Distribution of properties from sampling inhomogeneous materials by line transects

A theory related to the statistics of the structure and properties of inhomogeneous materials has been proposed, dealing with the distribution of properties from sampling of inhomogeneous structures by line transects. It is demonstrated that the empirical cumulative distribution functions of the intercepts from the microstructural constituents and their variances are important fingerprints of the inhomogeneous structures.Simulated sampling of the images of the microstructure by line transects has been proposed as a powerful method for characterization the distribution of properties of inhomogeneous structures. One of the advantages of the method based on the expected values of the order statistics of the intercepts is that the probability bounds of the property are determined without prior knowledge of the functional relationship between the property and the intercepts from the structural constituents.The concept intercept variance has an important application in determining the minimum transect length that stabilizes the variation of the intercept at a low value. Additionally, the concept ‘intercept variance’ can be used for topological optimization of the microstructure regarding the risk of intercepting a large amount of the weaker constituent. Equations regarding the variance of the intercepted fraction characterizing transect lengths with a specified distribution have also been derived.     

十二酰胺丙基二甲基羟乙基氯化铵与十二烷基硫酸钠水溶液的表面吸附和胶束形成

利用十二酰胺丙基二甲胺和氯乙醇反应 ,合成了十二酰胺丙基二甲基羟乙基氯化铵 (DDHA)阳离子表面活性剂 ,将其与十二烷基硫酸钠 (SDS)以不同摩尔比进行混合 ,测定了混合系统的表面张力 ,计算了单一系统和混合系统的饱和吸附量、分子最小截面积 ,表面层和胶束中 DDHA的摩尔分率及分子间相互作用参数 ,目视观察了混合系统的浑浊情况。结果表明 :在降低γcmc和 cmc方面 ,DDHA SDS混合系统有协同效应 ,表面层和胶束的组成与二组分配比有关 ,但是非对称的 ,等物质的量混合物中 ,DDHA在胶束和表面层中具有较大的摩尔分数。DDHA与 SDS在实验测定的各混合系统中都不出现混浊     

Study of liquid injection impact on the performance of new refrigerant mixtures

In this paper, the test results of liquid injection impact on the performance of new alternative refrigerant mixtures such as: R-410A, R-507, R-407C and R-404A are discussed, analysed and presented. The test results were obtained using an air-source heat pump set-up with enhanced surface tubing under various liquid injection ratios. Performance tests were conducted according to the ARI/ASHRAE standards. The performance data demonstrated that as liquid injection ratio increases, compressor head pressure and discharge temperature decrease. This has a positive effect in protecting the compressor. The effect of liquid injection on mixture behaviour varies from one mixture to another depending upon the mixture's composition. Furthermore, liquid injection appears to have a significant influence on R-410A behaviour compared to the other mixtures in question. Copyright © 2002 John Wiley & Sons, Ltd.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

Ionothermal synthesis of a three-dimensional zinc phosphate with DFT topology using unstable deep-eutectic solvent as template-delivery agent

A three-dimensional zinc phosphate compound with DFT topology, designated as ZnPO₄-EU1, has been synthesized by an ionothermal approach from the system HF-ZnO–P₂O₅-choline chloride-imidazolidone. Ethylenediamine, derived from decomposition of the imidazolidone component of the deep-eutectic solvent (DES) itself, is delivered to the synthesis and serves as an appropriate template for ZnPO₄-EU1. Experiments in which the synthesis conditions were varied showed that ZnPO₄-EU1 may be prepared over a wide molar ratio of P/Zn = 0.55–13.0. Powder X-ray diffraction patterns have been obtained at intervals to track the crystallization process of this material. The experimental data show that Zn₃(PO₄)₂ · 4H₂O (a dense phase) was first isolated from the DES after reaction for 1 h. Subsequently, the pure phase of ZnPO₄-EU1 was obtained with increasing crystallization time from 12 h to 72 h. The experimental results show that the nucleation and crystallization take place with relatively low levels of solvent degradation, demonstrating that zinc phosphate with a three-dimensional framework can be synthesized by in situ generation of an appropriate template using an unstable DES at high temperatures (150–200 °C).     

Configurational and nonconfigurational interactions between odorants in binary mixtures.

Studies on odor mixture perception suggest that although odor components can often be identified in mixtures, mixtures can also give rise to novel perceptual qualities that are not present in the components. Using an olfactory habituation task, the authors evaluated how the perceptual similarity between components in a mixture affects the perceptual quality of the mixture itself. Rats perceived binary mixtures composed of similar components as different from their 2 components, whereas binary mixtures composed of dissimilar components were perceived as very similar to their components. Results show that for both types of mixtures, pretraining to Component A reduces subsequent learning about Component B in rats trained in the presence of A. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Impact of uncertainties on estimations of heat pump cycle performance

Sensitivity analysis is used to show how uncertainties in basic factors, such as heat transfer, pressure drop, compressor efficiency, and thermophysical properties, influence the result of heat pump cycle performance estimations. By comparing the results of this analysis with uncertainty levels of estimations and experimental determinations, it is established to what extent improvements in accuracy are needed. The investigation was carried out for several different applications and, as working fluids, both pure substances and non-azeotropic mixtures were examined. It was found that evaporation heat transfer and compressor efficiency are two areas where improvements are needed. It is also shown that estimates using very accurate, substance-specific, equations of state differ from those using more general types by up to 1 % for COP and 2% for capacity.     

Remote sensing of species mixtures in conifer plantations using LiDAR height and intensity data

In even-aged, single species conifer plantations LiDAR height data can be modelled to provide accurate estimates of tree height and volume. However, it is apparent that growth models developed for single species stands are not directly transferable to a more general situation of mixed species plantations. This paper evaluates the ability of small footprint, dual-return, pulsed airborne LiDAR data to estimate the proportion of the productive species when mixed with a nurse crop in closed canopy plantations. A study area located in Galloway Forest District in Scotland is used as an example of Lodgepole pine and Sitka spruce mixed plantation; this area contains good examples of a wide range of pure and mixed species plantation types. Three species groups are studied: areas of pure Sitka spruce, areas of pure Lodgepole pine and areas where the two species have been planted together. Two approaches are assessed for detection of plantation mixtures: the first uses LiDAR intensity data to separate spruce and pine species and the second uses LiDAR-derived canopy density measures, coefficient of variation, skewness, percent of ground returns (which provides a measure of canopy openness) and the mean canopy height, which enables areas with height variations to be identified. From analysis of LiDAR data extracted from 54 study plots using logistic regression, the coefficient of variation and LiDAR intensity data provide the most useful predictors of the proportion of spruce in a pine/spruce mixture with coefficients of determination (R²) of 0.914 and 0.930 respectively. The method could be developed as a mapping tool, which in combination with existing inventory data should help to improve timber volume forecasting for mixed species even-aged plantations.     

Analytic methods for modeling longitudinal data from rolling therapy groups with membership turnover.

Interventions for a variety of emotional and behavioral problems are commonly delivered in the context of treatment groups, with many using rolling admission to sustain membership (i.e., admission, dropout, and discharge from group are perpetual and ongoing). The authors present an overview of the analytic challenges inherent in rolling group data and outline commonly used (but flawed) analytic and design approaches to addressing (or sidestepping) these issues. Moreover, the authors propose use of latent class pattern mixture models (LCPMMs) as a statistically and conceptually defensible approach for modeling treatment data from rolling groups. The LCPMM approach is illustrated with rolling group data from a group-based alcoholism pilot treatment trial (N = 128). Different inferences were made with regard to treatment efficacy under LCPMM vs. the commonly used standard group-clustered latent growth model (LGM); coupled with other preliminary findings in this area, inferences from LGMs may be overly liberal when applied to data from rolling groups. Continued work on data analytic difficulties in groups with membership turnover is critical for furthering the ecological validity of research on behavioral treatments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Granular gases in mechanical engineering: on the origin of heterogeneous ultrasonic shot peening

The behavior of an ultrasonic shot peening process is observed and analyzed by using a model of inelastic hard spheres in a gravitational field that are fluidized by a vibrating bottom wall (sonotrode) in a cylindrical chamber. A marked heterogeneous distribution of impacts appears when the collision between the shot and the side wall becomes inelastic with constant dissipation. This effect is one order of magnitude larger than the simple heterogeneity arising from boundary collision on the cylinder. Variable restitution coefficients bring the simulation closer to the general observation and allow the investigation of peening regimes with changing shot density. We compute within this model other physical quantities (impact velocities, impact angle, temperature and density profile) that are influenced by the number N of spheres.