Non-destructive ultrasonic investigation of the structure state of steam pipelines

The main purpose of the work is to study the dependence of the ultrasonic wave parameters on the structure state in tubes of boilers at thermo-electric power station. The changes of the velocity, spectra and attenuation of ultrasonic surface waves are caused by degradation of the structure and can be used for residual life estimation of the equipment.     

Novel alginate based nanocomposite hydrogels with incorporated silver nanoparticles

Alginate colloid solution containing electrochemically synthesized silver nanoparticles (AgNPs) was investigated regarding the nanoparticle stabilization and possibilities for production of alginate based nanocomposite hydrogels in different forms. AgNPs were shown to continue to grow in alginate solutions for additional 3 days after the synthesis by aggregative mechanism and Ostwald ripening. Thereafter, the colloid solution remains stable for 30 days and could be used alone or in mixtures with aqueous solutions of poly(vinyl alcohol) (PVA) and poly(N-vinyl-2-pyrrolidone) (PVP) while preserving AgNPs as verified by UV–Vis spectroscopy studies. We have optimized techniques for production of Ag/alginate microbeads and Ag/alginate/PVA beads, which were shown to efficiently release AgNPs decreasing the Escherichia coli concentration in suspensions for 99.9% over 24 h. Furthermore, Ag/hydrogel discs based on alginate, PVA and PVP were produced by freezing-thawing technique allowing adjustments of hydrogel composition and mechanical properties as demonstrated in compression studies performed in a biomimetic bioreactor.     

Relationship between the Undrained Shear Strength, Water Content, and Mineralogical Properties of Fine-Grained Soils

The relationship between the undrained shear strength of fine-grained soils and the water content can be described with a nonlinear function in which the type of soil is determined by two parameters. It is well known that these parameters depend mainly on the mineral compositions of soils; these relationships, however, have not yet been investigated. The findings described in this paper define those mineralogical properties of soils which determine the values of both parameters. Experimentally obtained results suggest that the parameters primarily depend on the size of the clay minerals, their quantity in soil composition, and the interlayer water quantity in the expanding clay minerals. As this dependence is well defined, the parameters, and thus the undrained shear strength at different water content, can be defined from knowledge of these mineralogical soil properties.     

A new approach for kinetic modeling and optimization of rubber molding

Although extensive research has been carried out on the understanding of the complex vulcanization process, the influence of reversion through exposure time and temperature on the vulcanization degree remains unclear. Therefore, the main aim of this study was a novel optimization approach that can help the industrial practitioners to select the optimal operating parameters, exposure time, and molding temperature, to achieve desired vulcanization degree of selected product. Spheres of four different diameters (2.5, 5, 10, and 20 cm) were selected as test geometry for simulation and optimization of rubber molding. Obtained vulcanization rheometer data for commercially available rubber blend (NR/SBR) were fitted by a new modeling approach, dividing vulcanization curve into two fitting sets: curing and reversion. The heat transfer equations for chosen geometry were coupled with proposed kinetic model. A new temperature-dependent kinetic parameter x, as the maximal reversion degree, was introduced, enabling determination of the lowest operating molding temperature (T_min = 132.36 °C), preventing high reversion and overheating of the rubber product. The final optimization goal was assessment of the optimal temperature and vulcanization time dependence on the rubber products dimensions. Proposed models have precise prediction with R² values greater than 0.8328 and MAPE less than 2.3099%.     

AMPK Activation Is Important for the Preservation of Insulin Sensitivity in Visceral,but Not in Subcutaneous Adipose Tissue of Postnatally Overfed Rat Model of Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a well-known reproductive syndrome usually associated with obesity, insulin resistance, and hyperinsulinemia. Although the first signs of PCOS begin early in adolescence, it is underexplored whether peripubertal obesity predisposes women to PCOS metabolic disturbances. To highlight that, we examined the impact of postnatal overfeeding-induced obesity, achieved by litter size reduction during the suckling period, on metabolic disturbances associated with visceral and subcutaneous adipose tissue (VAT and SAT) function in the 5α-dihydrotestosterone (5α-DHT)-induced animal model of PCOS. We analyzed markers of insulin signaling, lipid metabolism, and energy sensing in the VAT and SAT. Our results showed that postnatally overfed DHT-treated Wistar rats had increased VAT mass with hypertrophic adipocytes, together with hyperinsulinemia and increased HOMA index. In the VAT of these animals, insulin signaling remained unchanged while lipogenic markers decreased, which was accompanied by increased AMPK activation. In the SAT of the same animals, markers of lipogenesis and lipolysis increased, while the activity of AMPK decreased. Taken together, obtained results showed that postnatal overfeeding predisposes development of PCOS systemic insulin resistance, most likely as a result of worsened metabolic function of SAT, while VAT preserved its tissue insulin sensitivity through increased activity of AMPK.     

Uncensoring censored data for machine learning: A likelihood-based approach

Various machine learning techniques have been applied to different problems in survival analysis in the last decade. They were usually adapted to learning from censored survival data by using the information on observation time. This includes learning from parts of the data or interventions to the learning algorithms. Efficient models were established in various fields of clinical medicine and bioinformatics. In this paper, we propose a pre-processing method for adapting the censored survival data to be used with ordinary machine learning algorithms. This is done by pre-assigning censored instances a positive or negative outcome according to their features and observation time. The proposed procedure calculates the goodness of fit of each censored instance to both the distribution of positives and the spoiled distribution of negatives in the entire dataset and relabels that instance accordingly. We performed a thorough empirical testing of our method in a simulation study and on two real-world medical datasets, using the naive Bayes classifier and decision trees. When compared to one of the popular ML methods dealing with survival, our method provided good results, especially when applied to heavily censored data.     

Wood and bark of some poplar and willow clones as fuelwood

Poplars and willows are widely used to produce biomass for energy. Calorific values of wood and bark, as well as for whole tree of Populus × euramericana (cl. I-214), Populus deltoides (cl.PE 19/66) and white willow Salix alba (cl.378) of different ages were determined. one- and 2-year-old rooted cuttings were grown in plantations with high planting density, in order to produce a high biomass yield per hectare. Mature trees in both species (poplar and willow) originated from the corresponding plantations; willow 14-year old, and poplar 12 years (cl.I-214) and 8 years (cl.PE 19/66). As the share of bark depends on the age of wood, calorific values were determined separately for bark and for wood. The share of bark (proportion of total weight) in 1- and 2-year-old rooted cuttings ranged between 18% and 27%, and in older trees it was from 10% to 15%. The higher heating values of oven dry poplar wood (calculated for the whole tree, based on the proportion of bark) were from 15,787 (cl. I-214 1-year old) to 24,275 kJ/kg (cl.I-214 2-year old). The average calorific values of willow wood (whole tree with bark) were from 16,169 (14-year old) to 22,572 kJ/kg (2-year old). It should be pointed out that the calorific value of wood is more favorable than that of bark, and the highest calorific values refer to 2-year-old trees.     

Combined effects of inulin,pectin and guar gum on the quality and stability of partially baked frozen bread

Many attempts have been made to increase the nutritional value of bread by adding dietary fibre. However, fibre enrichment is usually associated with various technological problems. The aim of this study was to optimise the composition of a blend of inulin, pectin and guar gum to enrich the fibre content of partially baked frozen bread without impairing its technological quality. We prepared 20 formulations following a central composite design, together with 4 control breads. Bread enriched with inulin had higher crumb hardness, lower specific volume, shape, moisture content, and crumb cohesiveness than control bread, but improved flavour. Pectin and guar improved moisture content and crumb cohesiveness. There was no interaction between inulin and pectin for any of the bread attributes investigated, while interactions between inulin and guar were small. In contrast, guar and pectin significantly interacted to decrease volume and increase crumb hardness and chewiness. A desirability function method identified the optimised blend as containing 3% inulin, 0.9–1% pectin and 0.3–0.4% guar. Bread enriched with such blend had the following characteristics: specific volume, 4.06 cm³/g; shape, 0.63; crumb hardness, 189 g; resilience, 0.36; cohesiveness, 0.84; chewiness, 169 g; and flavour score, 4.6. Experimental values were close to the predicted ones, with prediction errors below 10% for all attributes tested. The specific volume, crumb hardness and chewiness of the enriched bread were superior to those of unenriched bread. However, undesirable textural changes occurred in the enriched bread during 12 weeks of frozen storage, and these changes strongly depended on the fibre blend composition.