A rapid one-step process for fabrication of biomimetic superhydrophobic surfaces by pulse electrodeposition

Inspired by some typical plants such as lotus leaves, superhydrophobic surfaces are commonly prepared by a combination of low surface energy materials and hierarchical micro/nano structures. In this work, superhydrophobic surfaces on copper substrates were prepared by a rapid, facile one-step pulse electrodepositing process, with different duty ratios in an electrolyte containing lanthanum chloride (LaCl3·6H2O), myristic acid (CH3(CH2)12COOH), and ethanol. The equivalent electrolytic time was only 10 min. The surface morphology, chemical composition and superhydrophobic property of the pulse electrodeposited surfaces were fully investigated with SEM, EDX, XRD, contact angle meter and time-lapse photographs of water droplets bouncing method. The results show that the as-prepared surfaces have micro/nano dual scale structures mainly consisting of La[CH3(CH2)12COO]3 crystals. The maximum water contact angle (WCA) is about 160.9°, and the corresponding sliding angle is about 5°. This method is time-saving and can be easily extended to other conductive materials, having a great potential for future applications

Structure modal optimization of a strapdown inertial navigation system for an electric helicopter using an adaptive surrogate model

The purpose of this research is to prove the eventuality of using a novel adaptive surrogate model for optimization problems. The adaptive surrogate model is based on iteration sampling and extended radial basis function (ERBF). This method improves the precision by a means that new sample points is placed in the blank area and all the sample points is uniformly distributed in the design region. The precision of the surrogate model is checked using standard error measure to determine whether updating the surrogate model or not. Since the prediction of modal frequencies require structure modal simulations. In order to decrease the number of computer simulations, a Multi-Island GA approach is combined with the adaptive surrogate model to find the optimum modal frequencies of a strapdown inertial navigation system for electric helicopters. The strapdown inertial navigation system is comprised of damping material, counterweight material and inertial navigation sensor. This is a multi-objective functions optimization problem since the modal frequencies are considered from mode 1 to mode 6 in this paper. Several weights of multi-objective functions are utilized to research the modal frequencies. The whole number of 15 sampling points is picked to build the primary surrogate model using Latin hypercube sampling (LHS). The results of adaptive surrogate model show that two new sampling points are needed to reform the precision of the surrogate model under the condition of 2 % confidence bounds. The structure modal optimization results show that the choice of the weights for the multi-objective functions has a major effect on the final optimum modal frequencies. Time- and frequency-domain analysis indicated that the optimum modal frequencies are far away from the excitation frequencies to avoid strapdown inertial navigation system resonance as far as possible

Drug Target Prediction Based on the Herbs Components: The Study on the Multitargets Pharmacological Mechanism of Qishenkeli Acting on the Coronary Heart Disease

In this paper, we present a case study of Qishenkeli (QSKL) to research TCM's underlying molecular mechanism, based on drug target prediction and analyses of TCM chemical components and following experimental validation. First, after determining the compositive compounds of QSKL, we use drugCIPHER-CS to predict their potential drug targets. These potential targets are significantly enriched with known cardiovascular disease-related drug targets. Then we find these potential drug targets are significantly enriched in the biological processes of neuroactive ligand-receptor interaction, aminoacyl-tRNA biosynthesis, calcium signaling pathway, glycine, serine and threonine metabolism, and renin-angiotensin system (RAAS), and so on. Then, animal model of coronary heart disease (CHD) induced by left anterior descending coronary artery ligation is applied to validate predicted pathway. RAAS pathway is selected as an example, and the results show that QSKL has effect on both rennin and angiotensin II receptor (AT1R), which eventually down regulates the angiotensin II (AngII). Bioinformatics combing with experiment verification can provide a credible and objective method to understand the complicated multitargets mechanism for Chinese herbal formula

Metabolomics-Based Study of Clinical and Animal Plasma Samples in Coronary Heart Disease with Blood Stasis Syndrome

The aim of this study is to explore a bridge connecting the mechanism basis and macro syndromes of coronary heart disease with experimental animal models. GC-MS technique was used to detect the metabolites of plasma samples in mini swine models with myocardial infarction (MI) and patients with unstable angina (UA). 30 metabolites were detected in the plasma samples of more than 50 percent of model group and control group in swine, while 37 metabolites were found in the plasma samples of UA patients and healthy control group. 21 metabolites in the plasma samples of swine model and 20 metabolites in patients with UA were found of significant value. Among which, 8 shared metabolites were found of low level expression in both swine model and UA patients. Independent Student's t-test, principal component analysis (PCA), and hierarchicalcluster analysis (HCA) were orderly applied to comprehend inner rules of variables in the data. The 8 shared metabolites could take place of the 21 or 20 metabolites in classification of swine model with MI and UA patients, which could be considered as a bridge connecting the mechanism basis and macrosyndromes of swine model with MI and UA patients

Role of A20 in cIAP-2 Protection against Tumor Necrosis Factor α (TNF-α)-Mediated Apoptosis in Endothelial Cells

Tumor necrosis factor α (TNF-α) influences endothelial cell viability by altering the regulatory molecules involved in induction or suppression of apoptosis. However, the underlying mechanisms are still not completely understood. In this study, we demonstrated that A20 (also known as TNFAIP3, tumor necrosis factor α-induced protein 3, and an anti-apoptotic protein) regulates the inhibitor of apoptosis protein-2 (cIAP-2) expression upon TNF-α induction in endothelial cells. Inhibition of A20 expression by its siRNA resulted in attenuating expression of TNF-α-induced cIAP-2, yet not cIAP-1 or XIAP. A20-induced cIAP-2 expression can be blocked by the inhibition of phosphatidyl inositol-3 kinase (PI3-K), but not nuclear factor (NF)-κB, while concomitantly increasing the number of endothelial apoptotic cells and caspase 3 activation. Moreover, TNF-α-mediated induction of apoptosis was enhanced by A20 inhibition, which could be rescued by cIAP-2. Taken together, these results identify A20 as a cytoprotective factor involved in cIAP-2 inhibitory pathway of TNF-α-induced apoptosis. This is consistent with the idea that endothelial cell viability is dependent on interactions between inducers and suppressors of apoptosis, susceptible to modulation by TNF-α

An empirical study of dynamic triobjective optimisation problems

Dynamic multiobjective optimisation deals with multiobjective problems whose objective functions, search spaces, or constraints are time-varying during the optimisation process. Due to wide presence in real-world applications, dynamic multiobjective problems (DMOPs) have been increasingly studied in recent years. Whilst most studies concentrated on DMOPs with only two objectives, there is little work on more objectives. This paper presents an empirical investigation of evolutionary algorithms for three-objective dynamic problems. Experimental studies show that all the evolutionary algorithms tested in this paper encounter performance degradedness to some extent. Amongst these algorithms, the multipopulation based change handling mechanism is generally more robust for a larger number of objectives, but has difficulty in deal with time-varying deceptive characteristics