The speed of calculating, tracking and filling the isolines has a direct impact on the performance of user interaction. In this paper, we begin with the serial algorithm of visualization and implement its parallel algorithm. First, we divide the Delaunay grids generated from the PEBI grids into several regions. Calculation, tracking of isolines and calculation of saturation are implemented in each region respectively. Then the tracking results of each region are integrated for the entire work area. The parallel examples using OpenMP on computers with dual-core/quad-core are given at the end of this paper. The experimental results show that the parallel processing can greatly reduce the time required for data processing in visualization.
Periprosthetic osteolysis (PPO) triggered by wear particles is the most severe complication of total joint replacement (TJR) surgeries, representing the major cause of implant failure, which is public health concern worldwide. Previous studies have confirmed the specialized role of osteoclast-induced progressive bone destruction in the progression of PPO. Additionally, the reactive oxygen species (ROS) induced by wear particles can promote excessive osteoclastogenesis and bone resorption. Nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4), a cellular enzyme, is considered to be responsible for the production of ROS and the formation of mature osteoclasts. However, NOX4 involvement in PPO has not yet been elucidated. Therefore, we investigated the mechanism by which NOX4 regulates osteoclast differentiation and the therapeutic effects on titanium nanoparticle-induced bone destruction. We found that NOX4 blockade suppressed osteoclastogenesis and enhanced the scavenging of intracellular ROS. Our rescue experiment revealed that nuclear factor-erythroid 2-related factor 2 (Nrf2) silencing reversed the effects of NOX4 blockade on ROS production and osteoclast differentiation. In addition, we found increased expression levels of NOX4 in PPO tissues, while NOX4 inhibition in vivo exerted protective effects on titanium nanoparticle-induced osteolysis through antiosteoclastic and antioxidant effects. Collectively, these findings suggested that NOX4 blockade suppresses titanium nanoparticle-induced bone destruction via activation of the Nrf2 signaling pathway and that NOX4 blockade may be an attractive therapeutic approach for preventing PPO.
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An ultra-high vacuum (UHV) compatible electron spectrometer employing a double toroidal analyzer has been developed. It is designed to be combined with a custom-made scanning tunneling microscope (STM) to study the spatially localized electron energy spectrum on a surface. A tip—sample system composed of a piezo-driven field-emission tungsten tip and a sample of highly ordered pyrolytic graphite (HOPG) is employed to test the performance of the spectrometer. Two-dimensional images of the energy-resolved and angle-dispersed electrons backscattered from the surface of HOPG are obtained, the performance is optimized and the spectrometer is calibrated. A complete electron energy loss spectrum covering the elastic peak to the secondary electron peaks for the HOPG surface, acquired at a tip voltage of −140 V and a sample current of 0.5 pA, is presented, demonstrating the viability of the spectrometer.
A simulation methodology to correlate process variations to the soft yield of 6-T FinFET SRAM cells is demonstrated. By using the TCAD tool which is calibrated to the recently published 25nm FinFET technology, process impacts on the device electrical characteristics are simulated and stored in behavioral models. Circuit simulations can then be carried out to calculate the read/write noise margin. Employing the linear function approximation of the noise margin with respect to the six individual process variation parameters in sigma, one can analytically solve the yield when noise margin drops to zero. The calculation results show that instead of Vt variation, parasitic resistance fluctuation dominates fails at high bias voltages. A simple design optimization guideline is also demonstrated to reduce Vmin of the given technology (to 0.5V in this work). This methodology can serve as useful guidelines for both process development and device design.
Abstract Although temperature modulation of a single (nonselective) semiconductor gas sensor has demonstrated its great capability on discriminating gas molecules, quantitative analysis of the type and concentration of structurally similar volatile organic compounds (VOCs) molecules remains a significant challenge. In this work, as an alternative to a single oxide sensor, sensor arrays composed of four types of NiO‐based sensor synchronously perform thermal modulation with a unique programmed cooling temperature profile. Apart from improved category discrimination by using entire sensor arrays, the peak temperature of the temperature profile plays an important role in distinguishing the concentration difference induced by subtle variations of the electrical responses. A high peak temperature of ≈ 300 ° C facilitates concentration discrimination (with an accuracy ratio of 85.9%). This work highlights the importance of the peak temperature in (simultaneous) quantitative analysis of the types and concentrations of VOCs molecules with similar properties.
High-performance InAs/GaSb type-II superlattice infrared detectors and focal plane arrays (FPAs) are normally grown by molecular beam epitaxy (MBE). In this work, we demonstrate the first long-wavelength infrared InAs/GaSb superlattice FPA grown by metalorganic chemical vapor deposition (MOCVD) with clear image. High-quality superlattice material was obtained evidenced by sharp X-ray diffraction peaks and atomic flat surface. Electrical and optical measurements performed on single element detectors showed a 50% cut-off wavelength of $\sim 10.1~\mu \text{m}$ , a dark current density of $2.5\times 10^{-5}$ A/cm 2 , a peak responsivity of 0.88 A/W and a peak detectivity of $1.7\times 10^{11}$ cm $\cdot $ Hz 1/2 /W at 80 K. A $320\times256$ FPA with $30~\mu \text{m}$ pixel pitch was then fabricated. With an integration time of 1.9 ms and an applied bias of -0.1 V, the FPA shows an average operability of 96.96%, a non-uniformity of 4.97%, a noise equivalent temperature difference of 51.1 mK and a peak detectivity of $2.3\times 10^{10}$ cm $\cdot $ Hz 1/2 /W at 80 K without thinning down the substrate.
In recent years, the smart electronic nose (E-nose) has witnessed rapid applications in diverse fields. Apart from sensor arrays, the recognition algorithm plays a determinant role in the performance of E-nose. Focusing on the signal processing of E-nose, the response signal characteristic of a sensor is introduced first in this article. Based on the differences between the processing of features, the algorithms are subsequently divided into traditional and artificial neural networks (ANNs)-based, and their respective properties are specifically analyzed through the application in reality. The evaluation metrics for these algorithms are then summarized. Finally, the challenges and prospects of the algorithm are concluded. This article aims to help researchers in diverse fields employ and explore the appropriate gas recognition algorithms for the emerging applications of E-nose.
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