Electrical and mechanical characterization by instrumented indentation technique of La0.85Sr0.15Ga0.8Mg0.2O3−δ electrolyte for SOFCs

La_0.85Sr_0.15Ga_0.8Mg_0.2O_3?δ pellets obtained by the polymeric organic complex solution method, isostatic pressing and sintering at 1350 °C have been electrical and mechanically studied. Electrical measurements evidenced reasonable ionic conductivities (0.01 S cm^?1 at 800 °C), which were comparable to those reported for the La_1?xSr_xGa_1?yMg_yO_3?δ prepared by other synthesis methods. On the other hand, the mechanical properties (elastic modulus, E and hardness, H) have been determined at micro/nanometric scale using the instrumented indentation technique. While E did not vary significantly with the increasing indentation depth (h), H values strongly decreased with the indentation depth up to 500 nm. For h > 500 nm, both mechanical properties remained almost constant, thus obtaining E = 271 ± 6 GPa and H = 13.2 ± 0.4 GPa. Finally, the residual imprints and fracture mechanisms have been observed by atomic force microscopy (AFM).     

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.     

Core–shell polypyrrole nanoparticles obtained by atmospheric pressure plasma polymerization

Polypyrrole hollow nanoparticles were prepared by atmospheric pressure plasma polymerization. The structure of the nanoparticles was studied using Fourier transform infrared and X‐ray photoelectron spectroscopies, thermogravimetric analysis, scanning and transmission electron microscopies and atomic force microscopy. In contrast to low‐pressure plasma polymerization of pyrrole, which can produce films and solid nanoparticles, we obtained two types of hollow nanoparticles: a fraction with single spherical core and another with a core composed of small bubbles. Thermal characterization allowed us to determine that the nanoparticles are composed of highly crosslinked polymer. A mechanism that explains the formation of both types of hollow nanoparticles as well as solid nanoparticles is proposed. Chemical characterization shows that, in addition to the expected chemical structures due to pyrrole polymerization, the high energy of the plasma at atmospheric pressure produces intense dehydrogenation and oxidation processes. The fluorescence spectrum of the nanoparticles, however, shows a peak at 482 nm indicating that some degree of π‐conjugation is present in the material. © 2014 Society of Chemical Industry     

Health-promoting effects in the gut and influence on lipid metabolism of Himanthalia elongata and Gigartina pistillata in hypercholesterolaemic Wistar rats

The intake of Himanthalia elongata and Gigartina pistillata from the Spanish Atlantic coasts was evaluated in Wistar rats. Both seaweed diets showed higher (p < 0.001) faecal excretion. Colonic fermentation increased (p < 0.001) total short-chain fatty acids (SCFAs) in Himanthalia-fed rats due to the higher (p < 0.001) levels of acetic, propionic and butyric acids. The intake of Gigartina increased (p < 0.001) propionic acid and decreased (p < 0.001) butyric acid. The apparent absorption and true retention of calcium and magnesium enhanced (p < 0.05) with Himanthalia diet, while Gigartina produced no significant effect. The serum concentration of HDL-C increased (p < 0.01), triglycerides (TGL) decreased (p < 0.001) and bile acids diminished (p < 0.001) in faeces of Himanthalia-fed rats. The Gigartina diet produced a decrease (p < 0.001) in TGL, total cholesterol (p < 0.01) and LDL-C (p < 0.05) in serum and reduced TGL in liver (p < 0.001). Thus, both seaweeds improved the lipid profile, and Himanthalia increased SCFA production and the absorption and retention of Ca and Mg as a result of the gut fermentation.     

Mechanical Characterization of Copper-Copper Wires Joined by Friction Welding Using Instrumented Indentation Technique

Friction welding samples of both the fire-refined high-conductivity (FRHC) and electrolytically tough pitch (ETP) copper alloy wires have been mechanically characterized by instrumented indentation technique and tensile test. Hardness profiles in the perpendicular direction to the weld interface, in both the central and peripheral zones, of the as-welded FRHC-FRHC and ETP-ETP samples have been investigated at nano-/micrometric scale. The microstructures of welds have been observed using both the optical microscopy and scanning electronic microscopy. The results show the typical friction welding zones: the interface zone, the thermo-mechanically affected zone (TMAZ), and the transition zone between the TMAZ and the base metal zone (BMZ) that present a microstructure and hardness close to the base metal. No presence of a heat-affected zone is observed. Although both welds show the same tendency in hardness distribution, FHRC-FHRC weld presents a TMAZ narrower than ETP-ETP one, which produces a stronger drop in hardness with increasing of the distance from welding central line, and a higher difference in hardness between the central and peripheral zones. The tensile tests of ETP-ETP welds showed that all samples broke by the BMZ that is far away from the interface of the welded joint, while the most of the FRHC-FRHC welds are broken at the TMAZ region at low strengths. These appreciable differences in mechanical properties for the FHRC-FHRC welds are probably generated by a stronger variation in their microstructural properties. Therefore, it may justify the welding failures in the FHRC-FHRC weld at the typical tensile stress for an industrial cold-drawn process of wires.     

Medical knowledge management for specific hospital departments

Medical knowledge representation and management is concerned with how to organise the often vague clinical experience of medical staff required for computable models. However, few knowledge management and acquisition tools have entered routine use, since such tools are not perceived by physicians as part of the clinical information process. An attempt to partially solve this problem, we identify two key aspects of knowledge representation and management tasks. The first is to adopt a medical knowledge standardisation to provide a consistent terminology control and to simplify the integration between knowledge management tools and the health information system. The second is to establish an effective knowledge acquisition process in specific medical fields by adapting knowledge acquisition tools. Therefore, the main goal of this work is to define computational models and to design mechanisms for the effective acquisition and management of medical knowledge in real-life hospital departments. To this end, we analyse the representation of medical knowledge (based on deep-causal models) and the development of knowledge management tools (based on ontologies), integrated within the information processing activities of the clinical user. Finally, we illustrate its applicability in the Intensive Care Unit and Pediatry scenarios.