European and Chinese legislation regulating the portrayal of women in television advertising: A comparison

This dissertation has two main purposes. On the one hand, it aims at comparing the gender stereotypes presented in the television commercials in China and in Europe. Considering the cultural, historical and socio-economical differences between these two contexts, it is interesting to examine the gender role models offered and used by the advertising industry in European Union and China in order to see if the gender stereotypes are similar and to evaluate to which extent they reflect, challenge or reinforce the gender roles of the society where they are broadcasted. On the other hand, the objective of this dissertation is to establish the degree of adequateness and effectiveness of the existing regulatory framework through an analysis of the positive and negative aspects of the regulatory acts issued to safeguard a fair representation of genders in the EU Member States and in China.

Phylogeny and phylogeography of the family Hyalidae (Crustacea: Amphipoda) along the northeast Atlantic coasts

The family Hyalidae comprises more than one hundred species, distributed worldwide. They are common and abundant in the littoral and shallow sublittoral habitats and they play an important role in the coastal food chain. Most studies about this family were dealing with taxonomy and ecology, while very little is known about phylogenetic relationship among genera and species. In the present study we aim to achieve the first approach of the phylogenetic patterns of this family in NE Atlantic Ocean and Mediterranean Sea, and to perform the first insight into the phylogeography Apohyale prevostii along both the North Atlantic coasts. In order to do that, eight species belonging to the genera Apohyale, Hyale, Serejohyale and Protohyale were investigated using the mitochondrial COI-5P barcode region. Specimens were collected along European and Moroccan Atlantic rocky shores, including Iceland, the British Isles, Macaronesia and in the Mediterranean Sea. Sequences of A. prevostii, from the NW Atlantic Ocean, available in BOLD and GenBank, were retrieved. As expected, phylogenetic analyses showed highly-divergent clades, clearly discriminating among different species clusters, confirming their morphology-based identifications. Although, within A. perieri, A. media, A. stebbingi, P. (Protohyale) schmidtii and S. spinidactylus, high genetic diversity was found, revealing putative cryptic species. The clade of A. prevostii and A. stebbingi appears well supported and divided from the other two congeneric species, and P. (Protohyale) schmidtii shows a basal divergence. The north-western Atlantic coasts were recently colonized by A. prevostii after the last glacial maximum from the European populations showing also a common haplotype in every population analysed. The use of the COI-5P as DNA barcode provided a good tool to underline the necessity of a revision of this emblematic family, as well as to discern taxonomically the possible new species flagged with this molecular device.

Long-period oscillations in GPS Up time series. Study over the European/Mediterranean area

The surface of the Earth is subjected to vertical deformations caused by geophysical and geological processes which can be monitored by Global Positioning System (GPS) observations. The purpose of this work is to investigate GPS height time series to identify interannual signals affecting the Earth’s surface over the European and Mediterranean area, during the period 2001-2019. Thirty-six homogeneously distributed GPS stations were selected from the online dataset made available by the Nevada Geodetic Laboratory (NGL) on the basis of the length and quality of the data series. The Principal Component Analysis (PCA) is the technique applied to extract the main patterns of the space and time variability of the GPS Up coordinate. The time series were studied by means of a frequency analysis using a periodogram and the real-valued Morlet wavelet. The periodogram is used to identify the dominant frequencies and the spectral density of the investigated signals; the second one is applied to identify the signals in the time domain and the relevant periodicities. This study has identified, over European and Mediterranean area, the presence of interannual non-linear signals with a period of 2-to-4 years, possibly related to atmospheric and hydrological loading displacements and to climate phenomena, such as El Niño Southern Oscillation (ENSO). A clear signal with a period of about six years is present in the vertical component of the GPS time series, likely explainable by the gravitational coupling between the Earth’s mantle and the inner core. Moreover, signals with a period in the order of 8-9 years, might be explained by mantle-inner core gravity coupling and the cycle of the lunar perigee, and a signal of 18.6 years, likely associated to lunar nodal cycle, were identified through the wavelet spectrum. However, these last two signals need further confirmation because the present length of the GPS time series is still too short when compared to the periods involved.

ICE Emissions Estimation through Machine-learning techniques to support real-world R&D experiments

The emissions estimation, both during homologation and standard driving, is one of the new challenges that automotive industries have to face. The new European and American regulation will allow a lower and lower quantity of Carbon Monoxide emission and will require that all the vehicles have to be able to monitor their own pollutants production. Since numerical models are too computationally expensive and approximated, new solutions based on Machine Learning are replacing standard techniques. In this project we considered a real V12 Internal Combustion Engine to propose a novel approach pushing Random Forests to generate meaningful prediction also in extreme cases (extrapolation, very high frequency peaks, noisy instrumentation etc.). The present work proposes also a data preprocessing pipeline for strongly unbalanced datasets and a reinterpretation of the regression problem as a classification problem in a logarithmic quantized domain. Results have been evaluated for two different models representing a pure interpolation scenario (more standard) and an extrapolation scenario, to test the out of bounds robustness of the model. The employed metrics take into account different aspects which can affect the homologation procedure, so the final analysis will focus on combining all the specific performances together to obtain the overall conclusions.