Biodiesel (FAME) Productivity,Catalytic Efficiency and Thermal Stability of Lipozyme TL IM for Crude Palm Oil Transesterification with Methanol

Crude palm oil (CPO) transesterification with methanol at room temperature is an important factor for optimizing biodiesel processing costs with respect to energy input; in addition, good stability of expensive lipase activity was ensured and is reported in this study. The enzyme loading, agitation speed and reaction time at a constant operating temperature of 30 °C were studied to find favourable operational conditions using a factorial design. Statistical analysis was used to assist the enzymatic transesterification so that a reduced mass transfer effect was achieved to obtain high FAME yields. The combination of optimum enzyme loading of 6.67 wt% and 150 rpm agitation speed for the system at 30 °C gave 81.73% FAME yield at 4 h and a production rate of 85.86% FAME yield/h. The high viscosity of CPO observed at 30 °C compared to 40 °C hindered the achievement of 96.15% FAME yield at room temperature. It was found that an increase of 10 °C invariably deactivated the lipase, but was compensated by the enhanced FAME production rate with 96.15% FAME yield after only 4 h reaction time. Thus, 40 °C was considered the most suitable operating temperature for lipozyme TL IM to catalyze CPO transesterification.     

Characterization of Turkish Virgin Olive Oils Produced from Early Harvest Olives

Olives were collected from various districts of Turkey (North and South Aegean sub-region, Bursa-Akhisar, South East Anatolia region) harvested over seven (2001–2007) seasons. The aim of this study was to characterize the chemical profiles of the oils derived from single variety Turkish olives including Ayvalik, Memecik, Gemlik, Erkence, Nizip Yaglik and Uslu. The olive oils were extracted by super press and three phase centrifugation from early harvest olives. Chosen quality indices included free fatty acid content (FFA), peroxide value (PV) and spectrophotometric characteristics in the ultraviolet (UV) region. According to the FFA results, 46% (11 out of 24 samples) were classified as extra virgin olive oils; whereas using the results of PV and UV, over 83% (over 19 of the 24 samples) had the extra virgin olive oil classification. Other measured parameters included oil stability (oxidative stability, chlorophyll pigment, pheophytin-α), cis–trans fatty acid composition and color index. Oxidative stability among oils differed whereas the cis–trans fatty acid values were within the national and international averages. Through the application of two multivariate statistical methods, Principal component and hierarchical analyses, early harvest virgin olive oil samples were classified according to the geographical locations categorized in terms of fatty acid profiles. Such statistical clustering gave rise to defined groups. These data provide evidence of the variation in virgin olive oil quality, especially early harvest and cis–trans isomers of fatty acid profiles from the diverse agronomic conditions in the olive growing regions of Turkey.     

Detection of heart valve diseases by using fuzzy discrete hidden Markov model

In the present study, biomedical based application was developed to classify the data belongs to normal and abnormal samples generated by Doppler ultrasound. This study consists of raw data obtaining and pre-processing, feature extraction and classification steps. In the pre-processing step, a high-pass filter, white de-noising and normalization were used. During the feature extraction step, wavelet entropy was applied by wavelet transform and short time fourier transform. Obtained features were classified by fuzzy discrete hidden Markov model (FDHMM). For this purpose, a FDHMM that consists of Sugeno and Choquet integrals and λ fuzzy measurement was defined to eliminate statistical dependence assumptions to increase the performance and to have better flexibility. Moreover, Sugeno integral was used together with triangular norms that are mentioned frequently in the literature in order to increase the performance. Experimental results show that recognition rate obtained by Sugeno fuzzy integral with triangular norm is more successful than recognition rates obtained by standard discrete HMM (DHMM) and Choquet integral based FDHMM. In addition to this, it is shown in this study that the performance of the Sugeno integral based method is better than the performances of artificial neural network (ANN) and HMM based classification systems that were used in previous studies of the authors.     

Quantum coherence effects in a Raman amplifier

We have studied optical pulse propagation in a Raman fiber amplifier doped with a three-level medium and driven by a control laser pulse. We analyze the spatial-temporal dynamics of pulse propagation for different atomic initial conditions. The propagation of an optical pulse through the amplifier can be sustained by a control laser that induces transparency via quantum coherence, which is useful for extending the distance between optical repeaters. Under certain conditions, amplification is achieved without population inversion. The results could be useful for laser control of optical pulses in amplifiers and waveguides.     

O-band to C-band wavelength converter by using four-wave mixing effect in 1310 nm SOA

In this paper we provide a detailed account of an ultra-wideband wavelength converter that shifts from 1310 to 1550?nm using a 1310?nm semiconductor optical amplifier as the nonlinear medium. The experimental approach uses an arrayed waveguide grating (AWG) as a method to slice the broadband output ASE of the 1310?nm SOA into multiple outputs at this O-band. A four-wave mixing technique is used to generate the wavelength conversion, whereby two wavelengths at 1310?nm are used and interact with the 1550?nm continuous wave output from a bismuth-based erbium-doped optical amplifier. In this demonstration, the interacting wavelengths are 1316.75, 1317.47 and 1542.21?nm. The downward conversion wavelengths are 1542.93 and 1541.49?nm, with a converted wavelength spacing of 224?nm.     

Double spacing multi-wavelength L-band Brillouin erbium fiber laser with Raman pump

A new multi-wavelength Brillouin erbium fiber laser (BEFL), which operates in the L-band region with double frequency Brillouin spacing, is demonstrated. This design uses a Raman pump (RP) and a piece of 2?km highly nonlinear fiber as a gain medium. The double frequency spacing is achieved by employing a dual ring configuration, which is formed by utilizing a four-port circulator that removes the odd-order Stoke signals. Twenty Stokes and seventeen anti-Stokes lines, which have optical signal to noise ratio (OSNR) greater than 15?dB, are generated simultaneously with a spacing of 0.16?nm when Brillouin pump and RP powers were fixed at the optimum values of 8 dBm and 40?mW, respectively. The BEFL can be tuned in the range between 1591?nm to 1618?nm. The proposed configuration increases the number of lines generated and the OSNR, and thus allows a compact multi-wavelength laser source to be realized.     

Tribological Properties of TiO<Subscript>2</Subscript> Reinforced Nickel Based MMCs Produced by Pulse Electrodeposition Technique

Nickel–TiO₂ composite coatings were prepared under pulse current conditions by co-deposition of TiO₂ particles and nickel from a Watts type bath. The effect of TiO₂ particle concentration was studied on microhardness, friction coefficient and wear resistance. The morphological features and the structures were studied by scanning electron microscope, X-ray diffraction analysis and 3D profilometry facilities. A wide particle size range (between 95 and 140 nm) was chosen to provide a high dispersion and load bearing ability for the co-deposited layers. It was determined that increasing the particle concentration in the electrolyte dramatically increased the co-deposited TiO₂ particles in the coating. The results showed that the high concentration of TiO₂ particles in the electrolyte yielded the highest amount of particles co-deposited in the plating layer. The influence of the co-deposited TiO₂ volume on microstructure and tribological properties in the coating were investigated. The wear tests were carried out using a constant load by a reciprocating ball-on disk configuration. Wear loss and friction coefficients of Ni/TiO₂ composites were decreased by increasing TiO₂ content in the electrolyte because of the increasing content of TiO₂ in the deposited layer. The change in wear mechanisms by changing TiO₂ content was also determined.     

Bovine spongiform encephalopathy in Germany

Bovine spongiform encephalopathy (BSE) has been described as an epidemic central nervous disorder in cattle from the United Kingdom. The disease is thought to have emerged by an interspecies transmission of the scrapie agent of sheep to cattle, after feeding scrapie-contaminated meat and bone meal (MBM). The disease has caused substantial economic losses for the British cattle industry. Because of strict veterinary regulations for the import of adult British cattle by the European Union and for MBM by most of the member states the spread of BSE to continental Europe could be efficiently controlled, and only few cases have been described outside the UK. Here we report the first German case of BSE diagnosed in a Scottish Highland cow. The affected cow was imported into Germany before the import ban for cattle from the UK was implemented. BSE was confirmed by histopathology, immunohistochemistry, animal experiments, immunoblotting and by electron microscopic detection of scrapie-associated fibrils (SAFs).     

Fuzzy logic model for the prediction of bond strength of high-strength lightweight concrete

In this study, a fuzzy logic prediction model for the bond strength of lightweight concrete containing mineral admixtures under different curing conditions was devised. A control concrete mixture containing only Portland cement, another mixture having fly ash replacing 15% by mass of cement, and a third mixture having silica fume replacing 10% by mass of cement are produced, and all specimens from these three mixtures are cured in three different conditions, which are: (1) in water tank of 20 ± 2 °C, (2) sealed in plastic bags in the laboratory, and (3) in air in the laboratory. At the end of each curing period, three specimens out of each concrete combination and curing condition were tested for compressive and bond strengths, and the average of three values were taken. The results obtained from the fuzzy logic prediction model were compared with the average results of the experiments, and they were found to be remarkably close to each other. The results show that the fuzzy logic can be used to predict bond strength of lightweight concrete.     

A new approach based on discrete hidden Markov model using Rocchio algorithm for the diagnosis of the brain diseases

Transcranial Doppler (TCD) study of the adult intracerebral circulation has gained an important popularity in last 10 years, since it is a non-invasive, easy to apply and reliable technique. In this study, an implementation on biomedical system has been developed for classification of signals gathered from middle cerebral arteries in the temporal area via TCD for 24 healthy and 82 ill people which have one of the four different brain patients such as; cerebral aneurysm, brain hemorrhage, cerebral oedema and brain tumor. Basically, the system is composed of feature extraction and classification parts. In the feature extraction stage, the Linear Predictive Coding (LPC) Analysis and Cepstral Analysis were applied in order to extract the cepstral and delta-cepstral coefficients in frame level as feature vectors. In the classification stage a new Discrete Hidden Markov Model (DHMM) based approach was proposed for the diagnosis of brain diseases. This proposed method was developed via Rocchio algorithm. Therefore, to calculate DHMM parameters regulated according to maximum likelihood (ML) approach, both training samples of related class and other classes were included in calculation. Thus, DHMM model parameters presenting one class were suggested to represent the training samples related to that class better as well as not to represent the training samples related to other classes. The performance of the proposed DHMM with Rocchio approach was compared with some methods such as DHMM, Artificial Neural Network (ANN), neuro-fuzzy approaches and obtained better classification performance than these methods.