Effect of short-term storage on phenolic content,o-diphenolase and peroxidase activities of cut yam tubers (Dioscorea sp)

The effect of short-term storage on the protein, phosphorus and phenolic content as well as peroxidase and o-diphenolase activities of cut, harvested Jamaican yam (Dioscorea sp) tubers (D rotundata. D alata and D cayenensis) was studied. There was an initial increase in the total phenolic content up to the third week of storage followed by a gradual decrease to the sixth week. Phenolic content was found to be highest in D cayenensis followed by D rotundata and D alata. The activities of peroxidase (EC 1. 11. 1. 7) and o-diphenolase (EC 1. 10.3.1) increased steadily up to the third week of storage and thereafter decreased to the fifth week. The intensity and rapidity of browning in tubers when cut, correlated very closely with the tuber o-diphenolase and phenolic content levels while the onset of rotting correlated with the peroxidase activity levels in the species studied.     

Effect of the percentage carbon equivalent on the nodule characteristics,density and modulus of elasticity of ductile cast iron

Successful melting and Mg treatment were conducted using a vortex unit which produced spheroidal graphite (SG) Fe ingots having a percentage carbon equivalent (%CE) ranging from 3.782 to 5.240. Microstructure examination revealed graphite nodules embedded in a white matrix (unetched condition). The variation of %CE proved to have a pronounced effect on the nodule characteristics. The nodule count showed a maximum value at %CE of 4.613. For metal-mould ingots it reached a value of 1584 nodules mm^–2, while for sand-mould ingots it reached a value of 970 nodules mm^–2. Nodule size was found to be inversely proportional to the nodule count for both sand- and metal-mould ingots. The nodularity of all ingots was, in general, higher than 95%. The density of SG Fe was found to decrease gradually (at %CE=3.782) from 7242 to 6969 kg m^–3. The modulus of elasticity (E) showed a boat-like curve having minimum values of 189 and 192 GPa for the sand and metal moulds, respectively.     

Morphological responses in thermally conditioned linear low density polyethylene

An octene-modified linear low density polyethylene has been used to examine the mechanisms involved during thermal annealing. Annealing temperatures ranged from 60 to 100°C. Annealing results in crystallinity increments and these respond to two concurrent effects. One involves the segregation from crystalline regions of low molecular weight moieties in the polymer's molecular weight distribution; the other is lamellar thickening, leading to the formation of more highly perfected crystalline domains. In the present polymer, the two effects were found to be in balance at annealing temperatures near 80°C leading to the optimum distribution of crystalline regions in the amorphous portions of the polymer. The effect of thermal conditioning on mechanical properties of the polymer was illustrated in terms of the initial modulus and the polymer's yield strength. The twin mechanisms of molecular fractionation and lamellar thickening were found to influence both of the mechanical property parameters.     

Dynamic-mechanical properties of polybutadiene rubbers

The dynamic properties of high-cis (98%) and cis-trans (42% cis) polybutadienes, crosslinked with 0.1 to 1.0% of crosslinking agent, have been studied using a torsion pendulum method over the temperature range ?170 to +20°C. For the high-cis rubber plots of damping factor (tan δ) against temperature showed the expected peak in the glass-transition region with an additional peak in the neighbourhood of 0°C attributable to crystallization. The cis-trans rubber showed two damping maxima in the transition region, separated by 30 to 40°C (depending on the degree of crosslinking), suggesting incipient phase separation of the component structures. The rebound resilience of the high-cis rubber at room temperature exceeded that of the cis-trans, reaching 92% at the highest crosslink density. Plots of resilience versus temperature for both rubbers showed a single minimum in the glass transition region.     

A novel silicon Schottky diode for NLTL applications

The design and simulation of a novel silicon Schottky diode for nonlinear transmission line (NLTL) applications is discussed in this paper. The Schottky diode was fabricated on a novel silicon-on-silicide-on-insulator (SSOI) substrate for minimized series resistance. Ion implantation technology was used as a low-cost alternative to molecular beam epitaxy to approximate the delta (/spl delta/) doping profile, which results in strong nonlinear CV characteristics. The equivalent circuit model of the Schottky diode under reverse bias conditions was extracted from the S-parameter measurement performed on the diode. The measured CV characteristics show strong nonlinearity, the junction capacitance varies from 182 to 47.5 fF as the reverse bias voltage is varied from 0 to -5 V. A parasitic inductance of 40 pH was measured for the silicon Schottky diode, which is much smaller than a comparable sized GaAs Schottky diode. This small inductance is an advantage for the silicon Schottky diode offering improvement in the silicon NLTL performance.     

Pyramid collaborative filtering technique for an intelligent autonomous guide agent

This article presents an autonomous guide agent that can observe a community of learners on the web, interpret the learners' inputs, and then assess their sharing. The goal of this agent is to find a reliable helper (tutor or other learner) to assist a learner in solving his task. Despite the growing number of Internet users, the ability to find helpers is still a challenging and important problem. Although helpers could have much useful information about courses to be taught, many learners fail to understand their presentations. For that, the agent must be able to deal autonomously with the following challenges: Do helpers have information that the learners need? Will helpers present information that learners can understand? And can we guarantee that these helpers will collaborate effectively with learners? We have developed a new filtering framework, called a pyramid collaborative filtering model, to whittle the number of helpers down to just one. We have proposed four levels for the pyramid. Moving from one level to another depends on three filtering techniques: domain model filtering, user model filtering, and credibility model filtering. A new technique is filtering according to helpers' credibilities. Our experiments show that this method greatly improves filtering effectiveness. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1065–1082, 2007.     

Effect of electric field on the vapor-phase growth of carbon nanostructures

A mathematical model of dc gas discharge plasma has been developed in order to determine the electric field strength at a substrate surface during plasmachemical deposition of carbon nanostructures. A numerical solution of the model equations has been obtained using the experimentally determined boundary conditions and model parameters. A comparison of the solution to experiment confirms the adequacy of the proposed mathematical model, which provides the electric field profiles and the electron and ion density distributions near the substrate surface. Estimations show that, for carbon nanostructures with a characteristic size of about 30 nm, the electric field strength at the surface is sufficiently high to provide for their directional growth along the field.     

CONTEXTUALIZING LEARNING OBJECTS USING ONTOLOGIES

Educational research over the past three years has intensified such that the context of learning resources needs to be properly modeled. Many researchers have described and even mandated the use of ontologies in the research being conducted, yet the process of actually connecting one or more ontologies to a learning object has not been extensively discussed. This paper describes a practical model for associating multiple ontologies with learning objects while making full use of the IEEE LOM specification. The model categorizes these ontologies according to five major categories of context based on the most popular fields of study actively being pursued by the educational research community: Thematic context, Pedagogical context, Learner context, Organizational context, and Historical/Statistical context.