Calcium deficient hydroxyapatite by precipitation: Continuous process by vortex reactor and semi-batch synthesis

Precipitation of calcium deficient hydroxyapatite nanoparticles in an environmentally benign manner by using only dilute solutions of calcium hydroxide and phosphoric acid without pH adjustment and addition of other chemicals, and water, being the only by-product was investigated by using continuous flow Vortex Reactor (VR) and Semi-Batch Reactor (SBR). The effect of hydrodynamics by changing the Reynolds number of the jets providing residence times of 8.4 ms to 4.37 s for VR, and by changing the stirrer speed between 100 rpm (Re = 2656) and 1000 rpm (Re = 26560) for SBR, on the particle size, particle size distribution, and morphology of the particles was investigated for both systems. It has been shown that it is possible to produce pure phase hydroxyapatite nanoparticles in the desired morphology by changing production system, without resorting to additives. While VR produced rod-like particles with the crystallite size around 4 nm, SBR produced spherical particles with the crystallite size of around 5 nm.     

Volatile organic compound profiles of yoghurt produced from cow's milk with different somatic cell counts

The present study aimed to investigate the effect of somatic cell count (SCC) of raw cow's milk on the volatile organic compound (VOC) profiles of yoghurt. Test yoghurt samples were produced from three batches of cow's milk with low, medium and high SCC, respectively. The VOCs were determined by gas chromatography–mass spectrometry (GC–MS) analysis. A lower diacetyl and acetoin content and a higher content of 2‐heptanone, and butanoic and hexanoic acids were established in the yoghurt samples from batches with high SCC of above 1 000 000 cells/cm³. The increased SCC of cow's milk had a negative effect on the volatile organic compound profiles of yoghurt.     

Polarization losses in reflector antennas

Various definitions for polarization-loss efficiency of Cassegrainian and front-fed reflectors are compared. The effects of flare angle, feed taper and the feed pattern asymmetry on the polarization-loss efficiency are investigated. The definitions based on aperture fields are shown to be inadequate and far fields must be used for calculating the polarization losses.     

A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment

Quality function deployment (QFD) is a systematic process for translating customer needs into engineering characteristics, and then communicating them throughout the enterprise in a way to ensure that details are quantified and controlled. The inherent fuzziness of relationships in QFD modeling justifies the use of fuzzy regression for estimating the relationships between both customer needs and engineering characteristics, and among engineering characteristics. Albeit QFD aims to maximize customer satisfaction, requirements related to enterprise satisfaction such as cost budget, extendibility, and technical difficulty also need to be considered. This paper presents a fuzzy multiple objective decision framework that includes not only fulfillment of engineering characteristics to maximize customer satisfaction, but also maximization of extendibility and minimization of technical difficulty of engineering characteristics as objectives subject to a financial budget constraint to determine target levels of engineering characteristics in product design. A real-world quality improvement problem is presented to illustrate the application of the decision approach.     

An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

An integrated decision making approach for ERP system selection

Enterprise resource planning (ERP) systems have gained major prominence by enabling companies to streamline their operations, leverage and integrate business data process. In order to implement an ERP project successfully, it is necessary to select an ERP system which can be aligned with the needs of the company. Thus, a robust decision making approach for ERP software selection requires both company needs and characteristics of the ERP system and their interactions to be taken into account. This paper develops a novel decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zero–one goal programming. The proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but also the interactions between ERP system characteristics through adopting the QFD principles. The presented methodology appears as a sound investment decision making tool for ERP systems as well as other information systems. The potential use of the proposed decision framework is illustrated through an application.     

Coal consumption and industrial production nexus in USA: Cointegration with two unknown structural breaks and causality approaches

The paper investigates the causality relationships among industrial production index, coal consumption and employment in industrial sector for the period of 1973:1–2011:10 in USA. After noticing that there are breaks in the regression model, the Hatemi-J test for cointegration is employed to the cases that take into account two possible regime shifts. It is concluded that there is a long run relationship between industrial production and industrial coal consumption with the breaks at 1983:4 and 1998:4. We found a negative relationship between coal consumption and industrial production for the period of 1973:1–1983:4 and positive relationship for 1983:5–1998:4 period. For the last period that covers 1983:5–2011:10, the cointegration relationship turned to negative. In addition, the results show that causal relationship between coal consumption and industrial production changes over time.     

Glycation of soy protein isolate with two ketoses: d-Allulose and fructose

Modification of food proteins to have improved functional properties is of great importance. In this study, modification of soy protein isolate (SPI) was achieved through glycation. SPI was glycated in a spray dryer (SD) and an incubator followed by freeze drying (FD). d -Allulose, an important rare sugar, was used in SPI glycation as the carbohydrate source, and results were compared with fructose. In addition to the sugar type, two different SPI powder: sugar ratios (1:1 and 5:1) were investigated. For the glycated samples, emulsification activity, free amino groups, protein solubility, Fourier-transform infrared spectroscopy analysis, antioxidant activity experiments and time-domain NMR relaxometry measurements for hydration were conducted. According to the results, the solubility of SPI that is limited in native form has shown a significant improvement after glycation through both FD and SD methods. Besides, glycation through the FD method was found to be more favourable due to its milder conditions than the SD method. Considering the physicochemical properties, the best combination for the highest glycation degree was found to be the samples prepared at the 1:1 ratio with d -Allulose in the FD method. Overall, it was concluded that glycation of SPI enhanced its functional properties such as antioxidant and emulsification activities.     

A Robust Macroelement Model for Soil–Pile Interaction under Cyclic Loads

The principal focus of this study is the development of a robust macroelement model for soil–pile interaction under cyclic loads. The model incorporates frictional forces and formation of gaps at the soil–pile interface as well as hysteretic behavior of the soil. The plastic envelope of the soil behavior is modeled via the so-called p–y approach, outlined in American Petroleum Institute’s guidelines for design of foundation piles for offshore platforms. The macroelement is an intuitive assembly of various basic elements, each of which incorporating a particular aspect of the soil–pile interaction. The modular structure of this macroelement allows straightforward adaptation of improved constitutive models for its building blocks. Herein, we focus on large-diameter, cast-in-drilled-hole reinforced concrete piles (piers) that are partially or fully embedded in soil. These types of piles are frequently used as support structures in highway construction. Consequently, the numerical robustness of the interaction model is assessed with parametric studies on pile systems and soil types relevant to this type of construction. Both elastic and inelastic pile behaviors are considered in the parametric studies. The results indicate that the proposed interaction element is numerically robust, and thus, amenable to routine structural analysis.