Biodiversity and technological properties of yeasts from Turkish sourdough

Food Science and Biotechnology - In this study, yeasts were isolated and characterized from twelve traditional sourdough samples which belongs to Black Sea and Aegean regions of Turkey. Twenty six...     

Evaluating of traumatic brain injuries using artificial neural networks

The purpose of this study is to develop a diagnostic system to detect the severity of traumatic brain injuries using artificial neural networks. Three layered back propagation neural network with an input layer of 10 nodes whose output providing the inputs to a hidden layer was used. Thirty-two patients with traumatic brain injuries in different age and gender were taken in the study. Electroencephalography, Trauma and Glasgow coma scores were used for evaluating the data. The results obtained from the system were compared with the findings of neurologists. We found a significant relationship between the findings of neurologists and systems output for normal, mild, moderate and severe electroencephalography tracing data. Getting this system in routine use will lead to make a rapid decision for the degree of trauma with electroencephalography and revised trauma score.     

Air and oxy-fuel combustion kinetics of low rank lignites

The air and oxy-fuel combustion processes of two low-grade lignite coals were investigated by thermogravimetric analysis (TGA) method. Coals were provided from two different coal mines in the Aegean region of Turkey. Oxy-fuel combustion experiments were carried out with three different gas mixtures of 21% O₂–79% CO₂; 40% O₂–60% CO₂ and 50% O₂–50% CO₂ at 950 °C and heating rates of 10 °C/min, 20 °C/min and 40 °C/min. The kinetics of the oxy-fuel combustion of coals were studied by using four different methods namely, Coats-Redfern (model-fitting method), Friedman (FR), Flynn–Wall–Ozawa's (FWO) and Kissinger–Akahira–Sunose's (KAS) methods. The apparent activation energies of combustion process calculated by FWO method are slightly but systematically higher than that calculated by the KAS and FR methods for the oxy-fuel atmospheres. Combustion behavior of both coals in the oxy-fuel combustion environment could vary significantly, likely due to their characteristics such ash and volatile matter contents.     

Early prostate cancer diagnosis by using artificial neural networks and support vector machines

The aim of this study is to design a classifier based expert system for early diagnosis of the organ in constraint phase to reach informed decision making without biopsy by using some selected features. The other purpose is to investigate a relationship between BMI (body mass index), smoking factor, and prostate cancer. The data used in this study were collected from 300 men (100: prostate adenocarcinoma, 200: chronic prostatism or benign prostatic hyperplasia). Weight, height, BMI, PSA (prostate specific antigen), Free PSA, age, prostate volume, density, smoking, systolic, diastolic, pulse, and Gleason score features were used and independent sample t-test was applied for feature selection. In order to classify related data, we have used following classifiers; scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Levenberg–Marquardt (LM) training algorithms of artificial neural networks (ANN) and linear, polynomial, and radial based kernel functions of support vector machine (SVM). It was determined that smoking is a factor increases the prostate cancer risk whereas BMI is not affected the prostate cancer. Since PSA, volume, density, and smoking features were to be statistically significant, they were chosen for classification. The proposed system was designed with polynomial based kernel function, which had the best performance (accuracy: 79%). In Turkish Family Health System, family physician to whom patients are applied firstly, would contribute to extract the risk map of illness and direct patients to correct treatments by using expert system such proposed.     

Fatty acid hydratase for value-added biotransformation: A review

The synthesis of hydroxy fatty acids (HFAs) from renewable oil feedstock by addition of water onto C=C bonds has attracted great attention in recent years. Given that selective asymmetric hydration of non-activated C=C bonds has been proven difficult to achieve with chemical catalysts, enzymatic catalysis by fatty acid hydratases (FAHs) presents an attractive alternative approach to produce value-added HFAs with high regio-, enantioand stereospecificity, as well as excellent atom economy. Even though FAHs have just been investigated as a potential biocatalyst for a decade, remarkable information about FAHs in different aspects is available; however, a comprehensive review has not been archived. Herein, we summarize the research progresses on biochemical characterization, structural and mechanistic determination, enzyme engineering, as well as biotechnological application of FAHs. The current challenges and opportunities for an efficient utilization of FAHs in organic synthesis and industrial applications are critically discussed.     

K-shell absorption jump factors and jump ratios in elements between Tm (Z = 69) and Os (Z = 76) derived from new mass attenuation coefficient measurements

The K-shell absorption jump factors and jump ratios were derived from new mass attenuation coefficients measured using an energy dispersive X-ray fluorescence (EDXRF) spectrometer for Tm, Yb elements being Tm₂O₃, Yb₂O₃ compounds and pure Lu, Hf, Ta, W, Re and Os. The measurements, in the region 56-77 keV, were done in a transmission geometry utilizing the K_α1, K_α2, K_β1 and K_β2 X- rays from different secondary source targets (Yb, Ta, Os, W, Re and Ir, etc.) excited by the 123.6 keV γ-photons from an ⁵⁷Co annular source and detected by an Ultra-LEGe solid state detector with a resolution of 150 eV at 5.9 keV. Experimental results have been compared with theoretically calculated values. The measured values of Tm, Yb, Lu, Hf, Ta, W, Re and Os are reported here for the first time.     

The Application of Critical Path Method (CPM) in Workflow Schema of Marble Processing Plants

The critical path method (CPM) is a widely applied technique in large-scale industrial project planning and control. Based on a detailed review of the current literature, no references have been found referring to the use of the CPM in marble processing plants and other industrial mineral plants. In this regard, this study proposes a new application area of CPM and suggests the implementation details of mineral processing workflows with particular emphasis on marble production facilities. In the study, the CPM is applied to marble processing plants for selecting an applicable production process and for determining the workflow schema in order to optimize the cost of operation and to effectively manage time. As a consequence of this analysis, a new production plan is proposed for medium-scale marble processing plants. A suitable marble processing plant has been built and taken into operation in accordance with the proposed plant plan. It has been observed that this plant has a higher production rate at a preferable capacity when compared to three other plants studied as a part of this research.     

Research on ethanol production and use from sugar beet in Turkey

Emissions of greenhouse gases such as CO₂, CO, CH₄ and NO_X from fossil fuel use are implicated in climate change. The use of bioethanol is one means to reduce fossil fuel use and emissions of greenhouse gases. This study investigated research to produce ethanol from sugar beet and use as fuel in Turkey. The calculated demand for bioethanol amounted to some 220,000 m³ where a 5% ethanol mix in petrol was used. Turkey has the potential to produce 30 million ton of sugar beet, which is sufficient to meet the bioethanol demand.     

A Novel Grounded Inductor Realization Using a Minimum Number of Active and Passive Components

In this study, we present a new topology for realizing a grounded inductor employing only a single current conveyor, called a negative‐type modified inverting second‐generation current conveyor (MICCII‐), and a minimum number of passive components, two resistors, and one capacitor. The non‐ideality effects of the MICCII‐on a simulated inductor are investigated. To demonstrate the performance of the presented inductance simulator, we use it to construct a third order Butterworth high‐pass filter and a parallel resonant circuit. Simulation results are given to confirm the theoretical analysis.