Application of membrane separation processes in petrochemical industry: a review

In this paper a general review on different membrane processes and membrane reactors was done. As the main aim of this paper is to review the application of membrane processes in petrochemical industry, processes such as olefin/paraffin separation, light solvent separation, solvent dewaxing, phenol and aromatic recovery, dehydrogenation, oxidative coupling of methane and steam reforming of methane were discussed in detail. Besides, separation using polymer-inorganic nano composite membranes and wastewater treatment using membrane bio-reactors were reviewed.     

Dy3Fe5O12 and DyFeO3 nanostructures: Green and facial auto-combustion synthesis,characterization and comparative study on electrochemical hydrogen storage

Although the technology of hydrogen energy heightened gradually, the application of binary metal oxides as a host for hydrogen sorption has not been widely established. Here we show, with a facial combustion method, the formation of Dy₃Fe₅O₁₂ and DyFeO₃ nanostructures with maximum average particle sizes ranging from 25 to 30 and 16–18 nm, respectively. The physical properties of the samples were served which further reflect in hydrogen storage properties. The discharge capacities of Dy₃Fe₅O₁₂ and DyFeO₃ nanoparticles were obtained at 2000 and 2100 mA h/g, respectively. The hydrogen storage properties were confirmed in their respective current-voltage cycles, prior to chronopotentiometry.     

Study of macromolecular interactions in low‐fat brined cheese modified with Zedu gum

The functionality of Zedu gum as a fat mimetic in low‐fat brined cheese was studied. The physicochemical, textural, rheological, microstructural and sensory properties of cheese samples modified with 0.1% and 0.25% of Zedu gum were compared to those of control cheeses (low‐fat and full‐fat cheeses with no fat mimetic) during ripening. To obtain further information about the cheeses' structure and interactions between macromolecules (casein protein and Zedu gum), other parameters were analysed by differential scanning calorimetry and Fourier transform infrared (FTIR) spectroscopy. Incorporation of Zedu gum into low‐fat cheese caused an open microstructure and softer texture in comparison with the control low‐fat cheese. The thermal properties and FTIR spectra of the cheeses were influenced by both fat mimetic and ripening time. On days 1 and 60 of ripening time, the lower value of enthalpy of the low‐fat cheese with 0.25 g of Zedu gum/kg of milk (AS 0.25) in comparison with control low‐fat cheese could have been due to the electrostatic nature of the interactions between Zedu gum and casein protein. On both days, the FTIR spectrum of AS 0.25 showed a well separated absorption at 1746 cm^?1 possibly due to the formation of ester groups as a result of the interaction of the carbonyl groups in Zedu gum with the hydroxyl groups of some amino acids in casein.     

Using backward elimination with a new model order reduction algorithm to select best double mixture model for document clustering

Probabilistic latent semantic analysis (PLSA) is a double structure mixture model which has got a wide application in text and web mining. This method is capable of establishing hidden semantic relations among the observed features, using a number of latent variables. In this approach, the selection of the correct number of latent variables is critical. In the most of the previous researches, the number of latent topics was selected based on the number of invoked classes. This paper presents a method, based on backward elimination approach, which is capable of unsupervised order selection in PLSA. This method starts with a model having a number of components more than the needed value, and then prunes the mixtures to reach their optimum size. During the elimination process, proper selection of some latent variables which must be deleted is the most essential problem, and its relation to the final performance of the pruned model is straightforward. To treat this problem, we introduce a new combined pruning method which selects the best options for removal, while keeping a low computational cost, at all. We conducted some experiments on two datasets from Reuters-21578 corpus. The obtained results show that this algorithm leads to an optimized number of latent variables and in turn achieves better clustering performance compared to the conventional model selection methods. It also shows superiority over the case in which a PLSA model with a fixed number of latent variables, equal to the real number of clusters, is exploited.     

Assessment of immobilized cell reactor and microbial fuel cell for simultaneous cheese whey treatment and lactic acid/electricity production

Two biological methods for treatment of cheese whey and concentrated cheese whey were investigated in this research. As the first method, fermentation of cheese whey for production of lactic acid, in an immobilized cell reactor (ICR) was successfully carried out. The immobilisation of Lactobacillus bulgaricus was performed by the enriched cells cultured media harvested at exponential growth phase. Furthermore, the FTIR analysis has been done to prove the production of lactic acid. The COD removal during the continuous process for both whey and concentrated whey was above 70% which showed the capability of reaction for wastewater treatment. The cells were immobilised by sodium alginate as a perfect polymer in this regard. The maximum produced lactic acid from whey was 10.7 g l^?1 at 0.125 h^?1 and 19.5 g l^?1 from concentrated whey at 0.063 h^?1. Finally it can be concluded that the process is efficient for lactic acid production and COD removal simultaneously. As the second studied method, whey and concentrated cheese whey were used as the sources of carbon in a microbial fuel cell. The power densities of 188.8 and 288.12 mW m^?2 were recorded for whey-fed and concentrated whey-fed MFCs while the COD removal were 95% and 86% respectively. Biological wastewater treatment can be a very efficient alternative for traditional wastewater treatment which selecting any and or integrating of them depends on specific applications needed to be achieved.     

Essential and trace elements content of commercial infant foods in the UK

There is a paucity of data in respect of the nutritional quality of complementary foods for infants and young children aged between 6 and 12 months. The primary objective of this study was to examine nutritive values of such complementary infant food on the UK market in order to ascertain their suitability relative to dietary guidelines for the 6–9 months age group. Quantitative analyses were conducted on eight different products representing four popular brands (meat and vegetable based) currently on sale in the UK. Eight major mineral and trace elements, namely: calcium, copper, magnesium, iron, zinc, potassium, sodium and selenium were measured by ICP–OES and ICP–MS. The results of these studies were referenced to the Recommended Nutrient Intake (RNI) values for 6–9 months old children, and a menu of entire daily intake of minerals and trace elements was composed taking into consideration the nutrient and energy intake from milk consumption. Based on these comparisons, all the food samples studied in this work contained less essential minerals than expected from the RNI values except for potassium in meat and vegetable based recipes. These results suggest that commercial complementary infant foods on the UK market may not contain the minimum levels of minerals required for the labelling declaration of micronutrient content (Commission Directive 2006/125/EC). This provides opportunities and scope for product optimisation to improve their nutritive value.