Species identification, distributioin and reproductive interactions of common smoot-hound and blackspotted smooth-hound shark (Genus mustelus) in the Adriatic Sea

Longstanding taxonomic ambiguity and uncertainty exist in the identification of the common (M. mustelus) and blackspotted (M. punctulatus) smooth-hound in the Adriatic Sea. The lack of a clear and accurate method of morphological identification, leading to frequent misidentification, prevents the collation of species-specific landings and survey data for these fishes and hampers the delineation of the distribution ranges and stock boundaries of the species. In this context, adequate species-specific conservation and management strategies can not be applied without risks of population declining and local extinction. In this thesis work I investigated the molecular ecology of the two smooth-hound sharks which are abundant in the demersal trawl surveys carried out in the NC Adriatic Sea to monitor and assess the fishery resources. Ecological and evolutionary relationships were assessed by two molecular tests: a DNA barcoding analysis to improve species identification (and consequently the knowledge of their spatial ecology and taxonomy) and a hybridization assay based on the nuclear codominant marker ITS2 to evaluate reproductive interactions (hybridization or gene introgression). The smooth-hound sharks (N=208) were collected during the MEDITS 2008 and 2010 campaigns along the Italian and Croatian coasts of the Adriatic Sea, in the Sicilian Channel and in the Algerian fisheries. Since the identification based on morphological characters is not strongly reliable, I performed a molecular identification of the specimens producing for each one the cytochrome oxidase subunit 1 (COI) gene sequence (ca. 640 bp long) and compared them with reference sequences from different databases (GenBank and BOLD). From these molecular ID data I inferred the distribution of the two target species in the NC Adriatic Sea. In almost the totality of the MEDITS hauls I found no evidence of species sympatry. The data collected during the MEDITS survey showed an almost different distribution of M. mustelus (confined along the Italian coasts) and M. punctulatus (confined along the Croatian coasts); just one sample (Gulf of Venice, where probably the ranges of the species overlap) was found to have catches of both the species. Despite these data results suggested no interaction occurred between my two target species at least during the summertime (the period in which MEDITS survey is carried out), I still wanted to know if there were inter-species reproductive interactions so I developed a simple molecular genetic method to detect hybridization. This method is based on DNA sequence polymorphism among species in the nuclear ribosomal Internal Transcribed Spacer 2 locus (ITS2). Its application to the 208 specimens collected raised important questions regarding the ecology of this two species in the Adriatic Sea. In fact results showed signs of hybridization and/or gene introgression in two sharks collected during the trawl survey of 2008 and one collected during the 2010 one along the Italian and Croatian coasts. In the case that it will be confirmed the hybrid nature of these individuals, a spatiotemporal overlapping of the mating behaviour and ecology must occur. At the spatial level, the northern part of the Adriatic Sea (an area where the two species occur with high frequency of immature individuals) could likely play the role of a common nursery area for both species.

The use of english as a lingua franca for scientific dissemination and its impact on EFL speakers with a Ph.D.

English has become the lingua franca for scientific divulgation and definitely has an impact on EFL speakers. They have to develop competences in a foreign language to publish their scientific articles and to become part of a community. Years of study, effort, and many challenges are daily present in the life of the students of the sciences. However, despite a certain skepticism, the impact English has on EFL speakers with a Ph.D. is positive: they are highly competent in a foreign language which allows them to establish better relationships around the globe and improve the world of science through collaborations and the publication of scientific articles.

"Portugal Vale A Pena" Un ritratto senza tempo del portogallo attraverso il prisma dei giornalisti

This dissertation aims at enhancing the cultural and linguistic skills in Portuguese of the author of this work, as it is a third language. This activity is carried out starting from the analysis and research of topics mentioned in a number of texts within a particular literary work, “Portugal Vale A Pena”. In this work, many Portuguese personalities express their vision on their country and state why Portugal matters. Since these texts have many cultural references, it can be assumed that such work of analysis and research can lead to better linguistic skills as well as a greater knowledge of the Portuguese culture. All of the chosen texts were originally written by journalists. This choice originates from the important service these professionals provide to the public as well as from the special role their work has played in my interpreting studies over the last couple of years. Chapter 1 explains why I chose this dissertation and who are the target users of these texts. Chapter 2 focuses on the role of journalists. A brief history of modern journalism is presented and its functions are analysed. This chapter also includes a section that examines which values make an event newsworthy. Attention is then paid to the evolution of Portuguese journalism, from Salazar's dictatorship until today. Teaching of journalism in Portuguese academia is also presented. Then, a selection of Portuguese-language media is offered. Chapter 3 focuses on some aspects of Portugal, with particular attention to its history. Finally, Chapter 4 presents a selection of texts from the original book. This part provides a biography of the authors, a translation with a comment and a presentation of some of the topics from the texts. To conclude, a glossary with words and expressions from the original text is included and their translations into Italian, Spanish and English are provided.

The Presence of Words in Visual Art from Surrealism to Conceptualism

Without a doubt, one of the biggest changes that affected XXth century art is the introduction of words into paintings and, in more recent years, in installations. For centuries, if words were part of a visual composition, they functioned as reference; strictly speaking, they were used as a guideline for a better perception of the subject represented. With the developments of the XXth century, words became a very important part of the visual composition, and sometimes embodied the composition itself. About this topic, American art critic and collector Russell Bowman wrote an interesting article called Words and images: A persistent paradox, in which he examines the American and the European art of the XXth century in almost its entirety, dividing it up in six “categories of intention”. The aforementioned categories are not based on the art history timeline, but on the role that language played for specific artists or movements. Taking inspiration from Bowman's article, this paper is structured in three chapters, respectively: words in juxtaposition and free association, words as means of exploration of language structures, and words as means for political and personal messages. The purpose of this paper is therefore to reflect on the role of language in contemporary art and on the way it has changed from artist to artist.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.