Nighttime bionic compass based on a short-wave infrared polarization sensing system.

Sky-bionic polar co-ordinate navigation is an effective means of providing navigational information in the absence of a priori information. Polar co-ordinate navigation during clear daytime conditions has been studied, but there has been a lack of research of it at night due to problems with noise. Therefore, in this paper, a short-wave infrared polarimetric sensor system is designed, which is capable of acquiring atmospheric polarimetric information in low illumination environments at night, compared with traditional visible band sensors. Additionally, based on the statistics of polarization angle information, an algorithm for removing noise and starlight is proposed to solve the influence of starlight and noise on the polarization information at night. After many outdoor experiments, we found that the method can output the heading angle stably and accurately, and its standard deviation is controlled to be 0.42° in a clear night.

Multispectral silicon-based photodetector with stacked PN junctions.

A multispectral silicon-based photodetector structure with stacked PN junctions is proposed in this study. The substrate layer of the proposed photodetector consists of four vertically stacked PN junction structures that contain four photodiodes. The designed structure achieves quantum efficiency of up to 70% and a response time of 5.1 × 10-8 s. The proposed photodetector has a simple structure, and the vertically stacked PN junction structure not only reduces the phenomenon of color aliasing, but also achieves multispectral absorption over the range from ultraviolet to visible light with high response speeds, which provides an effective way to perform high-quality imaging.

High-performance subwavelength polarizer using "sandwich" structured substrates.

A subwavelength polarizer based on "sandwich" structured substrates is proposed in this study. The proposed subwavelength polarizer consists of three layers of subwavelength aluminum wires and dielectric substrate. The designed structure achieves an extinction ratio (ER) greater than 90 dB in a 400-800 nm visible wavelength region, achieving a maximum ER of 135 dB at 750 nm. Our results demonstrate significant improvements over the conventional single- and double-grid polarizers in terms of an ER and spectral range coverage. The proposed subwavelength polarizer in this paper has great potential in polarimetric imaging, liquid crystal display, and other optical fields.

Design and Fabrication of a Novel Wheel-Ring Triaxial Gyroscope.

This paper presents a new type of three-axis gyroscope. The gyroscope comprises two independent parts, which are nested to further reduce the structure volume. The capacitive drive was adopted. The motion equation, capacitance design, and spring design of a three-axis gyroscope were introduced, and the corresponding formulas were derived. Furthermore, the X/Y driving frequency of the gyroscope was 5954.8 Hz, the Y-axis detection frequency was 5774.5 Hz, and the X-axis detection frequency was 6030.5 Hz, as determined by the finite element simulation method. The Z-axis driving frequency was 10,728 Hz, and the Z-axis sensing frequency was 10,725 Hz. The MEMS gyroscope's Z-axis driving mode and the sensing mode's frequency were slightly mismatched, so the gyroscope demonstrated a larger bandwidth and higher Z-axis mechanical sensitivity. In addition, the structure also has good Z-axis impact resistance. The transient impact simulation of the gyroscope structure showed that the maximum stress of the sensitive structure under the impact of 10,000 g@5 ms was 300.18 Mpa. The gyroscope was produced by etching silicon wafers in DRIE mode to obtain a high aspect ratio structure, tightly connected to the glass substrate by silicon/glass anode bonding technology.

Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising.

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.

Intrinsic Surface Effects of Tantalum and Titanium on Integrin α5ß1/ ERK1/2 Pathway-Mediated Osteogenic Differentiation in Rat Bone Mesenchymal Stromal Cells.

BACKGROUND/AIMS: Accumulating evidence demonstrates the superior osteoinductivity of tantalum (Ta) to that of titanium (Ti); however, the mechanisms underlying these differences are unclear. Thus, the objective of the present study was to examine the effects of Ta and Ti surfaces on osteogenesis using rat bone mesenchymal stromal cells (rBMSCs) as a model. METHODS: Ta and Ti substrates were polished to a mirror finish to minimize the influences of structural factors, and the intrinsic surface effects of the two materials on the integrin α5ß1/mitogen-activated protein kinases 3 and 1 (ERK1/2) cascade-mediated osteogenesis of rBMSCs were evaluated. Alkaline phosphatase (ALP) activity, Alizarin Red staining, real-time polymerase chain reaction, and western blot assays of critical osteogenic markers were conducted to evaluate the effects of the two substrates on cell osteogenesis. Moreover, the role of the integrin α5ß1/ERK1/2 pathway on the osteoinductive performance of Ta and Ti was assessed by up- and down-regulation of integrin α5 and ß1 with RNA interference, as well as through ERK1/2 inhibition with U0126. RESULTS: Osteogenesis of rBMSCs seeded on the Ta surface was superior to that of cells seeded on the Ti surface in terms of ALP activity, extracellular matrix calcification, and the expression of integrin α5, integrin ß1, ERK1/2, Runt-related transcription factor 2, osteocalcin, collagen type I, and ALP at both the mRNA and protein levels. Moreover, down-regulation of integrin α5 or integrin ß1, or ERK1/2 inhibition severely impaired the osteoblastic differentiation on the Ta surface. By contrast, over-expression of integrin α5 or integrin ß1 improved osteogenesis on the Ti substrates, while subsequent ERK1/2 inhibition abrogated this effect. CONCLUSION: The integrin α5ß1/ERK1/2 pathway plays a crucial role in regulating rBMSCs osteogenic differentiation; thus, the greater ability of a Ta surface to trigger integrin α5ß1/ERK1/2 signaling may explain its better osteoinductivity. The different effects of Ta and Ti surfaces on rBMSC osteogenesis are considered to be related to the conductive behaviors between integrin α5ß1 and the oxides spontaneously formed on the two metals. These results should facilitate the development of engineering strategies with Ta and Ti surfaces for improved osteogenesis in endosteal implants.

An Improved Strong Tracking Cubature Kalman Filter for GPS/INS Integrated Navigation Systems.

The cubature Kalman filter (CKF) is widely used in the application of GPS/INS integrated navigation systems. However, its performance may decline in accuracy and even diverge in the presence of process uncertainties. To solve the problem, a new algorithm named improved strong tracking seventh-degree spherical simplex-radial cubature Kalman filter (IST-7thSSRCKF) is proposed in this paper. In the proposed algorithm, the effect of process uncertainty is mitigated by using the improved strong tracking Kalman filter technique, in which the hypothesis testing method is adopted to identify the process uncertainty and the prior state estimate covariance in the CKF is further modified online according to the change in vehicle dynamics. In addition, a new seventh-degree spherical simplex-radial rule is employed to further improve the estimation accuracy of the strong tracking cubature Kalman filter. In this way, the proposed comprehensive algorithm integrates the advantage of 7thSSRCKF’s high accuracy and strong tracking filter’s strong robustness against process uncertainties. The GPS/INS integrated navigation problem with significant dynamic model errors is utilized to validate the performance of proposed IST-7thSSRCKF. Results demonstrate that the improved strong tracking cubature Kalman filter can achieve higher accuracy than the existing CKF and ST-CKF, and is more robust for the GPS/INS integrated navigation system.

A Noise Reduction Method for Dual-Mass Micro-Electromechanical Gyroscopes Based on Sample Entropy Empirical Mode Decomposition and Time-Frequency Peak Filtering.

The different noise components in a dual-mass micro-electromechanical system (MEMS) gyroscope structure is analyzed in this paper, including mechanical-thermal noise (MTN), electronic-thermal noise (ETN), flicker noise (FN) and Coriolis signal in-phase noise (IPN). The structure equivalent electronic model is established, and an improved white Gaussian noise reduction method for dual-mass MEMS gyroscopes is proposed which is based on sample entropy empirical mode decomposition (SEEMD) and time-frequency peak filtering (TFPF). There is a contradiction in TFPS, i.e., selecting a short window length may lead to good preservation of signal amplitude but bad random noise reduction, whereas selecting a long window length may lead to serious attenuation of the signal amplitude but effective random noise reduction. In order to achieve a good tradeoff between valid signal amplitude preservation and random noise reduction, SEEMD is adopted to improve TFPF. Firstly, the original signal is decomposed into intrinsic mode functions (IMFs) by EMD, and the SE of each IMF is calculated in order to classify the numerous IMFs into three different components; then short window TFPF is employed for low frequency component of IMFs, and long window TFPF is employed for high frequency component of IMFs, and the noise component of IMFs is wiped off directly; at last the final signal is obtained after reconstruction. Rotation experimental and temperature experimental are carried out to verify the proposed SEEMD-TFPF algorithm, the verification and comparison results show that the de-noising performance of SEEMD-TFPF is better than that achievable with the traditional wavelet, Kalman filter and fixed window length TFPF methods.

Optimization and Experimentation of Dual-Mass MEMS Gyroscope Quadrature Error Correction Methods.

This paper focuses on an optimal quadrature error correction method for the dual-mass MEMS gyroscope, in order to reduce the long term bias drift. It is known that the coupling stiffness and demodulation error are important elements causing bias drift. The coupling stiffness in dual-mass structures is analyzed. The experiment proves that the left and right masses' quadrature errors are different, and the quadrature correction system should be arranged independently. The process leading to quadrature error is proposed, and the Charge Injecting Correction (CIC), Quadrature Force Correction (QFC) and Coupling Stiffness Correction (CSC) methods are introduced. The correction objects of these three methods are the quadrature error signal, force and the coupling stiffness, respectively. The three methods are investigated through control theory analysis, model simulation and circuit experiments, and the results support the theoretical analysis. The bias stability results based on CIC, QFC and CSC are 48 °/h, 9.9 °/h and 3.7 °/h, respectively, and this value is 38 °/h before quadrature error correction. The CSC method is proved to be the better method for quadrature correction, and it improves the Angle Random Walking (ARW) value, increasing it from 0.66 °/√h to 0.21 °/√h. The CSC system general test results show that it works well across the full temperature range, and the bias stabilities of the six groups' output data are 3.8 °/h, 3.6 °/h, 3.4 °/h, 3.1 °/h, 3.0 °/h and 4.2 °/h, respectively, which proves the system has excellent repeatability.

The Development of a Dual-Warhead Impact System for Dynamic Linearity Measurement of a High-g Micro-Electro-Mechanical-Systems (MEMS) Accelerometer.

Despite its extreme significance, dynamic linearity measurement for high-g accelerometers has not been discussed experimentally in previous research. In this study, we developed a novel method using a dual-warhead Hopkinson bar to measure the dynamic linearity of a high-g acceleration sensor with a laser interference impact experiment. First, we theoretically determined that dynamic linearity is a performance indicator that can be used to assess the quality merits of high-g accelerometers and is the basis of the frequency response. We also found that the dynamic linearity of the dual-warhead Hopkinson bar without an accelerometer is 2.5% experimentally. Further, we verify that dynamic linearity of the accelerometer is 3.88% after calibrating the Hopkinson bar with the accelerometer. The results confirm the reliability and feasibility of measuring dynamic linearity for high-g accelerometers using this method.

Design and Fabrication of Micro Hemispheric Shell Resonator with Annular Electrodes.

Electrostatic driving and capacitive detection is widely used in micro hemispheric shell resonators (HSR). The capacitor gap distance is a dominant factor for the initial capacitance, and affects the driving voltage and sensitivity. In order to decrease the equivalent gap distance, a micro HSR with annular electrodes fabricated by a glassblowing method was developed. Central and annular cavities are defined, and then the inside gas drives glass softening and deformation at 770 °C. While the same force is applied, the deformation of the hemispherical shell is about 200 times that of the annular electrodes, illustrating that the deformation of the electrodes will not affect the measurement accuracy. S-shaped patterns on the annular electrodes and internal-gear-like patterns on the hemispherical shell can improve metal malleability and avoid metal cracking during glass expansion. An arched annular electrode and a hemispheric shell are demonstrated. Compared with HSR with a spherical electrode, the applied voltage could be reduced by 29%, and the capacitance could be increased by 39%, according to theoretical and numerical calculation. The surface roughness of glass after glassblowing was favorable (Rq = 0.296 nm, Ra = 0.217 nm). In brief, micro HSR with an annular electrode was fabricated, and its superiority was preliminarily confirmed.

Vacuum extraction enhances rhPDGF-BB immobilization on nanotubes to improve implant osseointegration in ovariectomized rats.

Nanotube morphology has been previously applied to improve osseointegration in osteoporosis, but the osteogenic capability of the technique requires further improvements. This study aimed to investigate the effects of vacuum extraction on the loading of rhPDGF-BB on nanotube arrays as well as its effects on the osseointegration of ovariectomized (OVX) rats. More rhPDGF-BB protein particles aggregated on the nanotube surface and into the nanotube after vacuum extraction for 10 min. The immobilized protein could be slowly released for at least 14 days and still kept its biological activity. In vitro, the immobilized rhPDGF-BB enhanced cell adhesion, proliferation and osteogenic differentiation. In vivo, more rhPDGF-BB immobilized on the nanotube surface also promoted the osseointegration. These results suggest that the enhanced immobilization of rhPDGF-BB on nanotube arrays can potentially be used in the future as an implant surface modification strategy in dental and orthopedic applications in osteoporotic patients. FROM THE CLINICAL EDITOR: This study presents convincing evidence that enhanced immobilization of recombinant human PDGF-BB protein particles on nanotubes lead to improved osteogenic differentiation in an experimental system. When used as a surface modification strategy for dental or orthopedic implants, this method was able to promote osseointegration even in an osteoporotic animal model, raising the likelihood for potential future clinical applications.

State-of-the-Art Functional Biomaterials in China.

In recent years, rapid advancements in multidisciplinary fields (materials, biology, chemical physics, etc [...].

MEMS Gyroscope Temperature Compensation Based on Improved Complete Ensemble Empirical Mode Decomposition and Optimized Extreme Learning Machine.

Herein, we investigate the temperature compensation for a dual-mass MEMS gyroscope. After introducing and simulating the dual-mass MEMS gyroscope's working modes, we propose a hybrid algorithm for temperature compensation relying on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sample entropy, time-frequency peak filtering, non-dominated sorting genetic algorithm-II (NSGA II) and extreme learning machine. Firstly, we use ICEEMDAN to decompose the gyroscope's output signal, and then we use sample entropy to classify the decomposed signals. For noise segments and mixed segments with different levels of noise, we use time-frequency peak filtering with different window lengths to achieve a trade-off between noise removal and signal retention. For the feature segment with temperature drift, we build a compensation model using extreme learning machine. To improve the compensation accuracy, NSGA II is used to optimize extreme learning machine, with the prediction error and the 2-norm of the output-layer connection weight as the optimization objectives. Enormous simulation experiments prove the excellent performance of our proposed scheme, which can achieve trade-offs in signal decomposition, classification, denoising and compensation. The improvement in the compensated gyroscope's output signal is analyzed based on Allen variance; its angle random walk is decreased from 0.531076°/h/√Hz to 6.65894 × 10-3°/h/√Hz and its bias stability is decreased from 32.7364°/h to 0.259247°/h.

Temperature Compensation for MEMS Accelerometer Based on a Fusion Algorithm.

This study proposes a fusion algorithm based on forward linear prediction (FLP) and particle swarm optimization-back propagation (PSO-BP) to compensate for the temperature drift. Firstly, the accelerometer signal is broken down into several intrinsic mode functions (IMFs) using variational modal decomposition (VMD); then, according to the FE algorithm, the IMF signal is separated into mixed components, temperature drift, and pure noise. After that, the mixed noise is denoised by FLP, and PSO-BP is employed to create a model for temperature adjustment. Finally, the processed mixed noise and the processed IMFs are rebuilt to obtain the enhanced output signal. To confirm that the suggested strategy works, temperature experiments are conducted. After the output signal is processed by the VMD-FE-FLP-PSO-BP algorithm, the acceleration random walk has been improved by 23%, the zero deviation has been enhanced by 24%, and the temperature coefficient has been enhanced by 92%, compared with the original signal.

Seamless Micro-Electro-Mechanical System-Inertial Navigation System/Polarization Compass Navigation Method with Data and Model Dual-Driven Approach.

The integration of micro-electro-mechanical system-inertial navigation systems (MEMS-INSs) with other autonomous navigation sensors, such as polarization compasses (PCs) and geomagnetic compasses, has been widely used to improve the navigation accuracy and reliability of vehicles in Internet of Things (IoT) applications. However, a MEMS-INS/PC integrated navigation system suffers from cumulative errors and time-varying measurement noise covariance in unknown, complex occlusion, and dynamic environments. To overcome these problems and improve the integrated navigation system's performance, a dual data- and model-driven MEMS-INS/PC seamless navigation method is proposed. This system uses a nonlinear autoregressive neural network (NARX) based on the Gauss-Newton Bayesian regularization training algorithm to model the relationship between the MEMS-INS outputs composed of the specific force and angular velocity data and the PC heading's angular increment, and to fit the integrated navigation system's dynamic characteristics, thus realizing data-driven operation. In the model-driven part, a nonlinear MEMS-INS/PC loosely coupled navigation model is established, the variational Bayesian method is used to estimate the time-varying measurement noise covariance, and the cubature Kalman filter method is then used to solve the nonlinear problem in the model. The robustness and effectiveness of the proposed method are verified experimentally. The experimental results show that the proposed method can provide high-precision heading information stably in complex, occluded, and dynamic environments.

A Temperature Compensation Approach for Micro-Electro-Mechanical Systems Accelerometer Based on Gated Recurrent Unit-Attention and Robust Local Mean Decomposition-Sample Entropy-Time-Frequency Peak Filtering.

MEMS accelerometers are significantly impacted by temperature and noise, leading to a considerable compromise in their accuracy. In response to this challenge, we propose a parallel denoising and temperature compensation fusion algorithm for MEMS accelerometers based on RLMD-SE-TFPF and GRU-attention. Firstly, we utilize robust local mean decomposition (RLMD) to decompose the output signal of the accelerometer into a series of product function (PF) signals and a residual signal. Secondly, we employ sample entropy (SE) to classify the decomposed signals, categorizing them into noise segments, mixed segments, and temperature drift segments. Next, we utilize the time-frequency peak filtering (TFPF) algorithm with varying window lengths to separately denoise the noise and mixed signal segments, enabling subsequent signal reconstruction and training. Considering the strong inertia of the temperature signal, we innovatively introduce the accelerometer's output time series as the model input when training the temperature compensation model. We incorporate gated recurrent unit (GRU) and attention modules, proposing a novel GRU-MLP-attention model (GMAN) architecture. Simulation experiments demonstrate the effectiveness of our proposed fusion algorithm. After processing the accelerometer output signal through the RLMD-SE-TFPF denoising algorithm and the GMAN temperature drift compensation model, the acceleration random walk is reduced by 96.11%, with values of 0.23032 g/h/Hz for the original accelerometer output signal and 0.00895695 g/h/Hz for the processed signal.

Robust Multifunctional Ultrathin 2 Nanometer Organic Nanofibers.

Ultrathin organic nanofibers (UTONFs) represent an emerging class of nanomaterials as they carry a set of favorable attributes, including ultrahigh specific surface area, lightweight, and mechanical flexibility, over inorganic counterparts, for use in biomedicine and nanotechnology. However, precise synthesis of uniform UTONFs (diameter ≤ 2 nm) with tailored functionalities remained challenging. Herein, we report robust multifunctional UTONFs using hydrophobic interaction-driven self-assembly of amphiphilic alternating peptoids containing hydrophobic photoresponsive azobenzene and hydrophilic hydroxyl moieties periodically arranged along the peptoid backbone. Notably, the as-crafted UTONFs are approximately 2 nm in diameter and tens of micrometers in length (an aspect ratio, AR, of ∼10000), exemplifying the UTONFs with the smallest diameter yielded via self-assembly. Intriguingly, UTONFs were disassembled into short-segmented nanofibers and controllably reassembled into UTONFs, resembling "step-growth polymerization". Photoisomerization of azobenzene moieties leads to reversible transformation between UTONFs and spherical micelles. Such meticulously engineered UTONFs demonstrate potential for catalysis, bioimaging, and antibacterial therapeutics. Our study highlights the significance of the rational design of amphiphiles containing alternating hydrophobic and hydrophilic moieties in constructing otherwise unattainable extremely thin UTONFs with ultrahigh AR and stimuli-responsive functionalities for energy and bionanotechnology.

Editorial for the Special Issue on Micro-Electromechanical System Inertial Devices.

Micro-electromechanical systems (MEMS) are miniature systems comprising micro-mechanical sensors, actuators, and microelectronic circuits [...].

Temperature Drift Compensation of Fiber Optic Gyroscopes Based on an Improved Method.

This study proposes an improved multi-scale permutation entropy complete ensemble empirical mode decomposition with adaptive noise (MPE-CEEMDAN) method based on adaptive Kalman filter (AKF) and grey wolf optimizer-least squares support vector machine (GWO-LSSVM). By establishing a temperature compensation model, the gyro temperature output signal is optimized and reconstructed, and a gyro output signal is obtained with better accuracy. Firstly, MPE-CEEMDAN is used to decompose the FOG output signal into several intrinsic mode functions (IMFs); then, the IMFs signal is divided into mixed noise, temperature drift, and other noise according to different frequencies. Secondly, the AKF method is used to denoise the mixed noise. Thirdly, in order to denoise the temperature drift, the fiber gyroscope temperature compensation model is established based on GWO-LSSVM, and the signal without temperature drift is obtained. Finally, the processed mixed noise, the processed temperature drift, the processed other noise, and the signal-dominated IMFs are reconstructed to acquire the improved output signal. The experimental results show that, by using the improved method, the output of a fiber optic gyroscope (FOG) ranging from -30 °C to 60 °C decreases, and the temperature drift dramatically declines. The factor of quantization noise (Q) reduces from 6.1269 × 10-3 to 1.0132 × 10-4, the factor of bias instability (B) reduces from 1.53 × 10-2 to 1 × 10-3, and the factor of random walk of angular velocity (N) reduces from 7.8034 × 10-4 to 7.2110 × 10-6. The improved algorithm can be adopted to denoise the output signal of the FOG with higher accuracy.