Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings.
Migration has become a structural part of the globalized society in which we live and, as such, it is essential to determine the causes and effects it produces in the involved social groups. Sociolinguistics has a very important role to play in this respect, insofar as its object of study focuses precisely on the analysis of the interrelationships between the linguistic and the social dimensions. This volume presents a series of proposals that involve theoretical approaches, models, and applications related to the process of sociolinguistic integration in contact situations arising from migration. The volume includes studies of general interest which present models and theoretical foundations for the analysis of this process of integration, as well as others which focus on other more specific aspects, such as how migration influences the construction of individual identity, emotional and affective factors in the preservation of the heritage language, and the processes of interlingual convergence that take place in situations of migratory contact. This volume also contains the didactic dimension applied to the immigrant population, with proposals for teaching with proven effectiveness.
Metallic biomaterials (biometals) are widely used for the manufacture of medical implants, ranging from load-bearing orthopaedic prostheses to dental and cardiovascular implants, because of their favourable combination of properties, including high strength, fracture toughness, biocompatibility, and wear and corrosion resistance. Owing to the significant consequences of implant material failure/degradation, in terms of both personal and financial burden, failure analysis of biometals has always been of paramount importance in order to understand the failure mechanisms and implement suitable solutions with the aim to improve the longevity of implants in the body. Failure Analysis of Biometals presents some of the latest developments and findings in this area. This includes a great range of common metallic biomaterials (Ti alloys, CoCrMo alloys, Mg alloys, and NiTi alloys) and their associated failure mechanisms (corrosion, fatigue, fracture, and fretting wear) that commonly occur in medical implants and surgical instruments.
Develops generalised just war principles that can be applied to all forms of armed conflict.
The importance of understanding metal–microbe interactions underlies a number of social–economic issues in the world. The antimicrobial resistance era has created a need for novel antimicrobials and within this fieldm metal and metalloid ions are promising solutions. Pollution sites, either co-contaminated with metals or with metals as the sole pollutant, contain microbes that are present as key participants, with both of these issues habing links to agriculture. Microbes also play key roles in the global geochemical cycle of many elements. Such statements solidify the need to understand metal–microbe interactions. Given that genomics has arguably become the most useful tool in biology, the application of this technology within the field of understanding metal resistance comes as no surprise. Whilst by no means comprehensive, this book provides examples of the applications of genomic approaches in the study of metal–microbe interactions. Here, we present a collection of manuscripts that highlights some present directions in the field. The book starts with a collection of three papers evaluating aspects of the genomics of the archetype metal resistant bacteria, Cuprividus metallidurans. This is followed by four studies that evaluate the mechanisms of metal resistance. The next two papers assess metal resistance in agricultural related situations, including a review on metal resistance in Listeria. The book concludes with a review on metal phytoremediation via Rhizobia and two subsequent studies of metal biotechnology relevance.
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