Content and English Language Integrated Learning: The use of Moodle in Aircraft Maintenance Training Programs

The aim of this work is to develop a prototype of an e-learning environment that can foster Content and Language Integrated Learning (CLIL) for students enrolled in an aircraft maintenance training program, which allows them to obtain a license valid in all EU member states. Background research is conducted to retrace the evolution of the field of educational technology, analyzing different learning theories – behaviorism, cognitivism, and (socio-)constructivism – and reflecting on how technology and its use in educational contexts has changed over time. Particular attention is given to technologies that have been used and proved effective in Computer Assisted Language Learning (CALL). Based on the background research and on students’ learning objectives, i.e. learning highly specialized contents and aeronautical technical English, a bilingual approach is chosen, three main tools are identified – a hypertextbook, an exercise creation activity, and a discussion forum – and the learning management system Moodle is chosen as delivery medium. The hypertextbook is based on the technical textbook written in English students already use. In order to foster text comprehension, the hypertextbook is enriched by hyperlinks and tooltips. Hyperlinks redirect students to webpages containing additional information both in English and in Italian, while tooltips show Italian equivalents of English technical terms. The exercise creation activity and the discussion forum foster interaction and collaboration among students, according to socio-constructivist principles. In the exercise creation activity, students collaboratively create a workbook, which allow them to deeply analyze and master the contents of the hypertextbook and at the same time create a learning tool that can help them, as well as future students, to enhance learning. In the discussion forum students can discuss their individual issues, content-related, English-related or e-learning environment-related, helping one other and offering instructors suggestions on how to improve both the hypertextbook and the workbook based on their needs.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Development of a fluorescent-based single liposome assay for studying calcium transporter LMCA1

The morphological and functional unit of all the living organisms is the cell. The transmembrane proteins, localized in the plasma membrane of cells, play a key role in the survival of the cells themselves. These proteins perform a variety of different tasks, for example the control of the homeostasis. In order to control the homeostasis, these proteins have to regulate the concentration of chemical elements, like ions, inside and outside the cell. These regulations are fundamental for the survival of the cell and to understand them we need to understand how transmembrane proteins work. Two of the most important categories of transmembrane proteins are ion channels and transporter proteins. The ion channels have been depth studied at the single molecule level since late 1970s with the development of patch-clamp technique. It is not possible to apply this technique to study the transporter proteins so a new technique is under development in order to investigate the behavior of transporter proteins at the single molecule level. This thesis describes the development of a nanoscale single liposome assay for functional studies of transporter proteins based on quantitative fluorescence microscopy in a highly-parallel manner and in real time. The transporter of interest is the prokaryotic transporter Listeria Monocytogenes Ca2+-ATPase1 (LMCA1), a structural analogue of the eukaryotic calcium pumps SERCA and PMCA. This technique will allow the characterization of LMCA1 functionality at the single molecule level. Three systematically characterized fluorescent sensors were tested at the single liposome scale in order to investigate if their properties are suitable to study the function of the transporter of interest. Further studies will be needed in order to characterize the selected calcium sensor and pH sensor both implemented together in single liposomes and in presence of the reconstituted protein LMCA1.