The effects of structural parameters on excitation force of airflow vibration piezoelectric generator

In order to meet the requirements of airflow vibration piezoelectric generator, and solve the critical issue of stable excitation force, the key is to effectively control structure sensitive parameters. The range of structural parameters of airflow excitation device are optimized by simplified orthogonal test. The result shows that corresponding to different resonator lengths, it approximates a linear increasing trend between the amplitude of excitation force and airflow velocity, and the greater length owns the smaller slope, and vice versa. It is relatively complex for the space and ring gaps, too big or too small gap would make the amplitude smaller or even no waveform formed. The length of resonator is the main factor impacting on the frequency of excitation sound pressure, and the frequency decreases with the increase of the length, presenting an inverse relationship, and the space and ring gaps have less effect on the frequency. Therefore, for high airflow velocity, the stable excitation force of high amplitude and frequency can be obtained by short resonator. In addition, reasonable space and ring gaps are also important for ensuring bigger amplitude of excitation sound pressure. The resulting sensitive parameter values of sound excitation device can be used as references for engineering design

EXPERIMENTAL STUDY ON THE SEISMIC DAMAGE OF AEOLIAN SAND CONCRETE COLUMNS WITH DIFFERENT REINFORCEMENTS

Aeolian sand is a kind of natural material with abundant reserves and a low price. Many scholars have conducted extensive studies on the engineering applications of aeolian sand. This paper addresses the seismic damage behaviour of aeolian sand concrete columns to promote the application of aeolian sand in frame structures. A total of 5 aeolian sand concrete column specimens with different reinforcements were studied using cyclic loading tests. The failure modes, stiffness degradation, bearing capacity, hysteresis peculiarity, ductility, and energy consumption of the specimens were analysed and compared. Then, applicable damage models of the specimens were proposed. The study results prove that the seismic damage behaviour of the specimens increases with the increase of longitudinal reinforcement percentage and with the transverse steel ratio when the replacement percentage of aeolian sand is constant. Additionally, the damage model which is revised in this paper agrees well with the test results. It can be used to assess the degree of damage to the aeolian sand concrete columns

All-trans-Retinoic Acid Ameliorated High Fat Diet-Induced Atherosclerosis in Rabbits by Inhibiting Platelet Activation and Inflammation

Background. All-trans-retinoic acid (atRA) is effective for many proliferative diseases. We investigated the protective effects of atRA against atherosclerosis. Methods. Rabbits were randomly allocated to receive basal diet or an HFD for 4 weeks. HFD group then received rosuvastatin (3 mg/day), atRA (5 mg/kg/day), or the same volume of vehicle, respectively, for next 8 weeks. Results. HFD group showed increases in plasma lipids and aortic plaque formation. P-selectin expression and fibrinogen binding on platelets or deposition on the intima of the aorta also increased significantly as did the levels of TNF-α, IL-6, and fibrinogen in plasma. After 8 weeks of treatment with atRA, there was a significant decrease in plasma lipids and improvement in aortic lesions. AtRA also inhibited the expression of P-selectin and fibrinogen binding on platelets and deposition on the intima of the aorta. Conclusion. AtRA can ameliorate HFD-induced AS in rabbits by inhibiting platelet activation and inflammation

The role of 1-octyl-3-methylimidazolium hexafluorophosphate in anticorrosion coating formula development

A hydrophobic ionic liquid (1-octyl-3-methylimidazolium hexafluorophosphate, C8mimPF6) with a function of inhibiting corrosion was encapsulated at different concentrations in the copolymer of poly (methyl methacrylate) and poly (butyl acrylate) through miniemulsion polymerization. These latexes were coated on steel samples whose corrosion properties were evaluated by electrochemical techniques. It was found that increasing the C8mimPF6 concentration from 0 wt% to 30 wt%, the corrosion inhibition efficiency was remarkably improved from 41% to 89% based on the charge transfer resistance and from 64% to 87% based on the corrosion current density, respectively. The ionic liquid did not attend the reaction during latex preparation but behaved as corrosion inhibitors on the steel surface. Such an anticorrosion effect could be ascribed to the physical adsorption of the C8mim+ cation on the reaction sites and the hydrophobicity enhancement resulting from the hydrophobic PF6− anion

A New Anthracene Derivative from Marine Streptomyces sp. W007 Exhibiting Highly and Selectively Cytotoxic Activities

A new anthracene derivative, 3-hydroxy-1-keto-3-methyl-8-methoxy-1,2,3, 4-tetrahydro-benz[α]anthracene, was isolated from the marine strain Streptomyces sp. W007, and its structure was established by spectroscopic analysis including mass spectra, 1D- and 2D-NMR (1H–1H COSY, HMBC, HSQC and NOESY) experiments. 3-hydroxy-1-keto-3-methyl-8-methoxy-1,2,3,4-tetrahydro-benz[α]anthracene showed cytotoxicity against human lung adenocarcinoma cell line A549

Grid investment capability prediction based on path analysis and BP neural network

With the more complex investment environment of China’s power grid, the accurate prediction of the investment ability of power grid enterprises has become an important prerequisite for managers to make precise investment decisions. This paper first selects the factors affecting the investment capacity of the power grid from the internal and external environment, and establishes the index system of the factors affecting the investment capacity. Secondly, the path analysis is used to deeply explore the interaction relationship and influence degree of each index and investment capacity. Finally, the maximum investment capacity of the power network can be predicted based on the BP neural network prediction model. The results show that the BP neural network prediction model can achieve higher prediction accuracy when predicting the power grid investment capability