Characterization of Galactomannan Stabilised Yogurt Drink Using Dynamic Rheology

A stabilised yogurt drink (SYD) was produced by mixing yogurt and water with the galactomannans guar (GG) and locust bean (LBG) gum at concentrations of 0.02, 0.06, 0.10, 0.14, and 0.20 g/100 g. The resulting colloid mixtures' viscous behaviour and stability was investigated. Rheological characterization using oscillatory methodology revealed that dynamic properties of elastic (G′), viscous (G″) modules and complex viscosity (η*) appreciably increased with increasing addition of both gums. Changing shear stress demonstrated complex flow behaviour and revealed the shear dependency of the SYD's flow behaviour. Syneresis decreased with increasing viscosity giving 93% improvement at 0.2 g/100 g gum addition.     

EFFECT OF PREHYDROGENATION ON HYDROCONVERSION OF MAYA RESIDUUM, PART I: PROCESS CHARACTERIZATION

Maya 650°F residuum was mildly prehydrogenated over a standard, commercially available, hydrodesulfurization catalyst. The product was then distilled to yield hydrogenated Maya 650°F residuum. This prehydrogenated residuum, and the untreated Maya 650°F residuum were separately hydroprocessed further at different process severities. The resulting products were then examined by elemental analyses to determine the effects of die prehydrogenation step on overall conversion and product quality.

The primary effect of the prehydrogenation step was to increase the overall conversions for sulfur, MCR, nitrogen, and asphaltenes. As a result, the hydro-conversion products derived from the prehydrogenation were substantially better quality than the corresponding direct hydroconversion products. The prehydrogenation step also lowered the severity required for equivalent residuum hydroconversion upgrading.     

EFFECT OF PREHYDROGENATION ON HYDROCONVERSION OF MAYA RESIDUUM, PART II: HYDROGEN INCORPORATION

Maya 650° F residuum (Maya AR) was prehydrogenated over a standard hydroprocessing catalyst. The 650°F residuum of this product lpar;HMaya ARrpar; and Maya AR were then separately hydroprocessed further at selected conditions. The products were examined by elemental, ¹H, and ¹³C NMR analyses to determine the how hydrogen was incorporated during processing.

For all processing steps, hydrogen was incorporated in capping fragments formed during cracking reactions, as well as in hydrogenation reactions, heteroatom removal, and hydrocarbon gas formation, but the distribution of the hydrogen was dependent upon the type and severity of the process: For the direct hydroconversion of Maya AR, 25 to 30% of the total hydrogen was incorporated for heteroatom removal and hydrocarbon gas formation. The remaining hydrogen was incorporated in hydrogenation and cracking reactions.

For the two-step hydroconversion process, 30 to 40% of the total hydrogen was incorporated for heteroatom removal and hydrocarbon gas formation. The remaining was primarily incorporated in hydrogenation reactions. Some was incorporated into cracking reactions in the moderate severity case, but almost none was seen in the low severity case.

The hydrogen incorporation during each specific processing step is discussed, along with an evaluation of the prehydrogenation step a residuum conversion process option. These results will be also compared to previously reported hydrogen incorporation measurements on other feeds and processing methods.     

Evaluation of the bond strength of different bonding agents to porcelain and metal alloy

This study was carried out with the purpose of testing the bond strength of different bonding agents bonded to different substrates.Substrates consisted of cylindrical specimens of three different materials: porcelain, metal, and a porcelain–metal combination. Specimens were all 10 mm in diameter and 4 mm thick. Surfaces to be bonded were air-abraded with Al₂O₃ and cleaned ultrasonically in distilled water for 10 min. After the preparation of the surface was complete, three different bonding agents were applied to the central region of the substrates. Composite resin of a 3.5 mm diameter and 2 mm thick was applied. All specimens were thermocycled between 5 and 55 °C for 200 cycles with a 30-s dwell time. After thermocycling, specimens were stored at 37 °C in distilled water for an additional 7 days before being subjected to a shear load. Shear testing was conducted Hounsfield test machine.The univariate analysis of variance and the Duncan multiple comparison test were used for statistical assessment. It was found that both type of bonding agents and of substrate led to statistically significant differences in bond strength (p<0.01).It was found that the highest bond strength was produced by Clearfil and on pure alloy substrate (33.36 MPa) and the lowest bond strength in Single Bond and porcelain–alloy substrate (4.25 MPa).     

Photocatalytic degradation kinetics of di- and tri-substituted phenolic compounds in aqueous solution by TiO2/UV

In this study, photocatalytic degradation of 2,4,6-trimethylphenol (TMP), 2,4,6-trichlorophenol (TCP), 2,4,6-tribromophenol (TBP), 2,4-dimethylphenol (DMP), 2,4-dichlorophenol (DCP) and 2,4-dibromophenol (DBP) has been studied by TiO₂/UV. Although degraded phenolic compound concentration increased by increasing initial concentration photocatalytic decomposition rates of di- and tri-substituted phenols at 0.1–0.5 mM initial concentrations decreased when the initial concentration increased. The fastest degradation observed for TCP and the slowest for TMP. Photodegradation kinetics of the compounds has been explained in terms of Langmuir–Hinshelwood kinetics model. Degradation rate constants have been observed to be extremely depended on electronegativity of the substituents on phenolic ring. Degradation rate constant and adsorption equilibrium constant of TCP were calculated as k 0.0083 mM min⁻¹ and K 9.03 mM⁻¹. For TBP and TMP the values of k and K were obtained as 0.0040 mM min⁻¹, 19.20 mM⁻¹, and 0.0017 mM min⁻¹, 51.68 mM⁻¹, respectively. Degradation rate constant of DBP was similar as DCP (0.0029 mM min⁻¹ for DBP and 0.0031 mM min⁻¹ for DCP) whereas adsorption equilibrium constants differed (48.40 mM⁻¹ for DBP and 30.52 mM⁻¹ for DCP). K and k of DMP found as 83.68 mM⁻¹ and 0.0019 mM min⁻¹, respectively. The adsorption equilibrium constants in the dark were ranged between 1.11 and 3.28 mM⁻¹ which are lower than those obtained in kinetics. Adsorption constants have inversely proportion with degradation rate constants for all phenolic compounds studied.     

Extraction,isolation and characterisation of oil bodies from pumpkin seeds for therapeutic use

Pumpkin, a member of the Cucurbitaceae family has been used frequently as functional medicines for therapeutic use. Several phytochemicals such as polysaccharides, phenolic glycosides, 13-hydroxy-9Z, 11E-octadecatrienoic acid from the leaves of pumpkin, proteins from germinated seeds, have been isolated.     

The hypoglycaemic effect of pumpkins as anti-diabetic and functional medicines

Diabetes mellitus is considered as a common, growing, serious, costly, and potentially preventable public health problem. In 2030, the number of people with diabetes is estimated to increase from 117 million in 2000 to 366 million. The prevalence of diabetes has and will continue to have burden on the health and finances of economic climates, which in turn, will impact on individuals, families and nations. There are many different types of insulins available to treat diabetes, but there are still physiological consequences for such use. Alternatives are, therefore, required and this includes herbal preparations as well as dietary plants in the form of curcubitaceae (pumpkin).Pumpkin is widely considered to have active hypoglycaemic properties. Pumpkin is a plant, which has been used frequently as functional food or medicine and belongs to the family Cucubitaceae, and consists of succulent stem with numerous seeds. Based on previous evidence of its fruit pulp, it is reported to have anti-diabetic effects.This review has focused on the main medicinal properties of pumpkin and how this has been used in animal models, and point out areas for future research to further elucidate mechanisms whereby this compound may reduce disease risk.     

EFFECT OF PREHYDROGENATION ON HYDROCONVERSION OF MAYA RESIDUUM,PART II: HYDROGEN INCORPORATION

ABSTRACT

Maya 650° F residuum (Maya AR) was prehydrogenated over a standard hydroprocessing catalyst. The 650°F residuum of this product lpar;HMaya ARrpar; and Maya AR were then separately hydroprocessed further at selected conditions. The products were examined by elemental, ¹H, and ¹³C NMR analyses to determine the how hydrogen was incorporated during processing.

For all processing steps, hydrogen was incorporated in capping fragments formed during cracking reactions, as well as in hydrogenation reactions, heteroatom removal, and hydrocarbon gas formation, but the distribution of the hydrogen was dependent upon the type and severity of the process: For the direct hydroconversion of Maya AR, 25 to 30% of the total hydrogen was incorporated for heteroatom removal and hydrocarbon gas formation. The remaining hydrogen was incorporated in hydrogenation and cracking reactions.

For the two-step hydroconversion process, 30 to 40% of the total hydrogen was incorporated for heteroatom removal and hydrocarbon gas formation. The remaining was primarily incorporated in hydrogenation reactions. Some was incorporated into cracking reactions in the moderate severity case, but almost none was seen in the low severity case.

The hydrogen incorporation during each specific processing step is discussed, along with an evaluation of the prehydrogenation step a residuum conversion process option. These results will be also compared to previously reported hydrogen incorporation measurements on other feeds and processing methods.     

Line-source modeling and estimation with magnetoencephalography

We propose a number of source models that are spatially distributed on a line for magnetoencephalography (MEG) using both a spherical head with radial sensors for more efficient computation and a realistic head model for more accurate results. We develop these models with increasing degrees of freedom, derive forward solutions, maximum-likelihood (ML) estimates, and Cramér-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to select the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models, to determine the regions where better estimates are possible and when it is possible to distinguish between line and focal sources. We demonstrate the usefulness of the proposed line-source models over the previously available focal source model in certain distributed source cases. Finally, we apply our methods to real MEG data, the N2O response after electric stimulation of the median nerve known to be an extended source.