Phospholipids and oxophospholipids in atherosclerotic plaques at different stages of plaque development

We identified and quantified the hydroperoxides, hydroxides, epoxides, isoprostanes, and core aldehydes of the major phospholipids as the main components of the oxophospholipids (a total of 5–25 pmol/μmol phosphatidylcholine) in a comparative study of human atheroma from selected stages of lesion development. The developmental stages examined included fatty streak, fibrous plaque, necrotic core, and calcified tissue. The lipid analyses were performed by normal-phase HPLC with on-line electrospray MS using conventional total lipid extracts. There was great variability in the proportions of the various oxidation products and a lack of a general trend. Specifically, the early oxidation products (hydroperoxides and epoxides) of the glycerophosphocholines were found at the advanced stages of the plaques in nearly the same relative abundance as the more advanced oxidation products (core aldehydes and acids). The anticipated linear accumulation of the more stable oxidation products with progressive development of the atherosclerotic plaque was not apparent. It is therefore suggested that lipid infiltration and/or local peroxidation is a continuous process characterized by the formation and destruction of both early and advanced products of lipid oxidation at all times. The process of lipid deposition appears to have been subject to both enzymatic and chemical modification of the normal tissue lipids. Clearly, the appearance of new and disproportionate old lipid species excludes randomness in any accumulation of oxidized LDL lipids in atheroma.     

Objectification theory and deaf cultural identity attitudes: Roles in deaf women's eating disorder symptomatology.

This study examined the generalizability of direct and mediated links posited in objectification theory among internalization of sociocultural standards of beauty, body surveillance, body shame, and eating disorder symptoms with a sample of Deaf women. The study also examined the role of marginal Deaf cultural identity attitudes within this framework. Data from 177 Deaf women indicated positive relations among internalization, body surveillance, body shame, and eating disorder symptomatology. Consistent with tenets of objectification theory, body shame mediated the links of internalization and body surveillance with eating disorder symptoms. In addition, marginal Deaf identity attitudes (but not hearing, immersion, or bicultural attitudes) were linked uniquely with eating disorder constructs and had significant indirect relations through internalization with body surveillance, body shame, and eating disorder symptoms. Implications for practice and future research are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Concurrent control chart patterns recognition with singular spectrum analysis and support vector machine

Since abnormal control chart patterns (CCPs) are indicators of production processes being out-of-control, it is a critical task to recognize these patterns effectively based on process measurements. Most methods on CCP recognition assume that the process data only suffers from single type of unnatural pattern. In reality, the observed process data could be the combination of several basic patterns, which leads to severe performance degradations in these methods. To address this problem, some independent component analysis (ICA) based schemes have been proposed. However, some limitations are observed in these algorithms, such as lacking of the capability of monitoring univariate processes with only one key measurement, misclassifications caused by the inherent permutation and scaling ambiguities, and inconsistent solution. This paper proposes a novel hybrid approach based on singular spectrum analysis (SSA) and support vector machine (SVM) to identify concurrent CCPs. In the proposed method, the observed data is first separated by SSA into multiple basic components, and then these separated components are classified by SVM for pattern recognition. The scheme is suitable for univariate concurrent CCPs identification, and the results are stable since it does not have shortcomings found in the ICA-based schemes. Furthermore, it has good generalization performance of dealing with the small samples. Superior performance of the proposed algorithm is achieved in simulations.     

Neural Network Identification Based Multivariable Feedback Linearization Robust Control for a Two-Link Manipulator

Regarding to the variations of the load and unmodeled dynamic, robot manipulators are known as a nonlinear dynamic system. Overcoming such problems like uncertainties and nonlinear characteristics in the model of two-link manipulator is the principal goal of this paper. To approach to this aim, a neural network is combined with a linear robust control in which the result has the advantages of, the first, approximated nonlinear elements and the second, the guaranteed robustness. To design the proposed controller, at first, multivariable feedback linearization is employed to convert the nonlinear model to linear one. Second, the unknown parameters of the system are identified by neural network based on a new proposed learning rule. Third, Mixed linear feedback-H_?∞? robust control method is proposed to stabilize the closed loop system. The closed loop system based on the proposed controller is analyzed and some numerical simulations are performed. Results show suitable responses of the closed loop system.     

Genetic-based random key generator (GRKG): a new method for generating more-random keys for one-time pad cryptosystem

In this paper, a new algorithm for generating more-randomized keys for symmetrical cipher one-time pad (OTP) according to the linear congruential (LCG) method based on the idea of genetic algorithm is proposed. The method, genetic-based random key generator, is proposed for generating keys for the OTP method with a high degree of key randomness; this adds more strength to the OTP method against breaking this cryptosystem. This algorithm is composed of two parts. Initially, the first population is being generated by LCG method, and then, genetic operators for generating the next populations are being used. Generating random keys with the presented method requires seven-parameter key that increases the security of communication between the transceivers.     

Evaluation of MODIS data for improved monitoring of the Caspian Sea

Moderate-Resolution Imaging Spectroradiometer (MODIS) optical and infrared data are used to monitor changes in the Caspian Sea coastline. The information extracted from MODIS images is converted into total water volume and mean lake level by combining a digital elevation model (DEM) with remote-sensing data. The elevation estimates were enhanced by reprocessing the MODIS data at the sub-pixel scale. The water volume variations estimated from MODIS data along with DEM are compared to other estimations derived from altimetry data sets, and show fair agreement.     

Aging fingerprint characterization of beer using electronic nose

In this work, attempts were made in order to characterize the change of aroma of alcoholic and non alcoholic beers during the aging process by use of a metal oxide semiconductor based electronic nose. The aged beer samples were statistically characterized in several classes. Linear techniques as principal component analysis (PCA) and Linear Discriminant Analaysis (LDA) were performed over the data that revealed non alcoholic beer classes are separated except a partial overlapping between zones corresponding to two specified classes of the aged beers. A clear discrimination was not found among the alcoholic beer classes showing the more stability of such type of beer compared with non alcoholic beer. In this research, to classify the classes, two types of artificial neural networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Backpropagation (BP) learning method. The classification success was found to be 90% and 100% for alcoholic and non alcoholic beers, respectively. Application of PNN showed the classification accuracy of 83% and 100%, respectively for the aged alcoholic and non alcoholic beer classes as well. Finally, this study showed the capability of the electronic nose system for the evaluation of the aroma fingerprint changes in beer during the aging process.     

La-Si-O-N glasses: Part II: Vickers hardness and refractive index

Vickers hardness and refractive index have been determined for a series of La-Si-O-N oxy-nitride glasses containing 30–62 e/o of La and 9–68 e/o of N. The hardness varies between 7.7 and 11.5 GPa at a load of 1 kg and is dependent of the N content, while the La content does not influence it significantly. The increase of the hardness with N content is, contrary to reported findings for other oxy-nitride glasses, found not to be linear over the whole compositional range. The refractive index varies between 1.8 and 2.3 and increases non-linearly with increasing N content. The compositional variations of hardness and refractive index are compared with previously published results.     

Prediction of H2 Content and Inert Gas Circulation Rate Effects on Batch Annealing Process

Steel strip coils need to be annealed after they leave the cold-rolling process. The purpose of annealing is to improve steel strip formability and to remove residual internal stresses imparted during rolling. Simultaneous increase of circulation rate and inert gas hydrogen content may have considerable effects on reducing the annealing process time. A mathematical model was developed to obtain a more accurate evaluation of the effects of these two parameters on heating and cooling cycles in the annealing process. The results from the simulation of an ordinary annealing process by the proposed model were compared with values measured at site and the accuracy of the model was confirmed. Finally, the effects of increasing hydrogen content and circulation rate were investigated, first independently from each other and then simultaneously. The predictions by the model showed that reduction of annealing time would be considerable when both parameters were simultaneously increased.