Prospects of the use of beta-carotene enriched food products in the prevention and therapy of radiation injuries]

Radio-protective effectiveness of short-term (19 and 4 h before, 4 and 24 h after irradiation), long-term (3 times/week during 30 days after irradiation) and delayed (1 or 2 days after irradiation) enrichment with crystallized beta-carotene, in single doses of 0.1, 1.0 or 5.0 mg was evaluated in experimental acute external gamma-irradiation (0.029 Gy/sec) within the range of absorbed doses 9--6 Gy. The results obtained have permitted the authors to recommend the ration enriched with carotinoid for prevention and therapy of acute radiation injuries.     

Morphological aspects of rubber fracture and wear

Morphology of carbon black (CB)‐filled rubber was studied with AFM and SEM and the classification of filler agglomerates, based on their internal structure and filler–matrix interactions, has been proposed. It varies according to the activity of CB and the kind of rubber. It has been shown that fracture of rubber starts either inside filler agglomerates (de‐cohesion) or in a filler–matrix interphase (de‐adhesion) initiating wear of the material. Microscopic observations correlate well with TGA and EPR data of wear debris collected during friction of rubber. The increase of thermal stability of CB and the appearance of additional spin signals, respectively, for elongated samples or debris, are proposed to be associated with de‐cohesion or de‐adhesion of the agglomerates. New approach to the fracture of rubber called “fatal agglomerate concept” is presented. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.     

Characterization of supported Pd-Pt catalysts by chemical probes

The temperature programmed (palladium) hydride decomposition appeared very effective method for diagnosing the extent of alloying in Pd-Pt/SiO₂ catalysts. Introduction of Pt to Pd catalysts moves the TPHD peak gradually towards lower temperatures and the shift in hydride decomposition peak is accompanied by a decrease in the amount of released hydrogen. The catalysts prepared the direct redox method showed much better alloy homogeneity than the samples prepared by coimpregnation. The results of probing with other techniques, i.e. catalytic probing with hydrodechlorination of CCl₂F₂ and XRD, were in line with TPHD data. The catalytic probing showed the presence of synergistic effect, a clear indication of Pd-Pt mixing. XRD data of post-reaction samples showed carbon incorporation into Pd-rich phase, whereas separate Pt-rich phase did not experience any bulk carbiding.