Therapeutic effect of a combination of montelukast and vitamins A and D drops in children with bronchial asthma, and its influence on quality of life

Purpose: To investigate the efficacy of a combination of montelukast and vitamins A and D drops in bronchial asthma children, and its effect on quality of life.Methods: Sixty bronchial asthma children from June 2018 to June 2020 were collected and randomized into study group and control group (30 cases in each group). Control group received montelukast sodium (chewable tablets), while the study group received vitamins A and D drops (capsules) plus. Clinical efficacy, lung function, serum inflammatory factors, and quality of life were evaluated and compared.Results: Compared with control group, total treatment effectiveness was higher and the symptom remission period was shorter in the study group (p < 0.05). Post-treatment, the parameters of FEV1 and FVC increased in both groups, but higher in the study group (p < 0.05). Serum levels of CRP and IL-4 in both groups decreased after treatment, while serum IL-10 levels were significantly up-regulated. Compared with control group, the levels of these indicators were improved in the study group (p < 0.05). Post-treatment Chinese Version of Pediatric Quality of Life Asthma Specific Scale (PedSQL) score was higher than before treatment, with higher values (for all indicators) in the study group (p < 0.05).Conclusion: The combination therapy of montelukast and vitamins A and D drops produces good clinical efficacy in children with bronchial asthma. It significantly shortens the time taken for relief of clinical symptoms, improves lung function, reduces inflammatory response, controls asthma, and improves the quality of life of the patients

Design of extended Kalman filtering neural network control system based on particle swarm identification of nonlinear U-model

This paper studies the modelling of a class of nonlinear plants with known structures but unknown parameters and proposes a general nonlinear U-model expression. The particle swarm optimization algorithm is used to identify the time-varying parameters of the nonlinear U-model online, which solves the identification problem of the nonlinear U-model system. Newton iterative algorithm is used for nonlinear model transformation. Extended Kalman filter (EKF) is used as the learning algorithm of radial basis function (RBF) neural network to solve the interference problem in a nonlinear system. After determining the number of network nodes in the neural network, EKF can simultaneously determine the network threshold and weight matrix, use the online learning ability of the neural network, adjust the network parameters, make the system output track the ideal output, and improve the convergence speed and anti-noise capability of the system. Finally, simulation examples are used to verify the identification effect of the particle swarm identification algorithm based on the U-model and the effectiveness of the extended Kalman filtering neural network control system based on particle swarm identification

Research on parallel control of CMAC and PD based on U model

In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional derivative (PD) in parallel is proposed. The algorithm learns online through a neural network while optimizing the output of the PD, which ultimately enables the actual output of the system to track up to the desired output. Considering that the nonlinear object has the characteristic of rapid change with time, the article improves the PD algorithm to nonlinear PD control algorithm to complete the design of the system. The algorithm automatically adjusts the weights according to the error magnitude to complete the controller parameter adjustment, thus reducing the error of the system. The simulation results show that the nonlinear PD algorithm is better than the PD algorithm, meanwhile, the tracking speed and control precision of the system are improved

A New Double Color Image Watermarking Algorithm Based on the SVD and Arnold Scrambling

We propose a new image watermarking scheme based on the real SVD and Arnold scrambling to embed a color watermarking image into a color host image. Before embedding watermark, the color watermark image W with size of M×M is scrambled by Arnold transformation to obtain a meaningless image W~. Then, the color host image A with size of N×N is divided into nonoverlapping N/M×N/M pixel blocks. In each (i,j) pixel block Ai,j, we form a real matrix Ci,j with the red, green, and blue components of Ai,j and perform the SVD of Ci,j. We then replace the three smallest singular values of Ci,j by the red, green, and blue values of W~ij with scaling factor, to form a new watermarked host image A~ij. With the reserve procedure, we can extract the watermark from the watermarked host image. In the process of the algorithm, we only need to perform real number algebra operations, which have very low computational complexity and are more effective than the one using the quaternion SVD of color image

Rapid Determination of Ractopamine Residues in Edible Animal Products by Enzyme-Linked Immunosorbent Assay: Development and Investigation of Matrix Effects

To determine ractopamine residues in animal food products (chicken muscle, pettitoes, pig muscle, and pig liver), we established a rapid direct competitive enzyme-linked immunosorbent assay (ELISA) using a polyclonal antibody generated from ractopamine-linker-BSA. The antibody showed high sensitivity and specificity in phosphate buffer, with an IC50 of 0.6 ng/mL, and the limit of detection was 0.04 ng/mL. The matrix effect of the samples was easily eliminated by one-step extraction with PBS, without any organic solution or clean-up procedure such as SPE or liquid-liquid extraction, making it a much more simple and rapid method than previously reported ones. The detection limit in blank samples was 0.2 μg/kg. To validate this new RAC (ractopamine hydrochloride) ELISA, a RAC-free pig liver sample spiked at three different concentrations was prepared and analyzed by HPLC and ELISA. The results showed a good correlation between the data of ELISA and HPLC (R2 > 0.95), which proves that the established ELISA is accurate enough to quantify the residue of RAC in the animal derived foods

Construction of Trisubstituted Chromone Skeletons Carrying Electron-Withdrawing Groups Via PhIO-Mediated Dehydrogenation and Its Application to the Synthesis of Frutinone A

Abstract The construction of the biologically interesting chromone skeleton was realized by PhIO-mediated dehydrogenation of chromanones under mild conditions. Interestingly, this method also found application in the synthesis of the naturally occurring frutinone A