Correlating Isothermal Friction Factor Data for Micro-Fin Tubes Using Logistic Dose-Response Curve Fitting Method

Simultaneous heat transfer and friction factor experiments for plain and micro-fin tubes were conducted in our previous study. The results showed that the heat transfer characteristics of the micro-fin tubes were the same as for the plain tube. However, the friction factor characteristics of the micro-fin tubes in the transition region were different compared to the plain tube. This type of friction factor data cannot be easily correlated by the traditional regression method. Therefore, a logistic dose-response curve-fitting method is proposed in this study. This particular method has recently been used by other researchers in correlating the friction factor data in plain tubes. In this study, three sets of micro-fin tubes friction factor data with different inlets from our previous study were correlated by the logistic dose-response curve-fitting method. All the fully developed friction factor data for the entire flow regime were predicted by a composite logistic dose-response function within ±11% deviation. The majority of the data (over 85%) was predicted with less than ±5% deviation.     

Asymmetry in retail gasoline and crude oil price movements in the United States: An application of hidden cointegration technique

There is a common belief that gasoline prices respond more quickly to crude oil price increases than decreases. Some economists and politicians believe that asymmetry in oil and gasoline price movements is the outcome of a non-competitive gasoline market requiring that governments take policy action to address “unfair pricing”. There is no consensus as to the existence, or nature, of the asymmetric relationship between prices of gasoline and crude oil. Much of this literature specifies asymmetry in the speed of adjustment and short-run adjustment coefficients. In contrast, Granger and Yoon's [Granger, C.W. and Yoon, G. “Hidden Cointegration”, University of California, San Diego, Department of Economics Working Paper, (2002).] Crouching Error Correction Model (CECM) identifies asymmetry of the cointegrating vectors between components (cumulative positive and negative changes) of the series. Applying the CECM to retail gasoline and crude oil prices for the U.S., we find that there is only evidence of cointegration between positive components of crude oil prices and negative components of gasoline prices. In contrast to the literature which attributes asymmetric price movements to market power of refiners, these findings suggest that gasoline prices –in the long run– are more influenced by the technological changes on the demand side than crude oil price movements on the supply side.     

Purification and characterization of membrane-bound polyphenoloxidase (mPPO) from Snake fruit [Salacca zalacca (Gaertn.) Voss]

Membrane-bound polyphenoloxidase (mPPO) an oxidative enzyme which is responsible for the undesirable browning reaction in Snake fruit (Salacca zalacca (Gaertn.) Voss) was investigated. The enzyme was extracted using a non-ionic detergent (Triton X-114), followed by temperature-induced phase partitioning technique which resulted in two separate layers (detergent-poor phase at the upper layer and detergent-rich phase at the lower layer). The upper detergent-poor phase extract was subsequently fractionated by 40–80% ammonium sulfate and chromatographed on HiTrap Phenyl Sepharose and Superdex 200 HR 10/30. The mPPO was purified to 14.1 folds with a recovery of 12.35%. A single prominent protein band appeared on native-PAGE and SDS–PAGE implying that the mPPO is a monomeric protein with estimated molecular weight of 38 kDa. Characterization study showed that mPPO from Snake fruit was optimally active at pH 6.5, temperature 30 °C and active towards diphenols as substrates. The K_m and V_max values were calculated to be 5.46 mM and 0.98 U/ml/min, respectively, when catechol was used as substrate. Among the chemical inhibitors tested, l-cysteine showed the best inhibitory effect, with an IC₅₀ of 1.3 ± 0.002 mM followed by ascorbic acid (1.5 ± 0.06 mM), glutathione (1.5 ± 0.07 mM), EDTA (100 ± 0.02 mM) and citric acid (186 ± 0.16 mM).     

Alcalase-generated proteolysates of stone fish (Actinopyga lecanora) flesh as a new source of antioxidant peptides

In the present study, the alcalase-generated proteolysates obtained after 8 h of proteolysis of stone fish flesh showed the most potent antioxidant activity in terms of DPPH^? radical scavenging activity (77.43%, IC₅₀ of 0.5 mg/mL), ABTS^? radical scavenging activity (92.73%, IC₅₀ of 0.33 mg/mL) and FRAP value (39.2 mmol/100 mL FeSO₄). These proteolysates profiled and characterized as antioxidative peptides. The proteolysates were initially subjected to ultrafiltration using MWCO Spin-X UF. Potent fractions were further characterized based on hydrophobicity using reversed-phase high-performance liquid chromatography (RP-HPLC) and isoelectric point using an OFFGEL isoelectric focusing fractionator. Results indicated that most of the antioxidative peptides found in fractions with a molecular weight (MW) of less than 2 kDa, hydrophilic (hydrophilicity >80%) and basic (pI = 9.7). The final purified fraction with the highest antioxidant activity was selected for peptide identification and sequencing using Q-TOF mass spectrometry. A total of four peptides were identified, from which Peptide 1 (GVSGLHID) showed the highest antioxidant activity and this has potential as a novel bioingredient of nutraceuticals and functional foods to promote human health.     

Identifying Potato Varieties Using Machine Vision and Artificial Neural Networks

The objective of this study is to develop a method for identifying and discriminating 10 potato varieties by combining machine vision and artificial neural network methods. The potato varieties include Agria, Savalan, Florida, Fontaneh, Natasha, Verona, Karso, Elody, Satina, and Emrad. A total number of 72 characteristic parameters specifying color, textural, and morphological features are found among these varieties. By using principal component analysis, 16 principal features are selected for identifying and discriminating potato varieties. The data obtained from image processing were classified using linear discriminant analysis and non-linear artificial neural network method. The accuracy of discriminant analysis were 73.3, 93.3, 73.3, 40, 73.3, 73.3, 66.7, 80, 40, and 53.3%, respectively, for the varieties used in this study. The classification accuracy was improved by 100% for all the varieties using neural network analysis and the correct classification ratio was 100% using this method. It is revealed from the results that machine vision technique and neural network analysis could identify potato varieties with acceptable accuracy.     

Methanol steam reforming in a microchannel reactor by Zn-, Ce- and Zr- modified mesoporous Cu/SBA-15 nanocatalyst

Hydrogen production by steam reforming of methanol was studied over several Cu/SAB-15-based nanocatalysts in a parallel-type microchannel reactor. The catalysts were prepared through impregnation method and XRD, BET, FT-IR, FE-SEM, TEM, H₂-TPR and TGA techniques were used to characterize surface and structural properties of the synthesized catalysts. The effects of reaction temperature, WHSV and S/C molar ratio on the methanol conversion and selectivities of the gaseous products were studied. Then, effects of the metallic promoters were investigated to improve performance of the catalysts. It was revealed that ZnO and CeO₂ promoters have positive effects on decreasing CO selectivity and ZrO₂ promotes methanol conversion. Furthermore, ZrO₂ and CeO₂ were declared to improve stability of the catalyst. Among the evaluated catalysts, Cu/ZnO/CeO₂/ZrO₂/SBA-15 can provide optimal methanol conversion with low CO concentration in the gaseous products. For this catalyst, the methanol conversion and hydrogen selectivity reached 95.2% and 94.6%, respectively.     

Histopathological graded liver lesions: what role does the IVIM analysis method have?

Magnetic Resonance Materials in Physics, Biology and Medicine - This study aims to investigate three different image processing methods on quantitative parameters of IVIM sequence, as well as...