Pure titanium particle loaded nanocomposites: study on the polymer/filler interface and hMSC biocompatibility

The integration of inorganic nanoparticles into polymer matrices allows for the modification of physical properties as well as the implementation of new features for unexplored application fields. Here, we propose the study of a new metal/polymer nanocomposite fabricated by dispersing pure Ti nanoparticles into a poly(methylmetacrilate) matrix via solvent casting process, to investigate its potential use as new biomaterial for biomedical applications. We demonstrated that Ti nanoparticles embedded in the poly(methylmetacrilate) matrix can act as reinforcing agent, not negatively influencing the biological response of human mesenchymal stem cell in terms of cytotoxicity and cell viability. As a function of relative amount and surface treatment, Ti nanoparticles may enhance mechanical strength of the composite—ranging from 31.1?±?2.5 to 43.7?±?0.7?MPa—also contributing to biological response in terms of adhesion and proliferation mechanisms. In particular, for 1?wt% Ti, treated Ti nanoparticles improve cell materials recognition, as confirmed by higher cell spreading-quantified in terms of cell area via image analysis—locally promoting stronger interactions at cell matrix interface. At this stage, these preliminary results suggest a promising use of pure Ti nanoparticles as filler in polymer composites for biomedical applications.     

A topological reconfiguration procedure for maximising local consumption of renewable energy in (Italian) active distribution networks

Distribution networks (DNs) are facing great changes, due to the strong increase in distributed generation (DG), often driven by renewable energy sources. Designed to deliver electrical power from the transmission system to the final consumers, they are now becoming active and may inject power into the transmission network. In case of large DN, a portion of the system can be absorbing power from the transmission grid, while another portion injects power into it. In order to satisfy the power balance as much as possible at the local level, the distribution system operators are interested in the minimisation of the power exchange with the transmission network, maximising the local consumption of DG energy. This paper presents a topological reconfiguration procedure, based on the branch exchange technique, for the maximisation of the local consumption of renewable energy. A case study is presented, based on a real DN located in northern Italy.     

Development and test of a new fuzzy-QFD approach for characterizing customers rating of extra virgin olive oil

This paper presents the development of an innovative fuzzy-QFD based methodology for characterizing customer rating of food products. The method has been tested on different samples of extra virgin olive oil to verify its suitability.The results demonstrated the effectiveness of such multi-criterion technique not only for the design and development of new products that meet customers’ requirements, but also for testing the quality of existing ones.The main innovation of the method, consists in the application of the fuzzy logic to address the issue, common in many decisional techniques, of dealing with data deriving from subjective verbally expressed evaluations that cannot be treated with mathematical models.The objective of this work was to test the combined assessment technique based on quality function deployment and fuzzy logic method for determining which characteristics of extra virgin olive oil influence most of the acceptance of the consumers toward the product. The relationship between consumer expectations, defined by a market survey, and main attributes of the examined products were assessed by means of the House of Quality (HOQ). The results obtained allowed to classify the quality of different brands of olive oil with respect to customer preferences.     

Current and Forward‐Looking Approaches to Technological and Nutritional Improvements of Gluten‐Free Bread with Legume Flours: A Critical Review

The gluten‐free market currently offers a range of products which can be safely consumed by patients affected by celiac disease. Nevertheless, challenges for optimal formulation remain on the way in terms of appreciable texture, flavor, and adequate nutritional characteristics. Within that framework, legumes have recently attracted attention among scientists as structure‐ and texture‐forming agents, as source of nutrients and bioactive compounds, and as a low‐glycemic‐index ingredient. This work aims at providing an updated and comprehensive overview of the advantages and disadvantages in the use of legumes in gluten‐free breadmaking. It also shows how legumes can contribute to tackling the main technological, nutritional, and organoleptic challenges. From this critical analysis, it emerged that viscoelastic properties of gluten‐free bread batter can be enhanced by the use of carob germ, chickpea, lupin, and soybean. Gluten‐free bread organoleptic acceptability can be improved by incorporating leguminous flours, such as carob, chickpea, lupin, and soybean. Moreover, a better nutritional quality of gluten‐free bread can be obtained by the addition of chickpea and soybean. Gaps and needs in the use of legumes in gluten‐free breadmaking emerged and were gathered together to have a sound basis for future studies. The technological and nutritional potential of sourdough should be more extensively exploited. Moreover, in vitro and in vivo studies should be prompted to understand the health benefits of bread formulated with legumes. A holistic approach, interfacing food science, nutrition, and health might help to have, on the market, products with improved sensory properties and nutritional profile.     

Protein Flexibility in Drug Discovery: From Theory to Computation

Nowadays it is widely accepted that the mechanisms of biomolecular recognition are strongly coupled to the intrinsic dynamic of proteins. In past years, this evidence has prompted the development of theoretical models of recognition able to describe ligand binding assisted by protein conformational changes. On a different perspective, the need to take into account protein flexibility in structure‐based drug discovery has stimulated the development of several and extremely diversified computational methods. Herein, on the basis of a parallel between the major recognition models and the simulation strategies used to account for protein flexibility in ligand binding, we sort out and describe the most innovative and promising implementations for structure‐based drug discovery.     

Dominance and influence of selected Saccharomyces cerevisiae strains on the analytical profile of craft beer refermentation

This study investigated the influence of Saccharomyces cerevisiae strains inoculated at the refermentation phase on the analytical profile of craft beer. After preliminary screening of 33 S. cerevisiae strains, four were selected and used in bottle refermentation trials. To attribute the flavour profile of the refermented beers to the inoculated strains, molecular characterization was carried out using a mini‐satellite protocol of amplification with inter‐δ primers. Fingerprinting analysis of 500 isolates showed that all of the inoculated strains used in the bottle refermentation dominated the process. The main analytical characters across the bottle refermentation trials were similar, while there were distinctive and significant variations in the volatile compounds. In particular, when compared with the starter strain used as control, the bottle refermentation trials using the DBVPG 2170, DBVPG 2187 and L951 S. cerevisiae strains showed significantly higher levels of the volatile compounds that are responsible for fruity and flowery aromas (i.e. isoamyl acetate, ethyl octanoate, ethyl dodecanoate phenyl ethyl acetate, β‐phenyl ethanol). This study indicates that the proper refermentation process results in the dominance of the selected starter strain, which produces fermentation compounds that show a specific analytical profile and give the craft beer its distinctive bioflavour. Copyright © 2014 The Institute of Brewing & Distilling     

A continuous-state Markov model for age- and state-dependent degradation processes

In order to approximate the unknown transition probability densities of a state-dependent, possibly inhomogeneous, Markov degradation model, a continuous-state discrete-time Markov model is proposed, which is based on the use of the Pearson’s family of distributions for approximating the true transition density. Unlike the alternative approach based on Markov chain approximation, the proposed one has the decisive advantage of dramatically reducing the computing time of the estimation procedure, thus allowing a age- and state-dependent model to be potentially applied also in more complex experimental frameworks, e.g., in presence of random effects. Hence, the proposed model is used to analyse, on the basis of real data from the literature, two different degradation phenomena, namely: the wear of some cutting tools and the crack growth of metallic specimens.