Characterization and Comparison of Free Fatty Acid Profiles of Eleven Varieties of Turkish Cheeses

Free fatty acids profiles of 11 different cheese varieties sold in Turkey were determined to assess the development of lipolysis. Results obtained showed that the concentrations of short chain fatty acids (C₄ and C₆ free fatty acids) were close in all cheeses (P > 0.05), except for Canak cheese. However, significant differences were noted among the samples for other free fatty acids including C₈ to C_18:2 (P < 0.05). Palmitic (C₁₆) and oleic (C_18:1) acids were the most abundant free fatty acids in all cheese samples. Principal component analysis was applied to simplify interpretation of the data and distinguish the variety of the cheeses on the plot. Canak cheese gave a dramatically different free fatty acid profile from the other cheeses, probably because of the fact that ripening of this variety is achieved in the earthenware pots for about 1 year. Van Otlu (ripened with special herbs) and Civil (ripened by spontaneously molding on its surface) cheeses differed from the others by ANOVA and principal component analysis techniques. In conclusion, the degree of lipolysis in the cheeses could be classified into extreme (Canak), high (Civil, Divle Tulum, Mihalic, and Van Otlu), mild (Ezine, Orgu, and Urfa), and low (Dil, Hellim, and Malatya) based on their FFA profiles.     

Performance of Single and Multi-stage Spouted Bed Drying Systems

A mathematical model is developed to predict the performance of single-stage and multi-stage drying systems using spouted beds. The model uses unsteady state analysis for batch operation to simulate the steady state operation of a continuously fed spouted bed. A parametric study is carried out to study the effect of the following parameters on the performance of a single-stage grain drying system: air flow rate per unit mass of the grain in the bed, ambient air temperature and humidity, initial and target moisture contents, the residence time in the bed, and the effectiveness of the heat exchanger to recover the thermal energy in the exhaust air. The parametric study is also extended to investigate the effect of these parameters (except ambient air temperature and humidity) on the performance of the multi-stage system. In addition, the number of stages is also included in the latter study. The results are presented in terms of charts which may be adopted for the design of such systems.     

Seawater Pretreatment by Microfiltration: An Economic Assessment

This paper conducts cost and economic analyses of the microfiltration system (MFS) seawater pretreatment technique for reverse osmosis (RO) application. The study is based on operational results from an RO plant in Kuwait and, for the sake of comparability, the analysis follows the same approach as the earlier studies that evaluated the cost-effectiveness of alternative techniques. The analysis shows that the MFS is as cost-effective as the beachwell system, which gives substantial cost savings compared with the conventional surface system.     

Introduction

Multibody System Dynamics -     

Acute compartment syndrome of the thigh after joint replacement with anticoagulation

We describe three patients with a compartment syndrome of the thigh, two after total hip replacement and one after total knee replacement. Two of the patients were fully anticoagulated. A compartment syndrome of the thigh is a rare, but important complication of joint replacement surgery if patients are receiving anticoagulants. Close observation is needed and when indicated monitoring of the intracompartmental pressure should be done. Early recognition of the signs and symptoms of an acute compartment syndrome and knowledge of the anatomy of the compartments of the thigh will help in the diagnosis and treatment of this potentially devastating complication.     

Steady supersonic flow-field predictions using proper orthogonal decomposition technique

In the present study, the proper orthogonal decomposition (POD) approach is coupled with the interpolation-extrapolation and the marching extrapolation procedure to predict the steady supersonic flow field by ensembling the data obtained from the numerical simulations. The procedure developed, uses an ensemble data for a given parametric variation and then it is applied to predict the steady flow field that has not been included in the parametric variations. The problem of axisymmetric surface-mounted triangular protuberance is used to demonstrate the efficiency and the accuracy of the proposed strategy. The Mach number and the protuberance height are used as the two parameters, for which the POD snapshots are collected by varying these parameters in the specified interval. The direct POD interpolation procedure performs accurately and efficiently when the flow field is reconstructed for the parameter whose value lies inside the snapshot ensembling interval. In order to predict the flow field outside the snapshot ensembling interval the direct POD extrapolation procedure is used. It is found that, in order to predict the complete supersonic steady-state flow field accurately, using POD interpolation or extrapolation procedure, the RMS deviations in the components of the reconstructed field from the ensembled data should be <1%. The direct POD extrapolation procedure is quite accurate near the ensembling interval but the predictions are inaccurate as one moves farther from the ensembling interval. A marching POD extrapolation (MPODE) procedure is also suggested which results in ameliorating the overall RMS error by 50% compared with the direct POD extrapolation procedure.     

An efficient approach for computing non‐Gaussian ARMA model coefficients using Pisarenko's method

This paper addresses the problem of estimating the coefficients of a general autoregressive moving average (ARMA) model from only third order cumulants (TOCs) of the noisy observations of the system output. The observed signal may be corrupted by additive coloured Gaussian noise. The system is driven by a zero‐mean independent and identically distributed (i.i.d.) non‐Gaussian sequence. The input is not observed. The unknown model coefficients are obtained using eigenvalue–eigenvector decomposition. The derivation of this procedure is an extension of Pisarenko harmonic autocorrelation‐based (PHA) method to third order statistics. It will be shown that the desired ARMA coefficients vector corresponds to the eigenvector associated with the minimum eigenvalue of a data covariance matrix of TOCs. The proposed method is also compared with well‐known algorithms as well as with the PHA method. Copyright © 2005 John Wiley & Sons, Ltd.     

A regression analysis of the effect of energy use in agriculture

This study investigates the impacts of energy use on productivity of Turkey's agriculture. It reports the results of a regression analysis of the relationship between energy use and agricultural productivity. The study is based on the analysis of the yearbook data for the period 1971–2003.

Agricultural productivity was specified as a function of its energy consumption (TOE) and gross additions of fixed assets during the year. Least square (LS) was employed to estimate equation parameters. The data of this study comes from the State Institute of Statistics (SIS) and The Ministry of Energy of Turkey.     

Study of the reliability of a binary symmetric channel under non‐Gaussian disturbances

The field of digital and data communications is becoming increasingly dominant because digital transmission offers data processing options and flexibilities not available with analog transmission. The main feature of a digital communication system is that during a finite interval of time, it sends a waveform from a finite set of possible waveform. One of the most important and fundamental models of communications channels is the binary symmetric channel (BSC). An important measure of system performance in a digital communication system is the probability of error. In this paper, the probability of error, the reliability, the entropy and the channel capacity of a BSC model are studied under non‐Gaussian noise disturbances. Namely, Cauchy, Laplace and logistic distributions are considered. It is found that the reliability of the signaling system is low under non‐Gaussian noise distributions compared to the Gaussian noise distribution. Several methods were used to reduce the error probability. The amount of improvement in reliability using the reduction methods is higher in the case of Gaussian noise. In order to achieve high reliability under non‐Gaussian noise distribution, it is required to increase signal‐to‐noise ratio (SNR) and increase number of repetitions when sending the same signal different times. Finally, it is observed that increasing the reliability for Cauchy distribution noise has totally failed based on sending the same signal different times and summing the received signals. Copyright © 2003 John Wiley & Sons, Ltd.