37 research outputs found
Human lower extremity joint moment prediction: A wavelet neural network approach
Joint moment is one of the most important factors in human gait analysis. It can be calculated using multi body dynamics but might not be straight forward. This study had two main purposes; firstly, to develop a generic multi-dimensional wavelet neural network (WNN) as a real-time surrogate model to calculate lower extremity joint moments and compare with those determined by multi body dynamics approach, secondly, to compare the calculation accuracy of WNN with feed forward artificial neural network (FFANN) as a traditional intelligent predictive structure in biomechanics. To aim these purposes, data of four patients walked with three different conditions were obtained from the literature. A total of 10 inputs including eight electromyography (EMG) signals and two ground reaction force (GRF) components were determined as the most informative inputs for the WNN based on the mutual information technique. Prediction ability of the network was tested at two different levels of inter-subject generalization. The WNN predictions were validated against outputs from multi body dynamics method in terms of normalized root mean square error (NRMSE (%)) and cross correlation coefficient (ρ). Results showed that WNN can predict joint moments to a high level of accuracy (NRMSE 0.94) compared to FFANN (NRMSE 0.89). A generic WNN could also calculate joint moments much faster and easier than multi body dynamics approach based on GRFs and EMG signals which released the necessity of motion capture. It is therefore indicated that the WNN can be a surrogate model for real-time gait biomechanics evaluation
RBF Neural Network Fractional-Order Sliding Mode Control with an Application to Direct a Three Matrix Converter under an Unbalanced Grid
This paper presents a fractional-order sliding mode control scheme based on an RBF neural network (RBFFOSMC) for a direct three matrix converter (DTMC) operating under unbalanced grid voltages. The RBF neural network (RBF NN) is designed to approximate a nonlinear fractional-order sliding mode controller. The proposed method aims to achieve constant active power whilst maintaining a near unity input power factor. First, an opportune reference current is accurately generated according to the reference power and the RBFFOSMC is designed in a dq reference frame to achieve a perfect tracking of the input current reference. An almost constant active power, free of low-frequency ripples, is then supplied from the grid after compensating for the output voltage. Simulation and experimental studies prove the feasibility and effectiveness of the proposed control method
RBF Neural Network Fractional-Order Sliding Mode Control with an Application to Direct a Three Matrix Converter under an Unbalanced Grid
This paper presents a fractional-order sliding mode control scheme based on an RBF neural network (RBFFOSMC) for a direct three matrix converter (DTMC) operating under unbalanced grid voltages. The RBF neural network (RBF NN) is designed to approximate a nonlinear fractional-order sliding mode controller. The proposed method aims to achieve constant active power whilst maintaining a near unity input power factor. First, an opportune reference current is accurately generated according to the reference power and the RBFFOSMC is designed in a dq reference frame to achieve a perfect tracking of the input current reference. An almost constant active power, free of low-frequency ripples, is then supplied from the grid after compensating for the output voltage. Simulation and experimental studies prove the feasibility and effectiveness of the proposed control method
EFFECT OF miR-663b ON INTERLEUKIN-1β-INDUCED INFLAMMATORY RESPONSE AND APOPTOSIS OF NUCLEUS PULPOSUS CELLS AND ITS MECHANISM
Objective To investigate the effect of miR-663b on the inflammatory response and apoptosis of nucleus pulposus cells (NPCs) induced by interleukin-1β (IL-1β) and its mechanism. Methods According to the different treatment me-thods, NPCs were divided into group A (no treatment), group B (induced by IL-1β), group C (IL-1β induction+miR-663b mimic transfection), and group D (IL-1β induction+miR-633b NC transfection). RT-qPCR was used to measure the expression levels of miR-663b, inflammatory factors [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β], type Ⅱ collagen, and po-lysaccharide in NPCs; CCK-8 assay and TUNEL staining were used to observe the proliferation and apoptosis of NPCs; Western blotting was used to measure the protein expression level of interleukin-1 receptor 1 (IL1R1) in NPCs. TargetScan database was used to predict the potential binding sites between miR-663b and IL1R1. The 293T cells were divided into group E (transfected with IL1R1-wt plasmid+miR-663b mimic), group F (transfected with IL1R1-wt plasmid+miR-663b mimic), group G (transfected with IL1R1-mut plasmid+miR-663b mimic), and group H (transfected with IL1R1-mut plasmid+mimic NC), and the luciferase activity of NPCs was measured for each group. Results RT-qPCR results showed that compared with groups A, B, and D, group C had a significant increase in the relative expression level of miR-663b (t=9.41-22.93,P<0.01), and compared with groups B and D, group C had significant changes in the relative expression levels of TNF-α, IL-6, IL-1β, type Ⅱ collagen, and polysaccharide (t=3.17-32.51,P<0.01). CCK-8 assay and TUNEL staining showed that compared with groups B and D, group C had a significant increase in the proliferation of NPCs (t=3.14,3.96,P<0.01) and a significant reduction in the apoptosis of NPCs (t=4.28,168.61,P<0.01). RT-qPCR and Western blotting showed that compared with groups B and D, group C had signi-ficant reductions in the relative protein expression levels of IL1R1 and IL1R1 in NPCs (t=6.39-12.84,P<0.01). Dual-luciferase reporter assay showed that group E had a significantly lower luciferase activity than groups F, G, and H (t=10.62-16.27,P<0.01). Conclusion This study shows that miR-663b may downregulate the expression of IL1R1 in NPCs through targeted bin-ding to IL1R1 and slow down the inflammatory response and apoptosis of NPCs
Application of mercury intrusion method and digital image analysis in quantitative analysis of micro-scale pores in tight sandstone reservoirs: a case study of X block in Wuqi Oil Field, Ordos Basin
In order to investigate the pore structures of the tight sandstone reservoirs in the 4+5th and 6th members of the Triassic Yanchang Formation (Chang4+5 and Chang6, respectively), and the 9th and 10th members of the Jurassic Yan'an Formation (Yan9 and Yan10, respectively) in the X block of Wuqi Oil Field, Ordos Basin, 12 samples were collected to analyze reservoir properties with the approaches of scanning electron microscope observation, X-ray diffraction and high pressure mercury intrusion. We also quantitatively characterized the pore parameter and fractal dimension of the tight sandstones by the using of digital image analysis and fractal geometry. In addition, we discussed the relationship between fractal dimension and sample properties (porosity, permeability), pore structure parameter (average pore-throat radius, sorting coefficient), pore geometric parameters (dominant pore size, perimeter over area, and pore body-to-throat ratio). The influence of sedimentary facies and diagenetic environment on pore structures were also quantitatively analyzed. Results show that the pore structure fractal dimension ranges from 2.164 to 2.895, with an average value of 2.395. Fractal dimension is negatively correlated to permeability, porosity and average pore-throat radius, and positively related to sorting coefficient. Tight sandstones in the study area generally show properties of low dominant pore size, high perimeter over area, lower body-to-throat ratio, and high dimensions. The fractal dimension is positively related to body-to-throat and perimeter-to-area ratio, and negatively related to pore size. It is indicated that the pore structure of the samples is relatively complex and has strong heterogeneity. Depositional environment affects the compositional maturity and structural maturity of reservoir
Triplet-Triplet Annihilation Upconversion with Reversible Emission-Tunability Induced by Chemical-Stimuli: a Remote Modulator for Photocontrol Isomerization
Triplet-triplet
annihilation upconversion (TTA-UC) has been widely studied, but color-tunable
TTA-UC system triggered by chemical stimuli has not yet been proposed. Herein,
reversible acid/base switching of TTA-UC emission wavelength is achieved for
the first time by a simple platform, composed of a direct singlet-triplet (S0-T1)
absorpting photosensitizer, and pH-responsive 9,10-di(pyridin-4-yl)anthracene
(DPyA) as acceptor. The photosensitizer-acceptor pair exhibits efficient UC
emission (quantum yield up to 3.3%, anti-Stokes shift up to 0.92 eV) with
remarkable contrast upon base/acid treatment (Δλem,max = 82 nm, 0.46 eV). In a proof-of-concept study,
the color-adjustable TTA-UC emission was applied as a remote modulator to
photo-control reversible chemical reactions for the first time. This platform
enriches the portfolio of color-switchable TTA-UC, and the mechanism would
inspire further development of smart UC systems and extend the application
field of upconversion