Kinetic analysis of plasma VLDL-TG and VLDL-remnant-TG turnover in anesthetized rats

We have estimated the turnover and relative pool sizes of nascent-VLDL-TG and VLDL-remnants-TG in anesthetized rats. [1-¹⁴C]Palmitoyl- and [2-³H]glyceryl-labeled “VLDL”-TG (including nascent VLDL-TG and VLDL-remnants-TG) were prepared by injecting labeled palmitate and glycerol into donor rats. Labeled serum from these rats was then injected intravenously into nembutalized male rats and serial blood samples taken for 30 min. Special care was taken to define any early components in the labeled “VLDL”-TG disappearance curves. In other experiments, the donors were rendered functionally hepatectomized 30 min after injection of³H-glycerol and the endogenous labeled VLDL-TG was allowed to circulate 30–60 min before collection of the TG-labeled VLDL-remnants-containing serum. The latter was injected into 4 recipient nembutalized rats and the remnant-TG-turnover measured by serial sampling as above. In two cases,¹⁴C-“VLDL” and³H-VLDL-remnants were injected as a single bolus into ether-anesthetized rats. Despite its complex composition, “VLDL”-TG in most cases disappeared in a single exponential fashion for 30 min with an average half-life of 5.9 min in nembutalized and 2.8 in ether-anesthetized rats. VLDL-remnants-TG showed a more complex behavior, but contained a major rapid component with a mean t_1/2 of ca. 1.5 min in both groups. The data, analyzed by multicompartmental analysis, were fitted to a simple model in which turnover of a larger nascent VLDL-TG pool with formation of a more rapidly turning over smaller pool of VLDL-remnant-TG is the rate-limiting step in overall TG removal from the d<1.006 fraction of rat serum. The data are consistent with our theoretical prediction that under these conditions the kinetics of the VLDL-remnants cannot be resolved from analysis of the total composite “VLDL” (nascent plus remnant) pool.     

Hyper-Spherical Search (HSS) algorithm: a novel meta-heuristic algorithm to optimize nonlinear functions

This paper proposes a novel optimization algorithm called Hyper-Spherical Search (HSS) algorithm. Like other evolutionary algorithms, the proposed algorithm starts with an initial population. Population individuals are of two types: particles and hyper-sphere centers that all together form particle sets. Searching the hyper-sphere inner space made by the hyper-sphere center and its particle is the basis of the proposed evolutionary algorithm. The HSS algorithm hopefully converges to a state at which there exists only one hyper-sphere center, and its particles are at the same position and have the same cost function value as the hyper-sphere center. Applying the proposed algorithm to some benchmark cost functions shows its ability in dealing with different types of optimization problems. The proposed method is compared with the genetic algorithm (GA), particle swarm optimization (PSO) and harmony search algorithm (HSA). The results show that the HSS algorithm has faster convergence and results in better solutions than GA, PSO and HSA.     

Classification of non-alcoholic beer based on aftertaste sensory evaluation by chemometric tools

Sensory evaluation is the application of knowledge and skills derived from several different scientific and technical disciplines, physiology, chemistry, mathematics and statistics, human behavior, and knowledge about product preparation practices. This research was aimed to evaluate aftertaste sensory attributes of commercial non-alcoholic beer brands (P1, P2, P3, P4, P5, P6, P7) by several chemometric tools. These attributes were bitter, sour, sweet, fruity, liquorice, artificial, body, intensity and duration. The results showed that the data are in a good consistency. Therefore, the brands were statistically classified in several categories. Linear techniques as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were performed over the data that revealed all types of beer are well separated except a partial overlapping between zones corresponding to P4, P6 and P7. In this research, for the confirmation of the groups observed in PCA and in order to calculate the errors in calibration and in validation, PLS-DA technique was used. Based on the quantitative data of PLS-DA, the classification accuracy values were ranked within 49-86%. Moreover, it was found that the classification accuracy of LDA was much better than PCA. It shows that this trained sensory panel can discriminate among the samples except an overlapping between two types of beer. Also, two types of artificial networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Back Propagation (BP) learning method. The highest classification success rate (correct predicted number over total number of measurements) of about 97% was obtained for RBF followed by 94% for BP. The results obtained in this study could be used as a reference for electronic nose and electronic tongue in beer quality control.     

Thermodynamic evaluation of integrated gasification combined cycle: Comparison between high‐ash and low‐ash coals

In the present study, a coal‐integrated gasification combined cycle power plant is simulated. A high‐ash coal and low‐ash coal are considered to compare the performance of the plant. The combined cycle is in typical commercial size with 450 MW capacity. The feeds are Tabas and Illinois #6 coals which approximately contain more than 30% and 10% ash and have higher heating values of 22.7 MJ/kg and 26.8 MJ/kg, respectively. Energy and exergy analyses are done by aspen plus ^® and ees , respectively. Energy analysis shows that the overall efficiencies of power plants using high‐ash and low‐ash coals are 33% and 28%, respectively. The result shows that in high‐ash case, 52 kg/s coal, 10 kg/s water, and 1050 kg/s air and in low‐ash case, 48 kg/s coal and 820 kg/s air are required for providing mentioned power, approximately. Exergy analysis shows that maximum exergy destruction is in heat recovery steam generator unit. Investigating the emissions shows that high percent of ash in the coal composition has slight effects on the IGCC pollution. Finally, from thermodynamic viewpoint, it is concluded that the high‐ash coal, like the conventional one, can be used as thermally efficient and environmentally compatible feed of IGCCs. Copyright © 2016 John Wiley & Sons, Ltd.     

Degradation of drag reducing polymers in aqueous solutions

The performance of drag reducing polymers in turbulent flow is restricted by their mechanical degradation. This study examines how the working fluid can affect the degradation behavior of diluted drag reducing polymeric solutions. Solutions having different proportions of tap water and de-ionized water served as the working fluids. Three commercially available water soluble polymeric agents, namely, an anionic copolymer of polyacrylamide, xanthan gum, and polyethylene oxide, were then added to these solutions. All experiments had identical flow rates corresponding to turbulent conditions in a laboratory scale pipe line. Variation of pressure drop in the pipe line was then measured for 2 hours. It was found that polymer degradation is accelerated in tap water solutions compared to that in de-ionized water solutions. However, this is dependent on the specification of the polymer used, namely, the molecular weight of the polymer and the rigidity of its molecular backbone. Furthermore, a new mathematical relation has been developed to investigate degradation of the polymers over time.     

Synthesis of pure zeolite Y using soluble silicate, a two-level factorial experimental design

Four methods were used for the synthesis of pure zeolite Y using soluble silicate as a silica source: (1) the gelling of soluble silicate to silica–alumina gel, by aluminate (or aluminium sulphate), (2) the precipitation of soluble silicate to precipitated silica–alumina gel, by aluminate (or aluminium sulphate), (3) the gelling of soluble silicate by sulphuric acid plus alumina impregnation, and (4) the precipitation of soluble silicate by sulphuric acid plus alumina impregnation. A 2⁴ two-level factorial design was used to study the influence of four different variables on the purity of zeolite Y (expressed in terms of degree of crystallinity). The ageing time turned out to be the most significant variable. Synthesis time, alkalinity and mixing rate were also found to be statistically significant. X-ray diffraction patterns were used to characterize the samples, which ranged from well-crystallized faujasite structures to amorphous materials. The highest purity achieved in method (1) was 38%. The best synthesis condition derived from method (1) was applied to the other three methods. Only method (4) yielded the pure zeolite Y. Therefore, the effect of silica–alumina precursor preparation on producing the pure zeolite Y is extremely important.