La comunicació des de la ciència : una assignatura encara pendent

In order to determine the areas in which scientific communication takes place and, in particular, communication from the field of science, this article establishes five circles. The first includes the interactions within each specialization; the second, the relations within the same branch of science; the third, within science as a whole; the fourth, within the society of knowledge, and the fifth, with society in general. From this starting point, diverse dysfunctions can be observed. In fact, communication works (though not without problems) in the framework of the relations between scientists in the same area of specialization. In this situation, two great channels of lateral communication are analyzed: journals and conferences. Outside of this first circle, many insufficiencies are detected in the descending communication (including the communication with other components of the same branch of science). And communication with the man in the street is found to be minimal, disordered and often incoheren

Chapter Machine Learning Models for Industrial Applications

More and more industries are aspiring to achieve a successful production using the known artificial intelligence. Machine learning (ML) stands as a powerful tool for making very accurate predictions, concept classification, intelligent control, maintenance predictions, and even fault and anomaly detection in real time. The use of machine learning models in industry means an increase in efficiency: energy savings, human resources efficiency, increase in product quality, decrease in environmental pollution, and many other advantages. In this chapter, we will present two industrial applications of machine learning. In all cases we achieve interesting results that in practice can be translated as an increase in production efficiency. The solutions described cover areas such as prediction of production quality in an oil and gas refinery and predictive maintenance for micro gas turbines. The results of the experiments carried out show the viability of the solutions

Toward a molecular profile of self-representation

Feeling embodiment over our body or body part has a major role in the understanding of the self and control of self-actions. Even though it is crucial in our daily life, embodiment is not an homogenous phenotype across population, as quantified by implicit and explicit measures (i.e., neuroimaging or self-reports). Studies have shown differences in neuropathological conditions compared to healthy controls, but also across healthy individuals. We discuss examples of self-perception differences, and the molecular origin of embodiment, focusing on clinical cases, during the first and second section. We then discuss two important questions in this molecular-to-embodiment relationship: (i) which are the molecular levels (and their associated techniques) that can be relevant to embodiment, and (ii) which are the most adequate experiments to correlate molecular profiles and embodiment quantification across individuals. Potential answers for both questions will be outlined during the third and fourth sections, respectively, in order to design a framework to study the molecular profile of body embodiment