A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors.

The development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and resolution. Mode-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance, providing a promising solution to overcome the limitations of traditional sensing technologies. Amplitude noise plays a key role in determining the resolution of mode-localized sensors, as the output metric is derived from the measured AR (amplitude ratio) within the weakly coupled resonator system. However, the amplitude noise originating from the weakly coupled resonator's closed-loop circuit has not yet been fully investigated. This paper presents a decouple-decomposition (DD) noise analysis model, which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop circuit. The DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the resonators. By integrating the decoupled weakly coupled resonators, the model decomposes the weakly coupled resonator's closed-loop circuit into distinct paths for amplitude and phase noise analyses. The DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled resonators. MATLAB/Simulink simulations verify the model's accuracy when compared to theoretical analysis. At the optimal operating point, the mode-localized tilt sensor achieves an input-referred instability of 3.91 × 10-4° and an input-referred AR of PSD of 2.01 × 10-4°/√Hz using the closed-loop noise model. This model is also applicable to other varieties of mode-localized sensors.

Analysis of the Thermally Induced Packaging Effects on the Frequency Drift of Micro-Electromechanical System Resonant Accelerometer.

Due to the working principle of MEMS resonant accelerometers, their thermally induced frequency drift is an inevitable practical issue for their extensive application. This paper is focused on reducing the thermally induced packaging effects on the frequency drift. A leadless ceramic chip carrier package with a stress-buffering layer was proposed for a MEMS resonant accelerometer, and the influences of packaging structure parameters on the frequency drift were investigated through finite element simulations and verified experimentally. Because of the thermal mismatch between dissimilar materials, the thermo-mechanical stress within the resonant beam leads to a change in the effective stiffness and causes the frequency drift to decrease linearly with increasing temperature. Furthermore, our investigations reveal that increasing the stress-buffering layer thickness and reducing the solder layer thickness can significantly minimize the thermo-mechanical stress within the resonant beam. As the neutral plane approaches the horizontal symmetry plane of the resonant beam when optimizing the packaging structure, the effects of the compressive and tensile stresses on the effective stiffness of the resonant beam will cancel each other out, which can dramatically reduce the frequency drift. These findings provide guidelines for packaging design through which to improve the temperature stability of MEMS resonant accelerometers.

An Evaluation of MEMS-IMU Performance on the Absolute Trajectory Error of Visual-Inertial Navigation System.

Nowadays, accurate and robust localization is preliminary for achieving a high autonomy for robots and emerging applications. More and more, sensors are fused to guarantee these requirements. A lot of related work has been developed, such as visual-inertial odometry (VIO). In this research, benefiting from the complementary sensing capabilities of IMU and cameras, many problems have been solved. However, few of them pay attention to the impact of different performance IMU on the accuracy of sensor fusion. When faced with actual scenarios, especially in the case of massive hardware deployment, there is the question of how to choose an IMU appropriately? In this paper, we chose six representative IMUs with different performances from consumer-grade to tactical grade for exploring. According to the final performance of VIO based on different IMUs in different scenarios, we analyzed the absolute trajectory error of Visual-Inertial Systems (VINS_Fusion). The assistance of IMU can improve the accuracy of multi-sensor fusion, but the improvement of fusion accuracy with different grade MEMS-IMU is not very significant in the eight experimental scenarios; the consumer-grade IMU can also have an excellent result. In addition, the IMU with low noise is more versatile and stable in various scenarios. The results build the route for the development of Inertial Navigation System (INS) fusion with visual odometry and at the same time, provide a guideline for the selection of IMU.

Novel nondelay-based reservoir computing with a single micromechanical nonlinear resonator for high-efficiency information processing.

Reservoir computing is a potential neuromorphic paradigm for promoting future disruptive applications in the era of the Internet of Things, owing to its well-known low training cost and compatibility with hardware. It has been successfully implemented by injecting an input signal into a spatially extended reservoir of nonlinear nodes or a temporally extended reservoir of a delayed feedback system to perform temporal information processing. Here we propose a novel nondelay-based reservoir computer using only a single micromechanical resonator with hybrid nonlinear dynamics that removes the usually required delayed feedback loop. The hybrid nonlinear dynamics of the resonator comprise a transient nonlinear response, and a Duffing nonlinear response is first used for reservoir computing. Due to the richness of this nonlinearity, the usually required delayed feedback loop can be omitted. To further simplify and improve the efficiency of reservoir computing, a self-masking process is utilized in our novel reservoir computer. Specifically, we numerically and experimentally demonstrate its excellent performance, and our system achieves a high recognition accuracy of 93% on a handwritten digit recognition benchmark and a normalized mean square error of 0.051 in a nonlinear autoregressive moving average task, which reveals its memory capacity. Furthermore, it also achieves 97.17 ± 1% accuracy on an actual human motion gesture classification task constructed from a six-axis IMU sensor. These remarkable results verify the feasibility of our system and open up a new pathway for the hardware implementation of reservoir computing.

Reduced mechanical function of the left atrial predicts adverse outcome in pregnant women with clustering of metabolic risk factors.

INTRODUCTION: The left atrial (LA) strain and strain rate are sensitive indicators of LA function. However, they are not widely used for the evaluation of pregnant women with metabolic diseases. The aim of this study was to assess the LA strain and strain rate of pregnant women with clustering of metabolic risk factors and to explore its prognostic effect on adverse pregnancy outcomes. MATERIALS AND METHODS: Sixty-three pregnant women with a clustering of metabolic risk factors (CMR group), fifty-seven women with pregnancy-induced hypertension (PIH group), fifty-seven women with gestational diabetes mellitus (GDM group), and fifty matched healthy pregnant women (control group) were retrospectively evaluated. LA function was evaluated with two-dimensional speckle-tracking imaging. Iatrogenic preterm delivery caused by severe preeclampsia, placental abruption, and fetal distress was regarded as the primary adverse outcome. RESULTS: The CMR group showed the lowest LA strain during reservoir phase (LASr), strain during contraction phase (LASct) and peak strain rate during conduit phase (pLASRcd) among the three groups (P < 0.05). LA strain during conduit phase (LAScd) and peak strain rate during reservoir phase (pLASRr) in the CMR group were lower than those in the control and GDM groups (P < 0.05). Multivariable Cox regression analysis demonstrated systolic blood pressure (HR = 1.03, 95% CI 1.01-1.05, p = 0.001) and LASr (HR = 0.86, 95% CI 0.80-0.92, p < 0.0001) to be independent predictors of iatrogenic preterm delivery. An LASr cutoff value ≤ 38.35% predicted the occurrence of iatrogenic preterm delivery. CONCLUSIONS: LA mechanical function in pregnant women with metabolic aggregation is deteriorated. An LASr value of 38.35% or less may indicate the occurrence of adverse pregnancy outcomes.

Enhancing Performance of Reservoir Computing System Based on Coupled MEMS Resonators.

Reservoir computing (RC) is an attractive paradigm of a recurrent neural network (RNN) architecture, owning to the ease of training and existing neuromorphic implementation. Its simulated performance matches other digital algorithms on a series of benchmarking tasks, such as prediction tasks and classification tasks. In this article, we propose a novel RC structure based on the coupled MEMS resonators with the enhanced dynamic richness to optimize the performance of the RC system both on the system level and data set level. Moreover, we first put forward that the dynamic richness of RC comprises linear dynamic richness and nonlinear dynamic richness, which can be enhanced by adding delayed feedbacks and nonlinear nodes, respectively. In order to set forth this point, we compare three typical RC structures, a single-nonlinearity RC structure with single-feedback, a single-nonlinearity RC structure with double-feedbacks, and the couple-nonlinearity RC structure with double-feedbacks. Specifically, four different tasks are enumerated to verify the performance of the three RC structures, and the results show the enhanced dynamic richness by adding delayed feedbacks and nonlinear nodes. These results prove that coupled MEMS resonators offer an interesting platform to implement a complex computing paradigm leveraging their rich dynamical features.

Viaxl: A Solution of a Low-Cost Real-Time Visual Accelerometer Based on Laser Speckle Optical Flow Detection.

Non-contact and non-destructive acceleration measurement is receiving considerable attention due to their low cost, flexibility, and simplicity of implementation, as well as their excellent performance in some emerging applications such as medical electronics applications, vibration monitoring, and some other special scenarios. In this paper, a visual accelerometer system based on laser speckle optical flow detection named Viaxl is proposed. Compared with the conventional non-contact acceleration measurement method based on a laser system, Viaxl has moderate and stable performance with the advantages of low cost and simplicity of implementation. Experiment results demonstrate that Viaxl, which consists of a commercial camera and a low-cost laser pointer, can achieve real-time, non-contact acceleration measurement, and confirm the basic system performance of Viaxl: a measurement nonlinearity better than 1.3%, up to 31 dB signal-to-noise ratio, and 1150 Hz theoretic bandwidth; this demonstrates the huge potential of Viaxl in a wide range of applications, and provides a new possible technical method for non-contact acceleration detection.

Identification of genes associated with matrix metalloproteinases in invasive lung adenocarcinoma.

The aim of the present study was to identify genes with similar function to that of matrix metalloproteinases (MMPs) in invasive lung adenocarcinoma (AC) and to screen the transcription factors that regulate MMPs. The gene expression dataset GSE2514, including 20 invasive lung AC samples and 19 adjacent normal lung samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the limma package in R. Genes with similar function to MMPs were identified by K-means clustering. Their correlations with MMPs were validated using Pearson correlation analysis. The expression of MMPs in lung cancer and normal tissues was evaluated by western blot analysis. Protein-protein interaction (PPI) network and transcriptional regulatory network analyses were performed with Retrieval of Interacting Genes and Database for Annotation, Visualization and Integrated Discovery, respectively. As a result, 269 DEGs were identified between invasive lung AC samples and normal lung samples, including 78 upregulated and 191 downregulated genes. Four MMPs (MMP1, MMP7, MMP9 and MMP12), which were upregulated in lung AC, were clustered into one group with other genes, including NAD(P)H quinone oxidoreductase 1, claudin 3 (CLDN3), S100 calcium-binding protein P, serine protease inhibitor Kazal type 1, collagen type XI α 1 chain, periostin and desmoplakin (DSP), following cluster analysis. Pearson correlation analysis further confirmed correlations between MMP9-CLDN3, MMP9-DSP and MMP12-DSP. PPI network analysis also indicated multiple interactions between MMPs-associated genes. Furthermore, MMPs were commonly regulated by CCAAT/enhancer binding protein α transcription factor. These findings may provide further insight into the mechanisms of MMPs in invasive lung AC.

Fusion Based on Visible Light Positioning and Inertial Navigation Using Extended Kalman Filters.

With the rapid development of smart technology, the need for location-based services (LBS) increases every day. Since classical positioning technology such as GPS cannot satisfy the needs of indoor positioning, new indoor positioning technologies, such as Bluetooth, Wi-Fi, and Visible light communication (VLC), have already cut a figure. VLC positioning has been proposed because it has higher accuracy, costs less, and is easier to accomplish in comparison to the other indoor positioning technologies. However, the practicality of VLC positioning is limited since it is easily affected by multipath effects and the layout of LEDs. Thus, we propose a fusion positioning system based on extended Kalman filters, which can fuse the VLC position and the inertial navigation data. The accuracy of the fusion positioning system is in centimeters, which is better compared to the VLC-based positioning or inertial navigation alone. Furthermore, the fusion positioning system has high accuracy, saves energy, costs little, and is easy to install, making it a promising candidate for future indoor positioning applications.

The effects of SAHA on radiosensitivity in pancreatic cancer cells by inducing apoptosis and targeting RAD51.

Suberoyl anilide hydroxamic acid (SAHA) is one of the most promising Histone deacetylases(HDAC) inhibitors which has shown significant anti-tumor activity for many malignancies. We explored the potential mechanism of the radiosensitivity effect of SAHA in Panc-1 cells and attempted to develop SAHA as a systemic treatment strategy for pancreatic cancer. Growth inhibition was detected by CCK-8 assay. Radiosensitizing enhancement ratio was determined by clonogenic assay. The cell cycle and apoptosis assay was detected using flow cytometry and annexin-V/PI. The level of Bax, Bcl-2, Ku70, Ku86, RAD51, RAD54 protein expression were detected using Western blot analysis. Gene silencing was processed by lentiviral vector and qRT-PCR was performed to detect mRNA expression. The results revealed that SAHA inhibited the proliferation of Panc-1 cells. SAHA enhanced the radiosensitivity with a sensitization enhancement ratio(SER) of 1.10 of the Panc-1 cells. SAHA induced G2-M phase arrest and apoptosis of Panc-1 cells with radiation. SAHA upregulated Bax and downregulated Bcl-2, Ku70, Ku86, RAD51, RAD54 protein expression of irradiated Panc-1 cells. SAHA enhanced the radiosensitivity of Panc-1 cells by modulating RAD51 expression. SAHA enhanced radiosensitivity to pancreatic carcinoma Panc-1 cells. It was associated with the G2-M phase arrest and apoptosis via modulation of Bax and Bcl-2 expression. Downregulation of Ku70, Ku86, RAD51 and RAD54 expression caused suppression of HR-mediated DNA repair. SAHA is a good radiosensitizer for pancreatic cancer treatment.

Factors associated with early recurrence after curative surgery for gastric cancer.

AIM: To characterize patterns of gastric cancer recurrence and patient survival and to identify predictors of early recurrence after surgery. METHODS: Clinicopathological data for 417 consecutive patients who underwent curative resection for gastric cancer were retrospectively analyzed. Tumor and node status was reclassified according to the 7(th) edition of the American Joint Committee on Cancer tumor-node-metastasis classification for carcinoma of the stomach. Survival data came from both the patients' follow-up records and telephone follow-ups. Recurrent gastric cancer was diagnosed based on clinical imaging, gastroscopy with biopsy, and/or cytological examination of ascites, or intraoperative findings in patients who underwent reoperation. Predictors of early recurrence were compared in patients with pT1 and pT2-4a stage tumors. Pearson's χ (2) test and Fisher's exact test were used to compare differences between categorical variables. Survival curves were constructed using the Kaplan-Meier method and compared via the log-rank test. Variables identified as potentially important for early recurrence using univariate analysis were determined by multivariate logistic regression analysis. RESULTS: Of 417 gastric cancer patients, 80 (19.2%) were diagnosed with early gastric cancer and the remaining 337 (80.8%) were diagnosed with locally advanced gastric cancer. After a median follow-up period of 56 mo, 194 patients (46.5%) experienced recurrence. The mean time from curative surgery to recurrence in these 194 patients was 24 ± 18 mo (range, 1-84 mo). Additionally, of these 194 patients, 129 (66.5%) experienced recurrence within 2 years after surgery. There was no significant difference in recurrence patterns between early and late recurrence (P < 0.05 each). For pT1 stage gastric cancer, tumor size (P = 0.011) and pN stage (P = 0.048) were associated with early recurrence of gastric tumors. Patient age, pT stage, pN stage, Lauren histotype, lymphovascular invasion, intraoperative chemotherapy, and postoperative chemotherapy were independent predictors of early recurrence in patients with pT2-4a stage gastric cancer (P < 0.05 each). CONCLUSION: Age, pT stage, pN stage, Lauren histotype, lymphovascular invasion, intraoperative chemotherapy, and postoperative chemotherapy are independent factors influencing early recurrence of pT2-4a stage gastric cancer.

Online Game Addiction among Chinese College Students Measurement and Attribution.

This study made an initial attempt to measure and attribute online game addiction among Chinese college students. We generated three factors of online game addiction: Control Disorder, Conflict, and Injury, as well as proposed a comprehensive model that attributed online game addiction to three groups of driving forces: environmental influences (most significant), characteristics of online games, and personal reasons.