Nonlinear modeling of FES-supported standing-up in paraplegia for selection of feedback sensors

This paper presents analysis of the standing-up manoeuvre in paraplegia considering the body supportive forces as a potential feedback source in functional electrical stimulation (FES)-assisted standing-up. The analysis investigates the significance of arm, feet, and seat reaction signals to the human body center-of-mass (COM) trajectory reconstruction. The standing-up behavior of eight paraplegic subjects was analyzed, measuring the motion kinematics and reaction forces to provide the data for modeling. Two nonlinear empirical modeling methods are implemented-Gaussian process (GP) priors and multilayer perceptron artificial neural networks (ANN)-and their performance in vertical and horizontal COM component reconstruction is compared. As the input, ten sensory configurations that incorporated different number of sensors were evaluated trading off the modeling performance for variables chosen and ease-of-use in everyday application. For the purpose of evaluation, the root-mean-square difference was calculated between the model output and the kinematics-based COM trajectory. Results show that the force feedback in COM assessment in FES assisted standing-up is comparable alternative to the kinematics measurement systems. It was demonstrated that the GP provided better modeling performance, at higher computational cost. Moreover, on the basis of averaged results, the use of a sensory system incorporating a six-dimensional handle force sensor and an instrumented foot insole is recommended. The configuration is practical for realization and with the GP model achieves an average accuracy of COM estimation 16 /spl plusmn/ 1.8 mm in horizontal and 39 /spl plusmn/ 3.7 mm in vertical direction. Some other configurations analyzed in the study exhibit better modeling accuracy, but are less practical for everyday usage

Hierarchical Gaussian process mixtures for regression

As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and other fields. However, two major problems arise when the model is applied to a large data-set with repeated measurements. One stems from the systematic heterogeneity among the different replications, and the other is the requirement to invert a covariance matrix which is involved in the implementation of the model. The dimension of this matrix equals the sample size of the training data-set. In this paper, a Gaussian process mixture model for regression is proposed for dealing with the above two problems, and a hybrid Markov chain Monte Carlo (MCMC) algorithm is used for its implementation. Application to a real data-set is reported

Effects of Mn and Ti doping on superconductivity and charge ordering in NaxCoO2 system

The superconductivity in Na0.3Co1-xMxO2.1.3H2O and the charge ordering in Na0.5Co1-xMxO2 have been investigated for M = Mn and Ti substituting for Co. We have first successfully synthesized the single-phase Na0.7Co1-xMxO2(M= Mn and Ti) materials with 0 < = x < = 0.1, then we obtained Na0.5Co1-xMxO2 (0 < = x < = 0.1, M = Mn and Ti) by Na deintercalation and Na0.3Co1-xMxO2.1.3H2O (0 < = x < = 0.1, M = Mn and Ti) by an additional water intercalations. X-ray diffraction measurements revealed that all samples are single-phase materials, their lattice parameters depend systematically on the Ti and Mn contents. Measurements of physical properties indicate that the superconductivity in Na0.3Co1-xMxO2.1.3H2O is suppressed evidently by Co-site doping and killed at x = 0.02 for Mn doping and x = 0.01 for Ti doping. Charge ordering and magnetic properties in Na0.5Co1-xMxO2 were also influenced by M-atom doping.Comment: 22 pages, 3 tables, and 6 figure

Active-learning accelerated computational screening of A2B@NG catalysts for CO2 electrochemical reduction

Available online 12 July 2023Few-atom catalysts, due to the unique coordination structure compared to metal particles and single-atom catalysts, have the potential to be applied for efficient electrochemical CO2 reduction (CRR). In this study, we designed a class of triple-atom A2B catalysts, with two A metal atoms and one B metal atom either horizontally or vertically embedded in the nitrogen-doped graphene plane. Metals A and B were selected from 17 elements across 3d to 5d transition metals. The structural stability and CRR activity of the 257 constructed A2B catalysts were evaluated. The active-learning approach was applied to predict the adsorption site of key reaction intermediate *CO, which only used 40% computing resources in comparison to “brute force” calculation and greatly accelerated the large amount of computation brought by the large number of A2B catalysts. Our results reveal that these triple atom catalysts can selectively produce more valuable hydrocarbon products while preserving high reactivity. Additionally, six triple-atom catalysts were proposed as potential CRR catalysts. These findings provide a theoretical understanding of the experimentally synthesized Fe3 and Ru3-N4 catalysts and lay a foundation for future discovery of few-atom catalysts and carbon materials in other applications. A new machine learning method, masked energy model, was also proposed which outperforms existing methods by approximately 5% when predicting low-coverage adsorption sites.Xinyu Li, Haobo Li, Zhen Zhang, Javen Qinfeng Shi, Yan Jiao, Shi-Zhang Qia

Structural Phase Transitions and Sodium Ordering in Na0.5CoO2: a Combined Electron Diffraction and Raman Spectroscopy Study

The nonstoichiometric NaxCoO2 system exhibits extraordinary physical properties that correlate with temperature and Na concentration in its layered lattice without evident long-range structure modification when conventional crystallographic techniques are applied. For instance, Na0.7CoO2, a thermodynamically stable phase, shows large thermoelectric power; water-intercalated Na0.33CoO2.1.3H2O is a newly discovered superconductor with Tc ~ 4K, and Na0.5CoO2 exhibits an unexpected charge ordering transition at around Tco ~ 55 K. Recent studies suggest that the transport and magnetic properties in the NaxCoO2 system strongly depend on the charge carrier density and local structural properties. Here we report a combined variable temperature transmission electron microscopy and Raman scattering investigation on structural transformations in Na0.5CoO2 single crystals. A series of structural phase transitions in the temperature range from 80 K to 1000 K are directly identified and the observed superstructures and modulated phases can be interpreted by Na-ordering. The Raman scattering measurements reveal phase separation and a systematic evolution of active modes along with phase transitions. Our work demonstrates that the high mobility and ordering of sodium cations among the CoO2 layers are a key factor for the presence of complex structural properties in NaxCoO2 materials, and also demonstrate that the combination of electron diffraction and Raman spectroscopy measurements is an efficient way for studying the cation ordering and phase transitions in related systems.Comment: 22 pages, 5 figure

EGAM Induced by Energetic-electrons and Nonlinear Interactions among EGAM, BAEs and Tearing Modes in a Toroidal Plasma

In this letter, it is reported that the first experimental results are associated with the GAM induced by energetic electrons (eEGAM) in HL-2A Ohmic plasma. The energetic-electrons are generated by parallel electric fields during magnetic reconnection associated with tearing mode (TM). The eEGAM localizes in the core plasma, i.e. in the vicinity of q=2 surface, and is very different from one excited by the drift-wave turbulence in the edge plasma. The analysis indicated that the eEGAM is provided with the magnetic components, whose intensities depend on the poloidal angles, and its mode numbers are jm/nj=2/0. Further, there exist intense nonlinear interactions among eEGAM, BAEs and strong tearing modes (TMs). These new findings shed light on the underlying physics mechanism for the excitation of the low frequency (LF) Alfv\'enic and acoustic uctuations.Comment: 5 pages,4 figure

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP). Methods: Thirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback. Results: Adherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS. Conclusion: This study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP