Effects of Penicillium roqueforti and whey cheese on gross composition,microbiology and proteolysis of mould‐ripened Civil cheese during ripening

Four different types of mould‐ripened Civil cheese were manufactured. A defined (nontoxigenic) strain of a Penicillium roqueforti (SC 509) was used as the secondary starter with and without addition of the whey cheese (Lor); in parallel, secondary starter‐free counterparts were manufactured. Chemical composition, microbiology and proteolysis were studied during the ripening. The incorporation of whey cheese in the manufacture of mould‐ripened Civil cheese altered the gross composition and adversely affected proteolysis in the cheeses. The inoculated P. roqueforti moulds appeared to grow slowly on those cheeses, and little proteolysis was evident in all cheese treatments during the first 90 days of ripening. However, sharp increases in the soluble nitrogen fractions were observed in all cheeses after 90 days. Microbiological analysis showed that the microbial counts in the cheeses were at high levels at the beginning of ripening, while their counts decreased approximately 1–2 log cfu/g towards the end of ripening.     

Raman Spectroscopic Barcode Use for Differentiation of Vegetable Oils and Determination of Their Major Fatty Acid Composition

In this study, differentiation of vegetable oils and determination of their major fatty acid (FA) composition were performed using Raman spectral barcoding approach. Samples from seven different sources (sunflower, corn, olive, canola, mustard, soybean and palm) were analyzed using Raman spectroscopy. Second derivative of the spectral data was utilized to generate unique barcodes of oils. Chemometric analyses, namely, principal component analysis (PCA) and partial least square (PLS) methods were used for data analysis. PCA was applied for classification of the samples according to the differences in their levels arising from their barcode data. A successful differentiation based on second derivative barcodes of Raman spectra (2D‐BRS) of vegetable oils was obtained. In addition, PLS method was applied on 2D‐BRS in order to determine the major FA composition of these samples. Coefficient of determination values for palmitic, stearic, oleic, linoleic, α‐linolenic, cis‐11 eicosenoic, erucic and nervonic acids were in the range of 0.970–0.989. Limit of detection and limit of quantification values were found to be satisfactory (0.09–8.09 and 0.30–26.95 % in oil) for these fatty acids . Advantages of both chemometric analysis and spectral barcoding approach have been utilized in the present study. Taking the second derivative of the Raman spectra has minimized background variability and sensitivity to intensity fluctuations. Spectral conversion to the barcodes has further increased the quality of information obtained from Raman spectra and also made it possible to improve the visualization of the data. Converting Raman spectra of oils into barcodes enables simpler presentation of the valuable information, and still allows further analysis such as classification of vegetable oils and prediction of their major fatty acids with high accuracy.     

Mechanism of boron tribromide electroreduction

This study was carried out to investigate the electrochemical behavior of boron tribromide in dimethlyformamide. The reduction of the compound was found to follow a CE mechanism. The kinetic parameters and the diffusion coefficient were calculated by the use of ultramicrodisc electrodes and chronoamperometry. The number of electrons transferred was found to be 2 by rotating disc and ultramicro disc electrodes and 3 by coulometry. These results are in good accordance with those obtained from molten boron salts. This study is important in regard to electrochemical boronizing at low temperatures.     

Excitation energy-dependent nature of Raman scattering spectrum in GaInNAs/GaAs quantum well structures

The excitation energy-dependent nature of Raman scattering spectrum, vibration, electronic or both, has been studied using different excitation sources on as-grown and annealed n- and p-type modulation-doped Ga_1 − xIn_xN_yAs_1 − y/GaAs quantum well structures. The samples were grown by molecular beam technique with different N concentrations (y = 0%, 0.9%, 1.2%, 1.7%) at the same In concentration of 32%. Micro-Raman measurements have been carried out using 532 and 758 nm lines of diode lasers, and the 1064 nm line of the Nd-YAG laser has been used for Fourier transform-Raman scattering measurements. Raman scattering measurements with different excitation sources have revealed that the excitation energy is the decisive mechanism on the nature of the Raman scattering spectrum. When the excitation energy is close to the electronic band gap energy of any constituent semiconductor materials in the sample, electronic transition dominates the spectrum, leading to a very broad peak. In the condition that the excitation energy is much higher than the band gap energy, only vibrational modes contribute to the Raman scattering spectrum of the samples. Line shapes of the Raman scattering spectrum with the 785 and 1064 nm lines of lasers have been observed to be very broad peaks, whose absolute peak energy values are in good agreement with the ones obtained from photoluminescence measurements. On the other hand, Raman scattering spectrum with the 532 nm line has exhibited only vibrational modes. As a complementary tool of Raman scattering measurements with the excitation source of 532 nm, which shows weak vibrational transitions, attenuated total reflectance infrared spectroscopy has been also carried out. The results exhibited that the nature of the Raman scattering spectrum is strongly excitation energy-dependent, and with suitable excitation energy, electronic and/or vibrational transitions can be investigated.     

Utilization of Catalytic Properties of the Encapsulated Lipase with Calix[4]arene-Adorned Sporopollenin

The dihydrazide calix[4]arene was immobilized onto sporopollenin in order to encapsulate Candida rugosa lipase (CRL) via sol-gel entrapment. The kinetic resolution of the new encapsulated lipase was investigated for enantioselective hydrolysis of racemic naproxen methyl ester and 2-phenoxypropionic acid methyl ester. The results demonstrated that the activity and enantioselectivity of the lipase were improved when the lipase was encapsulated in the presence of calix[4]arene-immobilized sporopollenin. The encapsulated lipase showed an excellent rate of enantioselectivity against the (R/S)-naproxen methyl and (R/S)-2-phenoxypropionic acid methyl esters, with E = 350 and 295, respectively, compared to the free enzyme.     

Synthesis and surface properties of polydimethylsiloxane‐based block copolymers: poly[dimethylsiloxane‐block‐ (ethyl methacrylate)] and poly[dimethylsiloxane‐block‐(hydroxyethyl methacrylate)]

A polydimethylsiloxane (PDMS) macroazoinitiator was synthesized from bis(hydroxyalkyl)‐terminated PDMS and 4,4′‐azobis‐4‐cyanopentanoic acid by a condensation reaction. The bifunctional macroinitiator was used for the block copolymerization of ethyl methacrylate (EMA) and 2‐(trimethylsilyloxy)ethyl methacrylate (TMSHEMA) monomers. The poly(DMS‐block‐EMA) and poly(DMS‐block‐TMSHEMA) copolymers thus obtained were characterized using Fourier transform infrared and ¹H NMR spectroscopy and differential scanning calorimetry. After the deprotection of trimethylsilyl groups, poly(DMS‐block‐HEMA) and poly(DMS‐block‐EMA) copolymer film surfaces were analysed using scanning electron microscopy and X‐ray photoelectron spectroscopy. The effects of the PDMS concentration in the copolymers on both air and glass sides of films were examined. The PDMS segments oriented and moved to the glass side in poly(DMS‐block‐EMA) copolymer film while orientation to the air side became evident with increasing DMS content in poly(DMS‐block‐HEMA) copolymer film. The block copolymerization technique described here is a versatile and economic method and is also applicable to a wide range of monomers. The copolymers obtained have phase‐separated morphologies and the effects of DMS segments on copolymer film surfaces are different at the glass and air sides. Copyright © 2010 Society of Chemical Industry     

The effect of post surface silanization and luting agents on the push-out bond strengths of adhesively inserted fiber reinforced posts

The effect of silane treatment on the push-out bond strengths of three different luting agents to fiber-reinforced composite (FRC) posts after thermocycling was evaluated.Sixty single-rooted human maxillary central incisors were sectioned below the cemento-enamel junction, and the roots were endodontically treated. RelyX Fiber Posts (size #2) were inserted using etch-and-rinse, self-etch, and self-adhesive luting agents (cementing agents). For half of the specimen in each group, the fiber posts were treated with a silane coupling agent. Bonded specimens were cut (2-mm-thick sections) and push-out tests were performed (crosshead speed, 0.5 mm/min). Failure modes were evaluated using a stereomicroscope at original magnification ×40.For each luting agent the use of silane did not result in any statistically significant difference at any level of the root compared to those of the control groups except for Variolink II and RelyX Unicem luting agents in apical root section (p<0.05; one-way ANOVA). The post hoc analysis showed that regardless of the pre-treatment procedures, Variolink II achieved significantly higher bond strengths than Panavia F 2.0 and RelyX Unicem in all root sections (p<0.05).The use of a silane coupling agent had no influence on bond strengths depending on the luting agent used, whereas the type of luting agent (etch-and-rinse, self-etch, and self-adhesive) appeared to be a significant influence on the push-out bond strength values independent of the pre-treatment used. Therefore, pre-treatment of fiber posts with a silane coupling agent does not seem to be mandatory, which saves time in the clinical situation.     

An expert system for detection of electrocardiographic changes in patients with partial epilepsy using wavelet-based neural networks

Abstract: In this study a wavelet‐based neural network model, employing the multilayer perceptron, is presented for the detection of electrocardiographic changes in patients with partial epilepsy. Decision making is performed in two stages: feature extraction using the wavelet transform, and multilayer perceptron neural networks (MLPNNs) trained with the backpropagation, delta‐bar‐delta, extended delta‐bar‐delta and quick propagation algorithms as classifiers. The classification results, the values of statistical parameters and performance evaluation parameters of the MLPNNs trained with different algorithms are compared. Two types of electrocardiogram beats (normal and partial epilepsy) obtained from the MIT‐BIH database were classified with accuracy varying from 90.00% to 97.50% by the MLPNNs trained with different algorithms.     

Comparison of different classification algorithms in clinical decision-making

Abstract: This paper gives an integrated view of implementing automated diagnostic systems for clinical decision-making. Because of the importance of making the right decision, better classification procedures are necessary for clinical decisions. The major objective of the paper is to be a guide for readers who want to develop an automated decision support system for clinical practice. The purpose was to determine an optimum classification scheme with high diagnostic accuracy for this problem. Several different classification algorithms were tested and benchmarked for their performance. The performance of the classification algorithms is illustrated on two data sets: the Pima Indians diabetes and the Wisconsin breast cancer. The present research demonstrates that the support vector machines achieved diagnostic accuracies which were higher than those of other automated diagnostic systems.     

Investigating Neutronic Parameters of a Thorium Fusion Breeder with Recurrent Neural Networks

Artificial neural networks (ANNs) have recently been introduced to the nuclear engineering applications as a fast and flexible vehicle to modeling, simulation and optimization. In this paper, a new approach based on recurrent neural networks (RNNs) was presented for the neutronic parameters of a thorium fusion breeder. The results of the RNNs implemented for the tritium breeding ratio computation, energy multiplication factor and net ²³³U production in a thorium fusion breeder and the results available in the literature obtained by using Scale 4.3 were compared. The drawn conclusions confirmed that the proposed RNNs could provide an accurate computation of the tritium breeding ratio computation, the energy multiplication factor and the net ²³³U production of the thorium fusion breeder.