Ordered porous nanomaterials: the merit of small

This paper will introduce the reader to some of the “classical” and “new” families of ordered porous materials which have arisen throughout the past decades and/or years. From what is perhaps the best-known family of zeolites, which even now to this day is under constant research, to the exciting new family of hierarchical porous materials, the number of strategies, structures, porous textures, and potential applications grows with every passing day. We will attempt to put these new families into perspective from a synthetic and applied point of view in order to give the reader as broad a perspective as possible into these exciting materials.

Geometrical study of the three-dimensional temperature–composition diagrams. An important aid to understand the behavior of the liquid–vapour equilibrium in ternary systems

In this work the usefulness of qualitatively studying and drawing three-dimensional temperature–composition diagrams for ternary systems is pointed out to understand and interpret the particular behavior of the liquid–vapour equilibrium of non-ideal ternary systems. Several examples have been used in order to highlight the interest and the possibilities of this tool, which should be an interesting support not only for lecturers, but also for researchers interested in experimental equilibrium data determination.

The aid of machine learning to overcome the classification of real health discharge reports written in Spanish

Hospitals attached to the Spanish Ministry of Health are currently using the International Classification of Diseases 9 Clinical Modification (ICD9-CM) to classify health discharge records. Nowadays, this work is manually done by experts. This paper tackles the automatic classification of real Discharge Records in Spanish following the ICD9-CM standard. The challenge is that the Discharge Records are written in spontaneous language. We explore several machine learning techniques to deal with the classification problem. Random Forest resulted in the most competitive one, achieving an F-measure of 0.876.

Aid decision algorithms to estimate the risk in congenital heart surgery

Background and objective: In this paper, we have tested the suitability of using different artificial intelligence-based algorithms for decision support when classifying the risk of congenital heart surgery. In this sense, classification of those surgical risks provides enormous benefits as the a priori estimation of surgical outcomes depending on either the type of disease or the type of repair, and other elements that influence the final result. This preventive estimation may help to avoid future complications, or even death. Methods: We have evaluated four machine learning algorithms to achieve our objective: multilayer perceptron, self-organizing map, radial basis function networks and decision trees. The architectures implemented have the aim of classifying among three types of surgical risk: low complexity, medium complexity and high complexity. Results: Accuracy outcomes achieved range between 80% and 99%, being the multilayer perceptron method the one that offered a higher hit ratio. Conclusions: According to the results, it is feasible to develop a clinical decision support system using the evaluated algorithms. Such system would help cardiology specialists, paediatricians and surgeons to forecast the level of risk related to a congenital heart disease surgery.

The Virtual Interactive Relationship Between BIM Project Teams: Effective Communication to aid Collaboration in the Design Process

Building Information Modelling (BIM) provides a shared source of information about a built asset, which creates a collaborative virtual environment for project teams. Literature suggests that to collaborate efficiently, the relationship between the project team is based on sympathy, obligation, trust and rapport. Communication increases in importance when working collaboratively but effective communication can only be achieved when the stakeholders are willing to act, react, listen and share information. Case study research and interviews with Architecture, Engineering and Construction (AEC) industry experts suggest that synchronous face-to-face communication is project teams’ preferred method, allowing teams to socialise and build rapport, accelerating the creation of trust between the stakeholders. However, virtual unified communication platforms are a close second-preferred option for communication between the teams. Effective methods for virtual communication in professional practice, such as virtual collaboration environments (CVE), that build trust and achieve similar spontaneous responses as face-to-face communication, are necessary to face the global challenges and can be achieved with the right people, processes and technology. This research paper investigates current industry methods for virtual communication within BIM projects and explores the suitability of avatar interaction in a collaborative virtual environment as an alternative to face-to-face communication to enhance collaboration between design teams’ professional practice on a project. Hence, this paper presents comparisons between the effectiveness of these communication methods within construction design teams with results of further experiments conducted to test recommendations for more efficient methods for virtual communication to add value in the workplace between design teams.