Adaptive Two-Stage Extended Kalman Filter Theory in Application of Sensorless Control for Permanent Magnet Synchronous Motor

Extended Kalman filters (EKF) have been widely used for sensorless field oriented control (FOC) in permanent magnet synchronous motor (PMSM). The first key problem associated with EKF is that the estimator requires all the plant dynamics and noise processes are exactly known. To compensate inaccurate model information and improve tracking ability, adaptive fading extended Kalman filtering algorithms have been proposed for the nonlinear system. The second key problem is that the EKF suffers from computational burden and numerical problems when state dimension is large. The two-stage extended Kalman filter (TSEKF) with respect to this problem has been extensively studied in the past. Combining the advantages of both AFEKF and TSEKF, this paper presents an adaptive two-stage extended Kalman filter (ATEKF) for closed-loop position and speed estimation of a PMSM to achieve sensorless operation. Experimental results demonstrate that the proposed ATEKF algorithm for PMSMs has strong robustness against model uncertainties and very good real-time state tracking ability

Adaptive Two-Stage Extended Kalman Filter Theory in Application of Sensorless Control for Permanent Magnet Synchronous Motor

Extended Kalman filters (EKF) have been widely used for sensorless field oriented control (FOC) in permanent magnet synchronous motor (PMSM). The first key problem associated with EKF is that the estimator requires all the plant dynamics and noise processes are exactly known. To compensate inaccurate model information and improve tracking ability, adaptive fading extended Kalman filtering algorithms have been proposed for the nonlinear system. The second key problem is that the EKF suffers from computational burden and numerical problems when state dimension is large. The two-stage extended Kalman filter (TSEKF) with respect to this problem has been extensively studied in the past. Combining the advantages of both AFEKF and TSEKF, this paper presents an adaptive two-stage extended Kalman filter (ATEKF) for closed-loop position and speed estimation of a PMSM to achieve sensorless operation. Experimental results demonstrate that the proposed ATEKF algorithm for PMSMs has strong robustness against model uncertainties and very good real-time state tracking ability

Novel PAX9 compound heterozygous variants in a Chinese family with non-syndromic oligodontia and genotype-phenotype analysis of PAX9 variants

Studies have reported that >91.9% of non-syndromic tooth agenesis cases are caused by seven pathogenic genes. Objective: To report novel heterozygous PAX9 variants in a Chinese family with non-syndromic oligodontia and summarize the reported genotype-phenotype relationship of PAX9 variants. Methodology: We recruited 28 patients with non-syndromic oligodontia who were admitted to the Hospital of Stomatology Hebei Medical University (China) from 2018 to 2021. Peripheral blood was collected from the probands and their core family members for whole-exome sequencing (WES) and variants were verified by Sanger sequencing. Bioinformatics tools were used to predict the pathogenicity of the variants. SWISS-MODEL homology modeling was used to analyze the three-dimensional structural changes of variant proteins. We also analyzed the genotype-phenotype relationships of PAX9 variants. Results: We identified novel compound heterozygous PAX9 variants (reference sequence NM_001372076.1) in a Chinese family with non-syndromic oligodontia: a new missense variant c.1010C>A (p.T337K) in exon 4 and a new frameshift variant c.330_331insGT (p.D113Afs*9) in exon 2, which was identified as the pathogenic variant in this family. This discovery expands the known variant spectrum of PAX9; then, we summarized the phenotypes of non-syndromic oligodontia with PAX9 variants. Conclusion: We found that PAX9 variants commonly lead to loss of the second molars

The Measurement of rho‐independent Transcription Terminator Efficiency

The purpose of this RFC is to provide standard methodology for the measurement of the absolute strength of terminators in bacteria. Because we have characterized the performance of terminator in E. coli and used a simple equation model, it can be expressed in PoPS

High-speed adaptive optics line scan confocal retinal imaging for human eye.

PURPOSE:Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. METHODS:A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye's optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. RESULTS:The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. CONCLUSIONS:We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss

The impact of COVID-19 vaccination campaign in Hong Kong SAR China and Singapore

Background: Vaccination has been the most important measure to mitigate the COVID-19 pandemic. The vaccination coverage was relatively low in Hong Kong Special Administrative Region China, compared to Singapore, in early 2022. Hypothetically, if the two regions, Hong Kong (HK) and Singapore (SG), swap their vaccination coverage rate, what outcome would occur? Method: We adopt the Susceptible – Vaccinated – Exposed – Infectious – Hospitalized – Death - Recovered model with a time-varying transmission rate and fit the model to weekly reported COVID-19 deaths (the data up to 2022 Nov 4) in HK and SG using R package POMP. After we obtain a reasonable fitting, we rerun our model with the estimated parameter values and swap the vaccination rates between HK and SG to explore what would happen. Results: Our model fits the data well. The reconstructed transmission rate was higher in HK than in SG in 2022. With a higher vaccination rate as in SG, the death total reported in HK would decrease by 37.5% and the timing of the peak would delay by 3 weeks. With a lower vaccination rate as in HK, the death total reported in SG would increase to 5.5-fold high with a peak 6 weeks earlier than the actual during the Delta variant period. Conclusions: Vaccination rate changes in HK and SG may lead to very different outcomes. This is likely due that the estimated transmission rates were very different in HK and SG which reflect the different control policies and dominant variants. Because of strong control measures, HK avoided large-scale community transmission of the Delta variant. Given the high breakthrough infection rate and transmission rate of the Omicron variant, increasing the vaccination rate in HK will likely yield a mild (but significant) contribution in terms of lives saved. While in SG, lower vaccination coverage to the level of HK will be disastrous

Research on the Prediction of Several Soil Properties in Heihe River Basin Based on Remote Sensing Images

Soil property monitoring is useful for sustainable agricultural production and environmental modeling. It is possible to automatically predict soil properties in a wide range based on remote sensing images. Heihe River Basin was chosen as the research area. Measurements on three soil properties, which were pH, organic carbon, and bulk density, were available there. Two kinds of attributes were extracted, which were the remote sensing index and terrain attributes. The prediction models were constructed by random forest algorithms. The features were determined by combining correlation statistics with prediction error, and different features were selected for each of the three properties. The validation experimental results are presented. The error results were as follows: pH (MAE = 0.28, RMSE = 0.39, R2 = 0.41), organic carbon (MAE = 4.75, RMSE = 8.26, R2 = 0.75), and bulk density (MAE = 0.11, RMSE = 0.13, R2 = 0.70). Through the analysis and comparison of the experimental results, it was proven that the algorithm in this paper had a good performance in the prediction of organic carbon and bulk density