Mimicking human skin sensation such as spontaneous multimodal perception and identification/discrimination of intermixed stimuli is severely hindered by the difficulty of efficient integration of ...complex cutaneous receptor‐emulating circuitry and the lack of an appropriate protocol to discern the intermixed signals. Here, a highly stretchable cross‐reactive sensor matrix is demonstrated, which can detect, classify, and discriminate various intermixed tactile and thermal stimuli using a machine‐learning approach. Particularly, the multimodal perception ability is achieved by utilizing a learning algorithm based on the bag‐of‐words (BoW) model, where, by learning and recognizing the stimulus‐dependent 2D output image patterns, the discrimination of each stimulus in various multimodal stimuli environments is possible. In addition, the single sensor device integrated in the cross‐reactive sensor matrix exhibits multimodal detection of strain, flexion, pressure, and temperature. It is hoped that his proof‐of‐concept device with machine‐learning‐based approach will provide a versatile route to simplify the electronic skin systems with reduced architecture complexity and adaptability to various environments beyond the limitation of conventional “lock and key” approaches.
A highly stretchable cross‐reactive sensor matrix for electronic‐skin applications is demonstrated, which can detect, classify, and discriminate various intermixed tactile and thermal stimuli based on machine learning. By adopting a learning algorithm based on the bag‐of‐words model, highly accurate classification of intermixed stimuli is achieved.
Mechanically stretchable strain sensors gain tremendous attention for bioinspired skin sensation systems and artificially intelligent tactile sensors. However, high‐accuracy detection of both strain ...intensity and direction with simple device/array structures is still insufficient. To overcome this limitation, an omnidirectional strain perception platform utilizing a stretchable strain sensor array with triangular‐sensor‐assembly (three sensors tilted by 45°) coupled with machine learning (ML) ‐based neural network classification algorithm, is proposed. The strain sensor, which is constructed with strain‐insensitive electrode regions and strain‐sensitive channel region, can minimize the undesirable electrical intrusion from the electrodes by strain, leading to a heterogeneous surface structure for more reliable strain sensing characteristics. The strain sensor exhibits decent sensitivity with gauge factor (GF) of ≈8, a moderate sensing range (≈0–35%), and relatively good reliability (3000 stretching cycles). More importantly, by employing a multiclass–multioutput behavior‐learned cognition algorithm, the stretchable sensor array with triangular‐sensor‐assembly exhibits highly accurate recognition of both direction and intensity of an arbitrary strain by interpretating the correlated signals from the three‐unit sensors. The omnidirectional strain perception platform with its neural network algorithm exhibits overall strain intensity and direction accuracy around 98% ± 2% over a strain range of ≈0–30% in various surface stimuli environments.
An omnidirectional strain sensor array for electronic skin applications, which can detect and predict both the 360° direction and strain intensity based on machine learning, is demonstrated. By adopting a learning algorithm based on the multiclass–multioutput model, highly accurate prediction of strain information is achieved.
In this paper, we propose the concept and design methodology for a resonant reactive shield for the reduction of magnetic field leakage from a wireless power transfer (WPT) systems. By using LC ...resonance, the reactive shield can generate a cancelling magnetic field to reduce the incident magnetic field from WPT coils and effectively reduce the total magnetic field without consuming additional power. The shielding effectiveness of the resonant reactive shield and its effect on WPT efficiency are analyzed with simulation and measurements. For practical application to wirelessly charged electric vehicles, an automatic tuning system for the resonant reactive shield is also proposed and implemented. The effectiveness of a resonant reactive shielding is verified by experiments in a wirelessly charged electric bus.
The assembly of death-inducing signaling complex (DISC) for activation of initiator caspase is a key step for the receptor-mediated apoptosis signaling. Many death effector domain (DED)-containing ...proteins are involved in DISC assembly and controlling. One of the main DISC component, caspase-8, contains DED and DED-mediated dimerization and oligomerization in the DISC is critical for the activation of this initiator caspase. There have been intensive studies to understand DED-mediated dimerization and oligomerization for the DISC assembly but no clear answer has been provided and there are many controversial arguments. Here, we suggested novel dimerization process of tandem DED of caspase-8 with crystallographic study.
This article analyzes a near-field shielding performance of conformal shielding materials for integrated-circuits (ICs) by experiments. Two test boards with loop-type and patch-type patterns are ...designed to generate magnetic-field and electric-field, respectively. These sources mimic typical electromagnetic radiations from actual ICs. For shielding analysis, single-layered conductive materials, multilayered conductive and magnetic materials, hybrid materials with a mixture of conductive and magnetic pastes are considered as conformal shielding materials, which are coated on the test boards for measurements. Magnetic-field and electric-field shielding effectiveness (SE) of the materials evaluate by measurements using loop-probe, strip-line, and gigahertz transverse electromagnetic cell at the frequency range from 300 kHz to 3 GHz. Near-field SEs measured by three methods correspond generally well with each other at the frequency range up to a few hundred MHz. At the higher frequency, the ambient EM environment can affect the accuracy of the near-field measurements by the loop-probe and strip-line. For validation, numerical simulation is fulfilled and compared with measured results. Theoretical interpretation based on the Schelkunoff's SE decomposition is also addressed.
Silicon-carbon nanocomposite materials are widely adopted in the anode of lithium-ion batteries (LIB). However, the lithium ion (Li+) transportation is hampered due to the significant accumulation of ...silicon nanoparticles (Si) and the change in their volume, which leads to decreased battery performance. In an attempt to optimize the electrode structure, we report on a self-assembly synthesis of silicon nanoparticles@nitrogen-doped reduced graphene oxide/carbon nanofiber (Si@N-doped rGO/CNF) composites as potential high-performance anodes for LIB through electrostatic attraction. A large number of vacancies or defects on the graphite plane are generated by N atoms, thus providing transmission channels for Li+ and improving the conductivity of the electrode. CNF can maintain the stability of the electrode structure and prevent Si from falling off the electrode. The three-dimensional composite structure of Si, N-doped rGO, and CNF can effectively buffer the volume changes of Si, form a stable solid electrolyte interface (SEI), and shorten the transmission distance of Li+ and the electrons, while also providing high conductivity and mechanical stability to the electrode. The Si@N-doped rGO/CNF electrode outperforms the Si@N-doped rGO and Si/rGO/CNF electrodes in cycle performance and rate capability, with a reversible specific capacity reaching 1276.8 mAh/g after 100 cycles and a Coulomb efficiency of 99%.
Multispectral satellite imaging sensors acquire various spectral band images and have a unique spectroscopic property in each band. Unfortunately, image artifacts from imaging sensor noise often ...affect the quality of scenes and have a negative impact on applications for satellite imagery. Recently, deep learning approaches have been extensively explored to remove noise in satellite imagery. Most deep learning denoising methods, however, follow a supervised learning scheme, which requires matched noisy image and clean image pairs that are difficult to collect in real situations. In this article, we propose a novel unsupervised multispectral denoising method for satellite imagery using a wavelet directional cycle-consistent adversarial network (WavCycleGAN). The proposed method is based on an unsupervised learning scheme using adversarial loss and cycle-consistency loss to overcome the lack of paired data. Moreover, in contrast to the standard image-domain cycleGAN, we introduce a wavelet directional learning scheme for effective denoising without sacrificing high-frequency components such as edges and detailed information. Experimental results for the removal of vertical stripes and wave noise in satellite imaging sensors demonstrate that the proposed method effectively removes noise and preserves important high-frequency features of satellite images.
In this article, analytic models are proposed for electromagnetic shielding analysis of planar materials using the ASTM D4935 standard fixture typically employed to measure far-field shielding ...effectiveness (SE). The fixture with an inserted planar material is divided into two coaxial line sections and one material section that are modeled as lossless and lossy transmission lines (TLs), respectively. Using the ABCD parameters of TLs, the far-field SEs of planar materials are analytically derived and calculated. In order to analyze the case where the conductive materials are coated on insulating substrates, contact impedances are considered at the inner and outer conductors of the flanged coaxial fixture. The proposed high-frequency model can accurately predict the absorption loss especially in the high-frequency where the skin depth of the material becomes smaller than its thickness. Low-frequency and lumped models are also derived by approximation of the high-frequency model. In addition, correction factors are introduced to remove the SE error in the low-frequency range due to the attached insulating substrates of the conducting materials. For verification, the proposed models are compared with the theoretical plane-wave SE and the measurement results presented in other literatures. They show a good agreement with each other. Lastly, an influence of the errors in the thicknesses and electrical parameters of actual materials on the analytic SE models is analyzed.
In this progress report, recent advances in the development of organic transistors with superior bias stress stability and in the understanding of the charge traps that degrade device performance ...under prolonged bias stress are reviewed, with a particular focus on materials science and engineering methods. The phenomenological aspects of bias stress effects and the experimental methods for investigating charge traps are described. The recent progress in the bias stress stability of organic transistors is discussed in terms of those components that are the main focus of attempts to improve bias stress stability, i.e., organic semiconductor layers, gate dielectrics, and source/drain contacts. A brief summary of this progress is presented and the outlook for future research in this field is assessed. This report aims to summarize recent progress in this field and to provide some guidelines for studying bias stress–induced charge‐trapping phenomena.
Charge trapping degrades the electrical performance of organic field‐effect transistors under prolonged gate‐bias stress. This bias stress instability can be understood deeply by studying charge traps inside the device. In this aspect, this report shows the recent progress in the bias stress stability of organic transistors and offers readers with guidelines to study the bias stress–induced charge traps, including theoretical analysis and quantification methods.
Epidemiological studies have indicated that regular intake of polyphenol-rich diets such as red wine and tea, are associated with a reduced risk of cardiovascular diseases. The beneficial effect of ...polyphenol-rich products has been attributable, at least in part, to their direct action on the endothelial function. Indeed, polyphenols from tea, grapes, cacao, berries, and plants have been shown to activate endothelial cells to increase the formation of potent vasoprotective factors including nitric oxide (NO) and to delay endothelial ageing. Moreover, intake of such polyphenol-rich products has been associated with the prevention and/or the improvement of an established endothelial dysfunction in several experimental models of cardiovascular diseases and in Humans with cardiovascular diseases. This review will discuss both experimental and clinical evidences indicating that polyphenols are able to promote endothelial and vascular health, as well as the underlying mechanisms.
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•Several polyphenol-rich diets reduce the risk of cardiovascular diseases.•Polyphenols can induce the endothelial formation of potent vasoprotective factors.•Polyphenols can prevent premature endothelial senescence and delay vascular ageing.•Polyphenols can prevent and/or improve established endothelial dysfunction.
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