Applied Physics Program Rice University HoustonTX77005 United States Department of Bioengineering Rice University HoustonTX77005 United States

Microinfarcts, the "invisible lesions", are prevalent in aged and injured brains and associated with cognitive impairments, yet their neurophysiological impact remains largely unknown. Using a multimodal chronic neural platform that combines functional microvasculature imaging with spatially resolved neural recording, the neurovascular effect of a single microinfarct is investigated. Unlike larger strokes, microinfarcts induced only temporary suppression of neural activity with minimal cell death, with recovery paralleling vasculature remodeling at the infarct core. Neural activity is more severely suppressed at the shallower cortical layer despite milder vascular damage compared to deeper layers, and the excitability of fast-spiking interneurons attenuation is accompanied by heightened bursting of regular spiking neurons. Spike phase locking at the low-gamma band is disrupted, indicating a lasting impairment of long-range assembly communication. These results highlight the subtle yet significant neurovascular disruptions of a single microinfarct. © 2025 The Author(s). Advanced Science published by Wiley-VCH GmbH.

关键词： Flexible electronics

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Following marginal stability manifolds in quasilinear dynamical reductions of multiscale flows in two space dimensions

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Physical Review E 2025年第2期111卷 025105-025105页

作者： Alessia Ferraro Gregory P. Chini T. M. Schneider Emergent Complexity in Physical Systems Laboratory (ECPS) École Polytechnique Fédérale de Lausanne CH-1015 Lausanne Switzerland Nordita Royal Institute of Technology and Stockholm University Stockholm 106 91 Sweden Department of Mechanical Engineering and Program in Integrated Applied Mathematics University of New Hampshire Durham New Hampshire 03824 USA

We derive a two-dimensional (2D) extension of a recently developed formalism for slow-fast quasilinear (QL) systems subject to fast instabilities. The emergent dynamics of these systems is characterized by a slow evolution of (suitably defined) mean fields coupled to marginally stable, fast fluctuation fields. By exploiting this scale separation, an efficient hybrid fast-eigenvalue/slow-initial-value solution algorithm can be developed in which the amplitude of the fast fluctuations is slaved to the slowly evolving mean fields to ensure marginal stability—and temporal scale separation—is maintained. For 2D systems, the fluctuation eigenfunctions are labeled by their Fourier wave numbers characterizing spatial variability in that extended spatial direction, and the marginal mode(s) must coincide with the fastest-growing mode(s) over all admissible Fourier wave numbers. Here we derive an ordinary differential equation governing the slow evolution of the wave number of the fastest-growing fluctuation mode that simultaneously must be slaved to the mean dynamics to ensure the mode has zero growth rate. We illustrate the procedure in the context of a 2D model partial differential equation that shares certain attributes with the equations governing strongly stratified shear flows and other strongly constrained forms of geophysical turbulence in extreme parameter regimes. The slaved evolution follows one or more marginal stability manifolds, which constitute select state-space structures that are not invariant under the full flow dynamics yet capture quasicoherent structures in physical space in a manner analogous to invariant solutions identified in, e.g., transitionally turbulent shear flows. Accordingly, we propose that marginal stability manifolds are central organizing structures in a dynamical systems description of certain classes of multiscale flows in which scale separation justifies a QL approximation of the dynamics.

关键词： Shear flow

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Mechanism of skyrmion condensation and pairing for twisted bilayer graphene

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Physical Review B 2022年第18期105卷 184505-184505页

作者： Dian Jing Alexander Conkey Tyner Pallab Goswami Department of Physics and Astronomy Northwestern University Evanston Illinois 60208 USA Department of Chemical and Biological Engineering Northwestern University Evanston Illinois 60208 USA Integrated Science Program Northwestern University Evanston Illinois 60208 USA Graduate Program in Applied Physics Northwestern University Evanston Illinois 60208 USA

When quantum flavor Hall insulator phases of itinerant fermions are disordered by strong quantum fluctuations, the condensation of skyrmion textures of order parameter fields can lead to superconductivity. In this work, we address the mechanism of skyrmion condensation by considering the scattering between (2+1)-dimensional Weyl fermions and hedgehog-type tunneling configurations of order parameters that violate the skyrmion-number conservation law. We show the quantized, flavor Hall conductivity (σxyf) controls the degeneracy of topologically protected, fermion zero-modes, localized on hedgehogs. The overlap between zero-mode eigenfunctions or 't Hooft vertex is shown to control the nature of the paired states. Employing this formalism for the N=2 model of twisted bilayer graphene, we describe the competition among flavor Hall orders, charge 4e− superconductivity, and various charge 2e− paired states in BCS and paired-density-wave channels. At charge neutrality, we show that the competition between flavor Hall insulators and charge 2e− states can be captured by SO(9) nonlinear sigma models. If the topological pairing mechanism can dominate over the conventional pairing mechanism, our work predicts the flavor-symmetry-preserving charge 4e− superconductivity as a natural candidate for the paired state in the vicinity of the charge neutral point.

关键词： FFLO Multiband superconductivity Pairing mechanisms Superconducting order parameter Superconductivity Topological insulators Topological phase transition Topological phases of matter Topological superconductors

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NOMAD: Nonlinear Manifold Decoders for Operator Learning

arXiv

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arXiv 2022年

作者： Seidman, Jacob H. Kissas, Georgios Perdikaris, Paris Pappas, George J. Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania United States Department of Electrical and Systems Engineering University of Pennsylvania United States

Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By directly learning maps (operators) between infinite dimensional function spaces, these models are able to learn discretization invariant representations of target functions. A common approach is to represent such target functions as linear combinations of basis elements learned from data. However, there are simple scenarios where, even though the target functions form a low dimensional submanifold, a very large number of basis elements is needed for an accurate linear representation. Here we present NOMAD, a novel operator learning framework with a nonlinear decoder map capable of learning finite dimensional representations of nonlinear submanifolds in function spaces. We show this method is able to accurately learn low dimensional representations of solution manifolds to partial differential equations while outperforming linear models of larger size. Additionally, we compare to state-of-the-art operator learning methods on a complex fluid dynamics benchmark and achieve competitive performance with a significantly smaller model size and training cost. © 2022, CC BY-NC-SA.

关键词： Benchmarking

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Computational analysis of Newtonian fluid in a 2-D square cavity with kinetic energy, enstrophy, and palinstrophy in the presence of bottom corner obstacle

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Results in physics 2025年 68卷

作者： Kumar, Dalmalka Praveen Rameshwar, Yadagiri Ali, Rifaqat Nazari, S. Kallel, Mohamed Galal, Ahmed M. Department of Mathematics University College of Science Osmania University Hyderabad 500007 India Department of Mathematics Applied College in Mohayil Asir King Khalid University Abha Saudi Arabia Researcher in Energy and Mechanical Engineering Iran Department of Physics College of Science Northern Border University Arar Saudi Arabia Department of Mechanical Engineering College of Engineering in Wadi Alddawasir Prince Sattam bin Abdulaziz University Saudi Arabia Production Engineering and Mechanical Design Department Faculty of Engineering Mansoura University Mansoura P.O 35516 Egypt

Understanding the impact of obstacles on lid-driven cavity (LDC) flows is critical for advancing flow control and optimization in fluid dynamics. In this study, we numerically investigate steady, two-dimensional Newtonian fluid flow within a square cavity featuring a lid-driven motion at Reynolds number Re = 100 by solving governing equations with the Fractional Step Method on a staggered grid in the Finite Volume framework, providing high-resolution streamline plots and vorticity contours. A rectangular obstacle with a fixed width (W = 0.2L) and varying heights (H = 0.20L,0.25L,0.50L,0.60L,0.80L and 0.95L) is systematically placed in three configurations: 1) bottom left-corner, 2) bottom right-corner and 3) both bottom (left–right) corners. The study investigates the influence of obstacle placement and height on kinetic energy (KE), enstrophy (Z), and palinstrophy (P) as well as obstacles focusing on the modulation of primary (PV) and secondary (SV) vortices, energy metrics, and flow topology in lid-driven cavity (LDC) flows, focusing on configurations with single and double corner. Fluid motion control in constrained environments, such as industrial mixing where vortex dynamics in lid-driven cavities optimize mixing and reduce dead zones by adjusting obstacle configurations and heat transfer, demands a detailed understanding of energy dissipation and rotational dynamics. The physics involved in KE and vortex dynamics is that increasing obstacle height progressively reduces the kinetic energy across all configurations, with the sharpest decline (38 %) observed in dual-corner obstacles due to amplified flow constriction and enhanced boundary layer effects. Single-corner obstacles disrupt the flow asymmetrically, whereas dual-corner setups create balanced but more confined vortex structures, impacting energy distribution and flow control. In rotational energy (Z) and gradient intensities (P), dual-corner obstacles induce the highest rotational energy (192 % increase

关键词： Enstrophy Lid-driven cavity Obstacle Palinstrophy Total kinetic energy Vortices’ area development

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Hydrogen Powered Fuel Cell Systems - A Review

Hydrogen Powered Fuel Cell Systems - A Review

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IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Sunday A. Afolalu Temitayo S. Ogedengbe Moses E. Emetere Stella I. Monye Monye N. Snow Dept. of Mechanical and Mechatronics Engineering Department Afe Babalola University Ado-Ekiti Nigeria Dept. of Mechanical Science University Johannesburg South Africa Dept. of Mechanical Engineering Department Nile University of Nigeria Abuja Dept. of Physics Program. Bowen University Iwo Osun State Nigeria Dept. of Information Communication Technology University of Delta Agbor Delta State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

The urgent need for sustainable energy sources has fuelled research into alternative power generation technologies. Among these, hydrogen fuel cells have emerged as promising candidates due to their high energy efficiency and zero-emission profile. This study presents a review on hydrogen energy and fuel cell. The design principles for fuel cells, hydrogen production methods, hydrogen storage technologies and the integration of fuel cells into power systems have been discussed. The review concludes with a discussion on technological advances in fuel cell materials and environmental impacts/sustainability of hydrogen fuel cells.

关键词： Renewable energy sources Humanities Hydrogen storage Reviews Hydrogen Fuel cells Production Power systems Sustainable development Power generation

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Design of Two-Dimensional Phosphorus-Doped Polymeric Graphitic Carbon Nitride Fluorescent Probe for the Highly Sensitive Picomolar Detection of Nitrofurazone in Biological Fluids and Environmental Samples

SSRN

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SSRN 2025年

作者： Sasikumar, G. Kausalya Shenthilkumar, R.R. Balla, Putra Kumar Kumar, E. Ranjith Indian Institute of Chemical Technology India Department of Mechanical Engineering Centre for Research and Development KPR Institute of Engineering and Technology Tamil Nadu Coimbatore641407 India Catalyst & Catalytic Reaction Engineering Laboratory Department of Chemical Engineering and Applied Chemistry Chungnam National University Daejeon34134 Korea Republic of Departments of Physics KPR Institute of Engineering and Technology Tamil Nadu Coimbatore641407 India

The escalating use of antibiotics poses significant risks to both human health and the environment. Consequently, methods for the detection of antibiotics must exhibit high selectivity and sensitivity. Our newly developed two-dimensional polymeric graphitic carbon nitride (g-CN) fluorescence sensor demonstrated remarkable specificity and responsiveness for identifying nitrofuran antibiotics. P-g-CN is produced through the thermal polymerisation of g-CN incorporating phosphorus heteroatoms with a high electron density. Both the g-CN and P-g-CN compounds were subjected to spectroscopic and microscopic analyses for a comprehensive characterisation. HRTEM images of P-g-CN revealed nanobelts for detection and biological research purposes. Among the antibiotics tested, NFZ demonstrated the highest fluorescence quenching efficiency of 77.65% for this particular probe. Our study included all nitrofuran-based antibiotics. The fluorescence sensor probe consisting of P-g-CN NBs exhibited quenching as the concentration of NFZ was increased at ambient temperature. This probe demonstrated high sensitivity and specificity in detecting and measuring NFZ antibiotics, with detection limits of 4.34 and 14.46 pM within a concentration range of 10 to 100 pM. Upon addition of NFZ, the quantum yield (QY) of P-g-CN decreased from 19% to 15%. To examine the fluorescence quenching process of the P-g-CN NBs, we employed NFZ, which enabled us to acquire time-resolved decay spectra. In ambient and biological samples, the sensor probe retrieved 94–112% of NFZ. This sensitive P-g-CN NB-based sensor probe for nitrofuran antibiotic detection may help fight antibiotic resistance and improve public health. © 2025, The Authors. All rights reserved.

关键词： Fluorescence quenching

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