Photodegradation of poly(neopentyl terephthalate)

In this paper we investigate the mechanism of photodegradation in simulated sun light (in a SUNTEST XXL+) of a polyester based on terephthalic units (poly(neopentyl terephthalate); PNT). The mechanisms of degradation were studied with MALDI-ToF MS, ATR-FTIR and SEC.     

Enriching breakfast sausages by feeding pigs with CLA supplemented diets

Approaches for improving the profile of functional unsaturated fatty acids in pork products include dietary supplementation of pigs with functional oils. Little information is available to indicate the benefit of this approach in a processed and cooked pork product such as breakfast sausages. Therefore, the aim of the present study is to examine the fatty acid profile and oxidation level in cooked pork sausages, produced following dietary supplementation with CLA compared to sunflower oil (SFO). Fat and moisture percentages, total fatty acid profiles and TBARS were analysed. Fatty acid profiles were altered in the sausages following all treatments. While a stronger effect was seen for CLA treatments, addition of SFO in the diet also resulted in linear increases of CLA in the sausages. CLA supplementation resulted in increased saturated fatty acid content; however, all treatments were within the recommended polyunsaturated/saturated fatty acid ratio of above 0.4. Improved oxidative stability was observed in sausages from CLA supplemented diets.     

Label-dependent node classification in the network

Relations between objects in various systems, such as hyperlinks connecting web pages, citations of scientific papers, conversations via email or social interactions in Web 2.0 portals are commonly modeled by networks. One of many interesting problems currently studied for such domains is node classification. Due to the nature of the networked data and the unavailability of collection of nodes' broad representation for training in majority of environments, only a very limited data may remain useful for classification. Therefore, there is a need for accurate and efficient algorithms that are able to perform good classification based only on scanty knowledge of network nodes.A new approach of sampling algorithm—LDGibbs, used in the context of collective classification with application of label-dependent features, is proposed in the paper in order to provide more accurate generalization for sparse datasets. Additionally, a new LDBootstrapping algorithm based on label-dependent features has been developed. Both new algorithms include additional steps to extract new input features based on graph structures but limited only to the nodes of a given label. It means that a separate set of structural features is provided for each label. The comparison with the other approaches, in particular with standard Gibbs Sampling and bootstrapping provided satisfactory results and revealed LDGibbs's superiority.     

A framework for interactive image color editing

We propose a new method for interactive image color replacement that creates smooth and naturally looking results with minimal user interaction. Our system expects as input a source image and rawly scribbled target color values and generates high quality results in interactive rates. To achieve this goal we introduce an algorithm that preserves pairwise distances of the signatures in the original image and simultaneously maps the color to the user defined target values. We propose efficient sub-sampling in order to reduce the computational load and adapt semi-supervised locally linear embedding to optimize the constraints in one objective function. We show the application of the algorithm on typical photographs and compare the results to other color replacement methods.     

Relational large scale multi-label classification method for video categorization

The problem of automated video categorization in large datasets is considered in the paper. A new Iterative Multi-label Propagation (IMP) algorithm for relational learning in multi-label data is proposed. Based on the information of the already categorized videos and their relations to other videos, the system assigns suitable categories—multiple labels to the unknown videos. The MapReduce approach to the IMP algorithm described in the paper enables processing of large datasets in parallel computing. The experiments carried out on 5-million videos dataset revealed the good efficiency of the multi-label classification for videos categorization. They have additionally shown that classification of all unknown videos required only several parallel iterations.     

Surface Tension,Density, and Thermal Expansionof (Bi-Ag)<Subscript>eut</Subscript>-Zn Alloys

The thermophysical properties of Bi-Ag eutectic-based alloys with additions of 3 at.%, 6 at.%, and 9 at.% Zn are presented. The density of liquid alloys was determined using the dilatometric method, while the surface tension was measured using the maximum bubble pressure method. Thermal expansion of solid alloys was measured with an optical dilatometric technique. It was found that addition of zinc to the Bi-Ag eutectic slightly decreases density, while an increase of the surface tension and thermal expansion coefficient is observed. Relatively good agreement is observed between surface tension calculated from the thermodynamic model and the experimental data.