Activity

The proposed magnetic haptic display leads to an untethered and non-contact interface for natural haptic rendering applications, which overcomes the constraints of mechanical linkages in tool-based traditional haptic devices.Memristive technologies are attractive due to their non-volatility, high-density, low-power and compatibility with CMOS. For memristive devices, a model corresponding to practical behavioral characteristics is highly favorable for the realization of its neuromorphic system and applications. This paper presents a novel flexible memristor model with electronic resistive switching memory behavior. Firstly, the Ag-Au/MoSe2-doped Se/Au-Ag memristor is prepared using hydrothermal synthesis method and magnetron sputtering method, and its performance test is conducted on an electrochemical workstation. Then, the mathematical model and SPICE circuit model of the Ag-Au/MoSe2-doped Se/Au-Ag memristor are constructed. The model accuracy is verified by using the electrochemical data derived from the performance test. Furthermore, the proposed model is applied to the circuit implementation of spiking neural network with biological mechanism. Finally, computer simulations and analysis are carried out to verify the validity and effectiveness of the entire scheme.Despite great innovations in upper-extremity prosthetic hardware in recent decades, controlling a multiple joint upper limb prosthesis such as an elbow/wrist/hand system is still an open clinical challenge, in large part due to an insufficient number of control inputs available to users. While simultaneous control is in its early stages, the common control approach is sequential control, in which joints and grasps are driven one at a time. In this paper, we introduce and evaluate a concept we call trajectory control, that builds upon this approach, in which motions of the wrist, elbow, and shoulder DOFs (and subsets of them) are coupled into predefined sets of coordinated trajectories; to be selected by the user and driven with a single input variable. These trajectories were designed based on an earlier motion study of activities of daily life obtained from human demonstrations. We experimentally evaluate the efficacy of our approach through a human subjects study in which tasks are performed in a virtual environment. The results show that as device complexity increased (i.e. greater number of DOFs corresponding to more proximal amputations), participants were able to complete tasks faster with trajectory control while exhibiting similar levels of body compensation when compared to sequential and simultaneous control. Additionally, participants found trajectory control to be more intuitive and displayed more natural movement.Autism – also known as Autism Spectrum Disorders or Autism Spectrum Conditions – is a neurodevelopmental condition characterized by repetitive behaviours and differences in communication and social interaction. As a consequence, many autistic individuals may struggle in everyday life, which sometimes manifests in depression, unemployment, or addiction. One crucial problem in patient support and treatment is the long waiting time to diagnosis, which was approximated to thirteen months on average. Yet, the earlier an intervention can take place the better the patient can be supported, which was identified as a crucial factor. We propose a system to support the screening of Autism Spectrum Disorders based on a virtual reality social interaction, namely a shopping experience, with an embodied agent. During this everyday interaction, behavioral responses are tracked and recorded. We analyze this behavior with machine learning approaches to classify participants from an autistic participant sample in comparison to a typically developed individuals control sample with high accuracy, demonstrating the feasibility of the approach. We believe that such tools can strongly impact the way mental disorders are assessed and may help to further find objective criteria and categorization.Crepuscular rays form when light encounters an optically thick or opaque medium which masks out portions of the visible scene. Real-time applications commonly estimate this phenomena by connecting paths between light sources and the camera after a single scattering event. We provide a set of algorithms for solving integration and sampling of single-scattered collimated light in a box-shaped medium and show how they extend to multiple scattering and convex media. First, a method for exactly integrating the unoccluded single scattering in rectilinear box-shaped medium is proposed and paired with a ratio estimator and moment-based approximation. Compared to previous methods, it requires only a single sample in unoccluded areas to compute the whole integral solution and provides greater convergence in the rest of the scene. Second, we derive an importance sampling scheme accounting for the entire geometry of the medium. This sampling strategy is then incorporated in an optimized Monte Carlo integration. The resulting integration scheme yields visible noise reduction and it is directly applicable to indoor scene rendering in room-scale interactive experiences. Furthermore, it extends to multiple light sources and achieves superior converge compared to independent sampling with existing algorithms. We validate our techniques against previous methods based on ray marching and distance sampling to prove their superior noise reduction capability.Conventional solid-state reaction method is generally difficult to fabricate dense (K, Na)NbO3 (KNN) -based ceramics because of the volatilization of alkali metal ions under high processing temperature. The addition of sintering aids is an effective way to improve the compactness of KNN-based ceramics in that they can suppress the volatilization of these ions by reducing the sintering temperature. Many efforts have been made to improve the sinterability of KNN-based ceramics and realize a dense microstructure, and the well-sintered KNN-based ceramics were obtained under relatively low sintering temperature. In this mini-tutorial, the mechanism of action of the sintering aids is discussed, and the effects of various sintering aids on the sintering characteristics of KNN-based ceramics is also emphasized. In addition, we also review the influence of the sintering aids on microstructure and electrical properties. Finally, we summarize the article and offer the prospect. This paper will provide the reference for the selection of sintering aid in KNN-based ceramics.Ultrasound localization microscopy (ULM) is an emerging vascular imaging technique that overcomes the resolution-penetration compromise of ultrasound imaging. Accurate and robust microbubble (MB) localization is essential for successful ULM. In this study, we present a deep learning (DL)-based localization technique that uses both Field-II simulation and in vivo chicken embryo chorioallantoic membrane (CAM) data for training. Both radio frequency (RF) and in-phase and quadrature (IQ) data were tested in this study. The simulation experiment shows that the proposed DL-based localization was able to reduce both missing MB localization rate and MB localization error. In general, RF data showed better performance than IQ. For the in vivo CAM study with high MB concentration, DL-based localization was able to reduce the vessel MB saturation time by more than 50% compared to conventional localization. In addition, we propose a DL-based framework for real-time visualization of the high-resolution microvasculature. The findings of this article support the use of DL for more robust and faster MB localization, especially under high MB concentrations. The results indicate that further improvement could be achieved by incorporating temporal information of the MB data.Although color flow imaging is one of the representative applications of the Doppler method, it can estimate only the velocity component in the direction of ultrasonic propagation, that is, the axial velocity component. The vector Doppler method with high-frame-rate plane wave imaging overcomes such a limitation by estimating the blood flow velocity vectors using the axial velocities obtained by emitting plane waves in multiple directions. The autocorrelation technique can be used for the estimation of the axial velocity using the phase shift of an ultrasonic echo signal between two transmit-receive events. The technique also requires the frequency of the received echo signal. Although the center frequency of the emitted ultrasonic signal is commonly used in the estimation of axial velocities, the center frequency should be estimated from the received signals. In this study, a method for the estimation of the center frequency designed particularly for the high-frame-rate plane wave imaging was developed. The proposed method estimates the wavenumbers of the received signal in lateral and vertical directions to estimate the wavenumber in the axial direction, from which the center frequency was estimated. The beam steering angle was also estimated from the wavenumbers in the two directions. The effect of the proposed method was validated in simulations. The absolute bias error (ABE) and root-mean squared error in estimated velocity vectors obtained by plane wave imaging with three beam steering angles (-15°, 0°, and 15°) were reduced from 9.27% and 14.80% to 1.15% and 8.75%, respectively, by the proposed method. Floxuridine mouse The applicability of the proposed method to in vivo measurements was also demonstrated using the in vivo recordings of human common carotid arteries. Physiologically consistent blood flow velocity distributions were obtained with respect to three subjects using the proposed method.Two 5 mm by 5 mm square aluminum lenses with a 6 mm depth of focus were machined and tested for histotripsy with a 40% volume fraction 1-3 PZT-5A composite and a Meggitt Pz-39 porous ceramics lapped to 315 [Formula see text] as the piezoelectric elements. The devices were air-backed, and an 89 [Formula see text] layer of Parylene-C was deposited on the lens, matching aluminum to water. Both devices were driven single-ended at 5.8 MHz, their optimal frequency after bonding to the lens, with ten cycles at a PRF of 1 kHz. The composite-based device showed no sign of free-field cavitation in water up to a drive level of 600 V, whereas the Pz39-based device was able to cavitate in water at a drive level of 220 V. In vivo ablation of a rat brain tissue was demonstrated through an opening in the skull and required the drive voltage be increased to 280 V. The ablation was monitored using B-mode imaging with an endoscopic 30 MHz ultrasound phased array and power Doppler overlay. Ablation was maintained for 12 s and, in the power Doppler image, the ablation zone grew steadily over this time to 1.9 mm by 3.4 mm. Immediately after treatment, the ablated area appeared anechoic, slowly filling with specular material.Ultrasound super-resolution imaging through localisation and tracking of microbubbles can achieve sub-wave-diffraction resolution in mapping both micro-vascular structure and flow dynamics in deep tissue in vivo. Currently, it is still challenging to achieve high accuracy in localisation and tracking particularly with limited imaging frame rates and in the presence of high bubble concentrations. This study introduces microbubble image features into a Kalman tracking framework, and makes the framework compatible with sparsity-based deconvolution to address these key challenges. The performance of the method is evaluated on both simulations using individual bubble signals segmented from in vivo data and experiments on a mouse brain and a human lymph node. The simulation results show that the deconvolution not only significantly improves the accuracy of isolating overlapping bubbles, but also preserves some image features of the bubbles. The combination of such features with Kalman motion model can achieve a significant improvement in tracking precision at a low frame rate over that using the distance measure, while the improvement is not significant at the highest frame rate.