The Acceleration Severity Index in the impact of a vehicle against permanent road equipment support structures

The acceleration Severity Index (ASI), described in European Standard EN12767 (The passive safety of support structures for road equipment. Requirements, classification and the test method) is regarded as the most important indicator of impact on the occupants. The requirements for experiments are described, having in mind that the results depend on many factors. One of them is the selection of a vehicle to be used in the crash test. To perform numerical vehicle crash simulation, the finite-element models of permanent road equipment support structures were developed using the LS Dyna software available. To examine the response of the vehicle upon the impact, the acceleration severity index curves were calculated and visualised in Matlab.     

一类综合评价指数编制路径及案例

综合评价指数是一种广义上的统计指数,在讨论了综合评价指数与一般统计指数不同的基础上,引述了综合评价指数一般编制步骤并详细分析研究了综合评价指数编制过程中的权重确定,提出了基于等权设计思想的加权修正综合评价指数编制方法,最后以甘肃省装备制造产业为例进行了展示.     

Comparative molecular field analysis of chromatographic hydrophobicity indices for some coumarin analogs

The chromatographic hydrophobicity index (CHI) is an HPLC‐based parameter that provides reliable guidance in optimization of pharmacological efficiency and adsorption, distribution, metabolism and exertion (ADME) profile of drug candidates. In the present work, classical and three‐dimensional quantitative structure–property relationship (QSPR) models were developed for prediction of CHI values of some 4‐hydroxycoumarin analogs on immobilized artificial membrane column. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) as 3D–QSPR methods were performed to gain insight into the key structural factors affecting on the chromatographic hydrophobicity of interested chemicals. The calculated parameters of Q ², R ² and standard error were 0.545, 0.996 and 0.773 for CoMFA model and 0.815, 0.986 and 1.44 for CoMSIA model, respectively. The contour maps for steric fields of the CoMFA model illustrate that the hydrophobicity of chemicals will be higher when the positions of R6, R7 and R8 in the 4‐hydroxycuomarin ring are substituted by alkyl groups. Moreover, by the analysis of the plots of electrostatic fields, it was concluded that the CHI value greatly increases if one hydrogen on coumarin ring is substituted by the F, Cl, Br, OH or OCH₃ group.     

环状硅酸盐图的友好指数集

Let G be a graph with vertex set V(G) and edge set E(G). A labeling f : V(G) →Z2 induces an edge labeling f*: E(G) → Z2 defined by f*(xy) = f(x) + f(y), for each edge xy ∈ E(G). For i ∈ Z2, let vf(i) = |{v ∈ V(G) : f(v) = i}| and ef(i) = |{e ∈ E(G) : f*(e) =i}|. A labeling f of a graph G is said to be friendly if |vf(0)- vf(1)| ≤ 1. The friendly index set of the graph G, denoted FI(G), is defined as {|ef(0)- ef(1)|: the vertex labeling f is friendly}. This is a generalization of graph cordiality. We investigate the friendly index sets of cyclic silicates CS(n, m).     

Chemical-Modified Nylon 4 Membrane for Pervaporation

Abstract

A hydrophilic polymer membrane was synthesized with 2-hydroxyethyl methacrylate (HEMA) onto a Nylon 4 polymer backbone, PHEMA-g-N4. The membranes were water permselective because of the hydrophilicity, and the water permselectivity increased with increasing the degree of grafting. Permseparation of water was investigated with respect to the feed aqueous alcohol concentration, feed temperature, size of the alcohols, and degree of grafting. The separation factors of this PHEMA-g-N4 membrane were higher than those of the unmodified Nylon 4 membrane for pervaporation of aqueous ethanol solution, while the permeation rate was slightly lower. A separation factor of 98 and a 194 g/m²·h permeation rate could be obtained. Compared with an unmodified Nylon 4 membrane, the PHEMA-g-N4 membrane effectively increased the pervaporation separation index for the water-ethanol mixtures on pervaporation separation.     

Functions of Acyclic Poly(ethylene Oxide) Homologs: Acceleration of Nucleophilic Reactions and Selective Ion Transport through Membranes

The acceleration effect of poly(ethylene oxide) on nucleophilic reactions was investigated. The enhancement of the reaction rate was interpreted by the cooperative solvation of alkali metal ions with ethereal oxygens of PEO resulting in active nucleophilic anions. In relation to the complex formation of alkali metal ions with PEO, the oligo(ethylene oxide) derivatives were prepared as the synthetic ionophores, which were able to transport alkali metal ions selectively through a liquid membrane against the alkali metal ion concentration.     

Miscibility Studies of Dextran/Poly(vinyl pyrrolidone) Blend in Solution

The miscibility of dextran (Dex)/poly(vinyl pyrrolidone) (PVP) in solution has been investigated in different percentages of the blend components by employing viscosity, density, refractive index and ultrasonic velocity methods at 30 and 50°C, respectively. Ultrasonic velocity and adiabatic compressibility against blend compositions were plotted and found to be linear. The interaction parameters μ and α have been obtained by using the viscosity data. The results indicated that the Dex/PVP blends are miscible in the entire composition range and it was further confirmed by ultrasonic velocity, density, refractive index studies. In addition, the results revealed that the change in temperature has no significant effect on the miscibility of Dex/PVP polymer blend.     

Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain

The rivality index (RI) is a normalized distance measurement between a molecule and their first nearest neighbours providing a robust prediction of the activity of a molecule based on the known activity of their nearest neighbours. Negative values of the RI describe molecules that would be correctly classified by a statistic algorithm and, vice versa, positive values of this index describe those molecules detected as outliers by the classification algorithms. In this paper, we have described a classification algorithm based on the RI and we have proposed four weighted schemes (kernels) for its calculation based on the measuring of different characteristics of the neighbourhood of molecules for each molecule of the dataset at established values of the threshold of neighbours. The results obtained have demonstrated that the proposed classification algorithm, based on the RI, generates more reliable and robust classification models than many of the more used and well-known machine learning algorithms. These results have been validated and corroborated by using 20 balanced and unbalanced benchmark datasets of different sizes and modelability. The classification models generated provide valuable information about the molecules of the dataset, the applicability domain of the models and the reliability of the predictions.