Endogenous and copper-induced lipid peroxidation and antioxidant activity of serum in hypercholesterolemic subjects

In order to observe the transport ability of peritoneum to small molecular substances, peritoneal equilibration test (PET) was performed in 52 CAPD patients. By analysing the relationship between peritoneal transport function and dialysis adequacy, we found the average urea KT/V and Cr were significantly lower in high and low transport groups (n = 6 and n = 2) than in high average and low average groups (n = 35 and n = 9). According to the results of PET, we adjusted the dialysis program of 11 patients and the dialysis adequacy was markedly improved. We concluded that PET was helpful for selecting and adjusting CAPD program, and discussed some questions which should be payed more attention in PET operation.     

The Influence of Surfactant on the Surface Characterization of Celestite in Spherical Oil Agglomeration

This study investigates the relationship between the critical surface tension of wetting of celestite and agglomeration recovery as well as the zeta potential in dependence of pH and amount of collector (Na‐Oleate). For this purpose, effects of pH and collector amount on the agglomeration recovery are investigated and zeta potential measurements and Fourier Transform Infrared Spectrophotometer (FTIR) analyses are carried out to determine the adsorption type of Na‐Oleate on celestite surface. The sessile drop technique is used for the measurement of contact angle and determination of the critical surface tension of wetting (Y_C) of celestite. The maximum agglomeration recovery is obtained at pH 7. The critical surface tension of wetting of celestite is very close to the surface tension of kerosene, which is 25.95 mN/m. Furthermore, at the optimum Na‐Oleate amount of 10 kg/ton, the critical surface tension of wetting of celestite is approximately equal to the surface tension of kerosene.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

Use of Warranties on Highway Projects: A Real Option Perspective

Since the introduction of warranty provisions in federal highway jobs, more and more state departments of transportation (DOTs) have considered the use of such provisions to protect their initial investment. This paper describes the pros and cons of warranty contracting in highway construction based on a survey of warranty practices in the United States. In particular, the need for state DOTs to buy a warranty for a well-built project is questioned. As an alternative, this paper introduces the warranty option, which gives the DOT the right to buy a warranty only if it becomes necessary at the end of construction. This option is exercised if the performance on site warrants it. This paper describes the mechanics of the warranty option and its advantages over the conventional warranty. A bid evaluation model is also developed for the warranty option approach.     

Methacrylic acid–acrylamide-g-poly(ethyleneterephthalate) fibres for urea hydrolysis

This paper presents the results of urease immobilization onto methacrylic acid–acrylamide grafted poly(ethyleneterephthalate) fibres. The graft yield strongly affected the maximum activity of the immobilized enzyme up to a value of 70·2%. Higher grafting caused a decline in urease activity and led to the degradation of the fibres. The minor changes observed in K_m and V_max demonstrated that the conformational changes existed during immobilization were not extensive. However, 70·2% methacrylic acid–acrylamide-g-fibres containing urease were more stable towards acidic and alkaline pH, high temperature and storage conditions compared with free enzyme. Apart from the increase in stability to heat inactivation, the initial enzymatic activity of the urease–fibre system remained almost unchanged even after 40 repeated assays corresponding to 10 h of operation in 4 months, indicating the excellent durability of the system.     

Extracting trust information from security system of a service

The issue of trust is a research problem in emerging open environments, such as ubiquitous networks. Such environments are highly dynamic and they contain diverse number of services and autonomous entities. Entities in open environments have different security needs from services. Trust computations related to the security systems of services necessitate information that meets needs of each entity. Obtaining such information is a challenging issue for entities. In this paper, we propose a model for extracting trust information from the security system of a service based on the needs of an entity. We formally represent security policies and security systems to extract trust information according to needs of an entity. The formal representation ensures an entity to extract trust information about a security property of a service and trust information about whole security system of the service. The proposed model is applied to Dental Clinic Patient Service as a case study with two scenarios. The scenarios are analyzed experimentally with simulations. The experimental evaluation shows that the proposed model provides trust information related to the security system of a service based on the needs of an entity and it is applicable in emerging open environments.     

A new ECG beat clustering method based on kernelized fuzzy c-means and hybrid ant colony optimization for continuous domains

The kernelized fuzzy c-means algorithm uses kernel methods to improve the clustering performance of the well known fuzzy c-means algorithm by mapping a given dataset into a higher dimensional space non-linearly. Thus, the newly obtained dataset is more likely to be linearly seprable. However, to further improve the clustering performance, an optimization method is required to overcome the drawbacks of the traditional algorithms such as, sensitivity to initialization, trapping into local minima and lack of prior knowledge for optimum paramaters of the kernel functions. In this paper, to overcome these drawbacks, a new clustering method based on kernelized fuzzy c-means algorithm and a recently proposed ant based optimization algorithm, hybrid ant colony optimization for continuous domains, is proposed. The proposed method is applied to a dataset which is obtained from MIT–BIH arrhythmia database. The dataset consists of six types of ECG beats including, Normal Beat (N), Premature Ventricular Contraction (PVC), Fusion of Ventricular and Normal Beat (F), Artrial Premature Beat (A), Right Bundle Branch Block Beat (R) and Fusion of Paced and Normal Beat (f). Four time domain features are extracted for each beat type and training and test sets are formed. After several experiments it is observed that the proposed method outperforms the traditional fuzzy c-means and kernelized fuzzy c-means algorithms.     

Optimum topology design of various geometrically nonlinear latticed domes using improved harmony search method

Domes are elegant and economical structures used in covering large areas. They are built in various forms. According to their form, they are given special names such as lamella, network, and geodesic domes. In this paper, optimum topological design algorithm is presented that determines the optimum number of rings, the optimum height of crown and tubular section designations for the member groups of these domes. The design algorithm developed has a routine that generates the data required for the geometry of these domes automatically. The minimum weight of each dome is taken as the objective function. The design constraints are implemented according to the provision of LRFD-AISC (Load and Resistance Factor Design–American Institute of Steel Constitution). The optimum topological design problem that considers these constraints turns out to be discrete programming problem. Improved harmony search algorithm is suggested to determine its optimum solution. The design algorithm also considers the geometric nonlinearity of these dome structures. Design examples are presented to demonstrate the effectiveness and robustness of the design optimization algorithm developed.