Vibration suppression and dynamic behavior analysis of an axially loaded beam with NES and nonlinear elastic supports

Recently, dynamic analysis of a beam structure with nonlinear energy sink (NES) and various supports is attracting great attention. Most of the existing studies are about the beam structure with NES or nonlinear boundary supports with zero rotational restraint, respectively. However, there is little research accounting for such two types of complex factors simultaneously. In this work, the dynamic behavior of an axially loaded beam with both NES and general boundary supports is modeled and studied. The Galerkin truncated method (GTM) is employed to make the prediction of dynamic behavior of such a beam system, in which the mode functions of axially loaded Euler–Bernoulli beam with linear elastic boundary conditions are selected as the trail and weight functions. Then, the Galerkin condition is used to discretize the nonlinear governing equation of the beam system and establish the residual equations. The Runge–Kutta method is used to solve the residual matrix which consists of residual equations directly, and the harmonic balance method is also used to verify the results from the GTM. The influence of NES on vibration suppression and dynamic behavior of the beam structure is investigated and discussed. Results show that the vibration states of the beam structure can be transformed effectively through the change of NES parameters. On the other hand, the NES with suitable parameters has a beneficial effect on the vibration suppression at both ends of the beam structure.

A new LC–MS/MS method for multiple residues/contaminants in bovine meat

A multi-class and multi-residue/contaminant method for the determination of veterinary drug and pesticide residues and mycotoxins in bovine meat has been developed and validated. The veterinary drug residues/contaminants included antimicrobials, anabolic hormones, lactones, β-agonists, mycotoxins, and pesticides. Isotopic labeled internal standards were included to compensate residual matrix effects. The calibrators used in the method demonstrated linearity with the R2 > 0.98. The decision limit (CCα) values were in the range from 0.067 to 2103.84 μg/kg, while the range for detection capability (CCβ) was from 0.083 to 2482.13 μg/kg. The limit of detection (LOD) and limit of quantification (LOQ) were in the range from 0.059 to 291.36 μg/kg, and 0.081 to 328.13 μg/kg, respectively. The recovery of analytes ranged from 61.28% to 116.20%. The intra-day coefficient of variation (CV) was from 0.97 to 25.93% and the inter-day CV was 2.30–34.04%. The method has been used for the determination of 49 residues/contaminants in bovine meat. Application of the method in routine analysis in bovine samples, revealed in limited samples the presences of enrofloxacin, oxytetracycline and sulfadiazine at the concentration of 35.22 µg/kg, 27.35 µg/kg, and 36.20 µg/kg, respectively.

Biclustering Analysis Using Plaid Model on Gene Expression Data of Colon Cancer

Unlike other typical clustering analysis, which considers column only, biclustering analysis processes a matrix into sub-matrices based on rows and columns simultaneously. One method of bicluster analysis uses the probabilistic model, like the plaid model, that provides overlapping bicluster. The plaid model calculates the value of an element given from a particular sub-matrix for each cell; thus, the value can be seen as the number of contributions of a particular bicluster. The algorithm begins with preparing the input data as a matrix, then an initial model is assessed and makes a residual matrix from the model. After that, we determine bicluster candidates, which are evaluated for its effect parameters and bicluster membership parameters. Finally, the bicluster candidate is pruned to give the optimal bicluster. We implemented the algorithm on gene expression dataset of colon cancer, where the rows and columns contain observations and types of genes, respectively. We carried out in six distinct scenarios in which each scenario uses different model parameters and threshold values. We measured the results using Jaccard index and coherence variance. Our experiments show that biclustering analysis on a model with mean, row, and column effects of colon cancer data output low coherence variance.

Research on Vulnerability Identification Algorithm of Power Grid Based on Complex Network

This paper mainly studies the vulnerability of node combination of two kinds of networks, and verifies whether all networks can use the pinning control optimization point selection algorithm. One is the primitive network, in which the nodes correspond to the components in the power grid, and the other is the dual network, in which the nodes are mapped to the nodes of the dual model, It is mapped as an edge, and then the vulnerability of node combination is studied by containment control theory. In the experiment, IEEE57 nodes are used to study the original network, and different combination nodes are used to attack the original network to study the vulnerability. By studying the dual network with IEEE14 nodes, it is found that the eigenvalues of the residual matrix after deleting the control nodes are all zero. Therefore, the dual model of power grid can not use the pinning control theory, and it further shows that not any network can use the pinning control theory to select points.

A New Lc-Ms/Ms Method for Multiple Residues/Contaminants In Bovine Meat

A multi-class and multi-residue/contaminant method for the determination of veterinary drug and pesticide residues and mycotoxins in bovine meat has been developed and validated. The veterinary drug residues/contaminants included antimicrobials, anabolic hormones, lactones, β-agonists, mycotoxins, and pesticides. Isotopic labeled internal standards were included to compensate residual matrix effects. The calibrators used in the method demonstrated linearity with the coefficient of correlation (R2) > 0.98. The decision limit (CCα) values were in the range from 0.067 to 2103.84 μg/kg, while the range for detection capability (CCβ) was from 0.083 to 2482.13 μg/kg. The limit of detection (LOD) and limit of quantification (LOQ) were in the range from 0.059 to 291.36 μg/kg, and 0.081 to 328.13 μg/kg, respectively. The recovery of analytes ranged from 61.28 % to 116.20 %. The intra-day coefficient of variation (CV) was from 0.97 to 25.93 % and the inter-day CV was 2.30-34.04 %. The method has been used for the determination of 49 residues/contaminants in bovine meat.

Mechanism of powellite crystallite expansion within nano-phase separated amorphous matrices under Au-irradiation

Effects of Au-irradiation on synthesized multi-phase glass ceramics that have CaMoO4 crystallites within a residual matrix characterized by two Tgs.

Error bounds for augmented truncation approximations of Markov chains via the perturbation method

LetPbe the transition matrix of a positive recurrent Markov chain on the integers with invariant probability vectorπT, and let(n)P̃ be a stochastic matrix, formed by augmenting the entries of the (n+ 1) x (n+ 1) northwest corner truncation ofParbitrarily, with invariant probability vector(n)πT. We derive computableV-norm bounds on the error betweenπTand(n)πTin terms of the perturbation method from three different aspects: the Poisson equation, the residual matrix, and the norm ergodicity coefficient, which we prove to be effective by showing that they converge to 0 asntends to ∞ under suitable conditions. We illustrate our results through several examples. Comparing our error bounds with the ones of Tweedie (1998), we see that our bounds are more applicable and accurate. Moreover, we also consider possible extensions of our results to continuous-time Markov chains.