Advances in emerging technologies for wireless collection and the timely analysis of various information captured by wearable devices are of growing interest. Herein, a crosslinked ionic hydrogel ...prepared by a facile photocuring process is proposed, which allows wearable devices to be further incorporated into two wireless integrated systems for pressure monitoring applications. The device exhibits a simplified structure by effectively sharing functional layers, rather than conventional two separate combinations, offering the salient performance of iontronic sensing and electrochromic properties to simultaneously quantify and visualize pressure. The developed smart patch system is demonstrated to monitor physiological signals in real‐time utilizing the user interface of remote portable equipment with the Bluetooth protocol and on‐site electrochromic displays. Moreover, a passive wireless system based on the magnetic coupling effect is designed, which can operate free from the battery and simultaneously acquire multiple pressure information. It is envisioned that the strategies would hold enormous potential for flexible electronics, versatile sensing platforms, and wireless on‐body networks.
A novel photocurable hydrogel is developed to implement a two‐in‐one wearable device with a simple structure, which can quantify and visualize pressure simultaneously. Incorporated with wireless strategies, two integrated systems of smart patch and passive sensing are demonstrated, showing the potential for timely and on‐site monitoring of physiological signals, and human–machine interfaces for various pressure information acquisition.
Objective: Accelerated magnetic resonance (MR) image acquisition with compressed sensing (CS) and parallel imaging is a powerful method to reduce MR imaging scan time. However, many reconstruction ...algorithms have high computational costs. To address this, we investigate deep residual learning networks to remove aliasing artifacts from artifact corrupted images. Methods: The deep residual learning networks are composed of magnitude and phase networks that are separately trained. If both phase and magnitude information are available, the proposed algorithm can work as an iterative k-space interpolation algorithm using framelet representation. When only magnitude data are available, the proposed approach works as an image domain postprocessing algorithm. Results: Even with strong coherent aliasing artifacts, the proposed network successfully learned and removed the aliasing artifacts, whereas current parallel and CS reconstruction methods were unable to remove these artifacts. Conclusion: Comparisons using single and multiple coil acquisition show that the proposed residual network provides good reconstruction results with orders of magnitude faster computational time than existing CS methods. Significance: The proposed deep learning framework may have a great potential for accelerated MR reconstruction by generating accurate results immediately.
A mass-producible mesoporous graphene nanoball (MGB) was fabricated via a precursor-assisted chemical vapor deposition (CVD) technique for supercapacitor application. Polystyrene balls and reduced ...iron created under high temperature and a hydrogen gas environment provide a solid carbon source and a catalyst for graphene growth during the precursor-assisted CVD process, respectively. Carboxylic acid and sulfonic acid functionalization of the polystyrene ball facilitates homogeneous dispersion of the hydrophobic polymer template in the metal precursor solution, thus, resulting in a MGB with a uniform number of graphene layers. The MGB is shown to have a specific surface area of 508 m(2)/g and is mesoporous with a mean mesopore diameter of 4.27 nm. Mesopores are generated by the removal of agglomerated iron domains, permeating down through the soft polystyrene spheres and providing the surface for subsequent graphene growth during the heating process in a hydrogen environment. This technique requires only drop-casting of the precursor/polystyrene solution, allowing for mass-production of multilayer MGBs. The supercapacitor fabricated by the use of the MGB as an electrode demonstrates a specific capacitance of 206 F/g and more than 96% retention of capacitance after 10,000 cycles. The outstanding characteristics of the MGB as an electrode for supercapacitors verify the strong potential for use in energy-related areas.
In this paper, we propose a three-dimensional (3D) convolutional neural network (CNN)-based method for predicting the degree of motion sickness induced by a 360° stereoscopic video. We consider the ...user's eye movement as a new feature, in addition to the motion velocity and depth features of a video used in previous work. For this purpose, we use saliency, optical flow, and disparity maps of an input video, which represent eye movement, velocity, and depth, respectively, as the input of the 3D CNN. To train our machine-learning model, we extend the dataset established in the previous work using two data augmentation techniques: frame shifting and pixel shifting. Consequently, our model can predict the degree of motion sickness more precisely than the previous method, and the results have a more similar correlation to the distribution of ground-truth sickness.
A polarization-independent metamaterial analog of electromagnetically induced transparency (EIT) at microwave frequencies for normal incidence and linearly polarized waves is experimentally and ...numerically demonstrated. The metamaterial consists of coupled "bright" split-ring resonators (SRRs) and "dark" spiral resonators (SRs) with virtually equal resonance frequencies. Normally incident plane waves with linear polarization strongly couple to the SRR, but are weakly interacting with the SR, regardless of the polarization state. A sharp transmission peak (i.e., the transparency window) with narrow spectral width and slow wave property is observed for the metamaterial at the resonant frequency of both, the bright SRR and the dark SR. The influence of the coupling strength between the SRR and SR on the frequency, width, magnitude, and quality factor of the metamaterial's transparency window is theoretically predicted by a two-particle model, and numerically validated using full-wave electromagnetic simulation. In addition, it is numerically demonstrated that the EIT-like metamaterial can be employed as a refractive-index-based sensor with a sensitivity of 77.25 mm/RIU, which means that the resonance wavelength of the sensor shifts 77.25 mm per unit change of refractive index of the surrounding medium.
Nanostructured bismuth (Bi) nanoflakes were designed and directly grown on Cu substrate using a novel pulse electrodeposition method. Compared with conventional bismuth film grown by direct current ...electrodeposition, Bi nanoflakes have large number of edge and corner sites. As it has been proven by numerical simulation, sharp edge or corner sites of the nanostructures form strong local electric fields, which boost the catalytic activity for the electrochemical reduction of CO2 in aqueous solution. The Bi nanoflakes showed a high HCOO- faradaic efficiency (FE = 79.5%) at low potential of −0.4 VRHE and achieved a maximum FE close to 100% at −0.6 VRHE, meaning that the shape control of Bi electrocatalyst is indeed an efficient way to reduce the electrical power consumption for HCOO- production. Moreover, Bi nanoflakes were stable during 10h operation in 0.1M KHCO3 aqueous solution. The results suggest that tailoring the nanostructure is a key in developing a high performance noble-metal-free electrocatalyst for electrochemical CO2 reduction in aqueous solution.
Bismuth (Bi) nanoflakes were designed using a novel pulse electrodeposition method. Compared with conventional Bi film grown by direct electrodeposition, Bi nanoflakes have a large number of edge and corner sites, which boost the catalytic activity. The novel-metal-free Bi electrocatalyst achieved highly electrochemical CO2 reduction in aqueous solution. Display omitted
•Bismuth (Bi) nanoflakes were designed and directly grown on Cu substrate using a novel pulse-electrodeposition method.•Relationship between the shape and catalytic performance was elucidated.•Electrochemical CO2 reduction with high HCOO- production rate was achieved at low potential.
The multiple measurement vector (MMV) problem addresses the identification of unknown input vectors that share common sparse support. Even though MMV problems have been traditionally addressed within ...the context of sensor array signal processing, the recent trend is to apply compressive sensing (CS) due to its capability to estimate sparse support even with an insufficient number of snapshots, in which case classical array signal processing fails. However, CS guarantees the accurate recovery in a probabilistic manner, which often shows inferior performance in the regime where the traditional array signal processing approaches succeed. The apparent dichotomy between the probabilistic CS and deterministic sensor array signal processing has not been fully understood. The main contribution of the present article is a unified approach that revisits the link between CS and array signal processing first unveiled in the mid 1990s by Feng and Bresler. The new algorithm, which we call compressive MUSIC, identifies the parts of support using CS, after which the remaining supports are estimated using a novel generalized MUSIC criterion. Using a large system MMV model, we show that our compressive MUSIC requires a smaller number of sensor elements for accurate support recovery than the existing CS methods and that it can approach the optimal -bound with finite number of snapshots even in cases where the signals are linearly dependent.
Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilating filter-based ...low-rank Hankel matrix approach is proposed as a general framework for sparsity-driven k-space interpolation method which unifies pMRI and CS-MRI. Specifically, our framework is based on a novel observation that the transform domain sparsity in the primary space implies the low-rankness of weighted Hankel matrix in the reciprocal space. This converts pMRI and CS-MRI to a k-space interpolation problem using a structured matrix completion. Experimental results using in vivo data for single/multicoil imaging as well as dynamic imaging confirmed that the proposed method outperforms the state-of-the-art pMRI and CS-MRI.
This article presents a dual-mode power divider (PD) that offers new working mechanism, compact size, significant design freedom, wide working bandwidth, arbitrary power division, and ultrawide ...isolation between the two output ports. The structure is simple in comparison with conventional Wilkinson PDs in that only two composite right-and left-handed (CRLH) transmission lines (TLs) grounded through two resistors are used. Different from previous CRLH-TL-embedded studies in that almost all CRLH-TLs operate at quarter-wavelength phase responses, in the present work, the zero-degree property is noted and used to modify the impedance variation curves. Additionally, because of the use of grounded resistors, the proposed PD can operate in two modes, such that when high-value resistors are used, the PD operates in a lossless mode, while when low-value resistors are used, the PD operates in an attenuated mode. Because working power has been significantly improved due to progress in modern RF system development, more attenuation elements are required. This means that attenuated PDs will become very useful in the future. For verification, two PDs operating in different working modes and power divisions are designed and fabricated. Based on the experimental results, both PDs demonstrate good performance over more than 60% of the bandwidth with reference to the 15-dB <inline-formula> <tex-math notation="LaTeX">S_{11} </tex-math></inline-formula>, ultrawide isolation, full port matching, and compact size.
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