An LpL^p- Primal-Dual Weak Galerkin method for div-curl Systems

This paper presents a new $L^p$-primal-dual weak Galerkin (PDWG) finite element method for the div-curl system with the normal boundary condition for $p>1$. Two crucial features for the proposed $L^p$-PDWG finite element scheme are as follows: (1) it offers an accurate and reliable numerical solution to the div-curl system under the low $W^{\alpha, p}$-regularity ($\alpha>0$) assumption for the exact solution; (2) it offers an effective approximation of the normal harmonic vector fields on domains with complex topology. An optimal order error estimate is established in the $L^q$-norm for the primal variable where $\frac{1}{p}+\frac{1}{q}=1$. A series of numerical experiments are presented to demonstrate the performance of the proposed $L^p$-PDWG algorithm.Comment: 22 pages, 2 figures, 8 tables. arXiv admin note: text overlap with arXiv:2101.0346

PHARMACOLOGICAL EXPERIMENTAL STUDY OF THE ANTI-DEPRESSANT EFFECT OF TOTAL SAIKOSAPONINS.

Background: Chai Hu has the hepato-protective, choleretic, anti-tussive, analgesic, anti-inflammatory, anti-viral, hypotensive, hypolipidemic, and anti-tumor pharmacological effects. In this study, the objective of this paper was to study the anti-depressant effect of total saikosaponins. Materials and Methods: Total saikosaponins were extracted by reflux method, and were identified by thin layer chromatography (TLC). The anti-depressant effect of total saikosaponins was investigated in vitro by tail suspension test, forced swimming test, and reserpine antagonism test in mice. Results: Two times of reflux extraction, temperature of 70℃, and extraction time of 4hrs, for each extraction could improve the yield of saikosaponins. Each treatment group (100, 200, and 300 mg/kg), could significantly shorten the immobility time of mice in the tail suspension test in a somewhat dose-dependent manner. The total saikosaponins antagonized the reserpine-induced akinesia, and ptosis in mice. Conclusion: Total saikosaponins have an anti-depressant effect

A novel high-fidelity unscented particle filtering method for the accurate state of charge estimation of lithium-ion batteries.

Power Li-ion batteries are one of the core "three powers" systems of new energy vehicles, and its accurate batteries modeling and state prediction have become the core technology of the scientific and technological progress in the industry. This paper takes the ternary Li-ion batteries as the research subject. Aiming at the mathematical expressions of different structural features, innovatively construct a second-order Thevenin equivalent circuit model with autoregressive effect. This model can characterize the internal reaction mechanism of Li-ion batteries and fit the complex electrochemical reactions inside the battery. An improved particle filter model, namely a new high-fidelity unscented particle filter method, is designed and established. By introducing a suitable suggested density function, the model can accurately calculate the mean and variance, solve the particle degradation problem, and find out the Li-ion batteries state of charge, which is suitable for complex charging and discharging conditions. By further improving the theoretical analysis and combining with experiments under different working conditions, this method studies the Li-ion batteries state of charge. The test results show that the average absolute error of the improved equivalent circuit model is reduced by 0.00457 V, and the error rate is stably kept within 1%, which has the ability to describe Li-ion batteries well. When using the high-fidelity unscented particle filter algorithm to estimate the state of charge of the lithium battery, the robustness of the system is improved, the following effect is better, and the estimation error is controlled within 1.5%, which brings good practical value to the power Li-ion batteries

STUDY ON THE ANTI-DEPRESSANT EFFECT OF CHAIHU GUIZHI DECOCTION AND ITS MECHINISIMS OF ACTIONS

Background: Chaihu Guizhi has the effects of treating exogenous wind-cold; alternating episodes of chills and fever; noisy nose and retching; strong headache; chest and rib-side pain, and fullness, in clinical practice, it can also be used for the treatment of depression. The objective of this paper was to study the anti-depressant effect of Chaihu Guizhi decoction and its mechanism. Materials and Methods: The anti-depressant effect of Chaihu Guizhi decoction was investigated by forced swimming test, tail suspension test and antagonism of reserpine hypothermia test in mice. Results: Chaihu Guizhi decoction could significantly shorten immobility time of mice in the forced swimming test, and dose-dependence significantly shorten immobility time of mice in the tail suspension test, after administration of 50, 100, and 200mg/kg, Chaihu Guizhi decoction, a significant dose-dependent antagonism of reserpine-induced hypothermia was observed in mice of each treatment group. Conclusion: Chaihu Guizhi decoction has an antidepressant effect

Online full-parameter identification and SOC estimation of lithium-ion battery pack based on composite electrochemical-dual circuit polarization modeling.

A new composite electrochemistry-dual circuit polarization model (E-DCP) is proposed by combining the advantages of various electrochemical empirical models in this paper. Then, the multi-innovation least squares (MILS) algorithm is used to perform online full parameter identification for the E-DCP model in order to improve data usage efficiency and parameter identification accuracy. In addition, on the basis of the E-DCP model, the MILS and the extended Kalman filter (EKF) are combined to enhance the state estimation accuracy of the battery management system (BMS). Finally, the model and the algorithm are both verified through urban dynamometer driving schedule (UDDS) and the complex charge-discharge loop test. The results indicate that the accuracy of E-DCP is relatively high under different working conditions, and the errors of state of charge (SOC) estimation after the combination of MILS and EKF are all within 2.2%. This lays a concrete foundation for practical use of the BMS in the future

A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm.

As the unscented Kalman filtering algorithm is sensitive to the battery model and susceptible to the uncertain noise interference, an improved iterate calculation method is proposed to improve the charged state prediction accuracy of the lithium ion battery packs by introducing a novel splice Kalman filtering algorithm with adaptive robust performance. The battery is modeled by composite equivalent modeling and its parameters are identified effectively by investigating the hybrid power pulse test. The sensitivity analysis is carried out for the model parameters to obtain the influence degree on the prediction effect of different factors, providing a basis of the adaptive battery characterization. Subsequently, its implementation process is carried out including model building and adaptive noise correction that are perceived by the iterate charged state calculation. Its experimental results are analyzed and compared with other algorithms through the physical tests. The polarization resistance is obtained as Rp = 16.66 mΩ and capacitance is identified as Cp = 13.71 kF. The ohm internal resistance is calculated as Ro = 68.71 mΩ and the charged state has a prediction error of 1.38% with good robustness effect, providing a foundational basis of the power prediction for the lithium ion battery packs

Co-estimation of state-of-charge and state-of-health for high-capacity lithium-ion batteries.

To address the challenges of efficient state monitoring of lithium-ion batteries in electric vehicles, a co-estimation algorithm of state-of-charge (SOC) and state-of-health (SOH) is developed. The algorithm integrates techniques of adaptive recursive least squares and dual adaptive extended Kalman filtering to enhance robustness, mitigate data saturation, and reduce the impact of colored noise. At 25C, the algorithm is tested and verified under dynamic stress test (DST) and Beijing bus DST conditions. Under the Beijing bus DST condition, the algorithm achieves a mean absolute error (MAE) of 0.17% and a root mean square error (RMSE) of 0.19% for SOC estimation, with a convergence time of 4 s. Under the DST condition, the corresponding values are 0.05% for MAE, 0.07% for RMSE, and 5 s for convergence time. Moreover, in this research, the SOH is described as having internal resistance. Under the Beijing bus DST condition, the MAE and the RMSE of the estimated internal resistance of the proposed approach are 0.018% and 0.075%, with the corresponding values of 0.014% and 0.043% under the DST condition. The results of the experiments provide empirical evidence for the challenges associated with the efficacious estimation of SOC and SOH

Molecular genetic analysis of phosphomannomutase genes in Triticum monococcum

AbstractIn higher plants, phosphomannomutase (PMM) is essential for synthesizing the antioxidant ascorbic acid through the Smirnoff–Wheeler pathway. Previously, we characterized six PMM genes (TaPMM-A1, A2, B1, B2, D1 and D2) in common wheat (Triticum aestivum, AABBDD). Here, we report a molecular genetic analysis of PMM genes in Triticum monococcum (AmAm), a diploid wheat species whose Am genome is closely related to the A genome of common wheat. Two distinct PMM genes, TmPMM-1 and TmPMM-2, were found in T. monococcum. The coding region of TmPMM-1 was intact and highly conserved. In contrast, two main TmPMM-2 alleles were identified, with TmPMM-2a possessing an intact coding sequence and TmPMM-2b being a pseudogene. The transcript level of TmPMM-2a was much higher than that of TmPMM-2b, and a bacterially expressed TmPMM-2a recombinant protein displayed relatively high PMM activity. In general, the total transcript level of PMM was substantially higher in accessions carrying TmPMM-1 and TmPMM-2a than those harboring TmPMM-1 and TmPMM-2b. However, total PMM protein and activity levels did not differ drastically between the two genotypes. This work provides new information on PMM genes in T. monococcum and expands our understanding on Triticeae PMM genes, which may aid further functional and applied studies of PMM in crop plants