Effects of Resources Exploitation on Water Quality: case studies in Salt Water Intrusion and Acid Mine Drainage

Throughout the world, pressures on water resources are increasing, mainly as a result of human activity. Because of their accessibility, groundwater and surface water are the most used reservoirs. The evaluation of the water quality requires the identification of the interconnections among the water reservoirs, natural landscape features, human activities and aquatic health. This study focuses on the estimation of the water pollution linked to two different environmental issues: salt water intrusion and acid mine drainage related to the exploitation of natural resources. Effects of salt water intrusion occurring in the shallow aquifer north of Ravenna (Italy) was analysed through the study of ion- exchange occurring in the area and its variance throughout the year, applying a depth-specific sampling method. In the study area were identified ion exchange, calcite and dolomite precipitation, and gypsum dissolution and sulphate reduction as the main processes controlling the groundwater composition. High concentrations of arsenic detected only at specific depth indicate its connexion with the organic matter. Acid mine drainage effects related to the tin extraction in the Bolivian Altiplano was studied, on water and sediment matrix. Water contamination results strictly dependent on the seasonal variation, on pH and redox conditions. During the dry season the strong evaporation and scarce water flow lead to low pH values, high concentrations of heavy metals in surface waters and precipitation of secondary minerals along the river, which could be released in oxidizing conditions as demonstrated through the sequential extraction analysis. The increase of the water flow during the wet season lead to an increase of pH values and a decrease in heavy metal concentrations, due to dilution effect and, as e.g. for the iron, to precipitation.

An interdisciplinary analysis of obesity: theory and empirical evidence

The dissertation is structured in three parts. The first part compares US and EU agricultural policies since the end of WWII. There is not enough evidence for claiming that agricultural support has a negative impact on obesity trends. I discuss the possibility of an exchange in best practices to fight obesity. There are relevant economic, societal and legal differences between the US and the EU. However, partnerships against obesity are welcomed. The second part presents a socio-ecological model of the determinants of obesity. I employ an interdisciplinary model because it captures the simultaneous influence of several variables. Obesity is an interaction of pre-birth, primary and secondary socialization factors. To test the significance of each factor, I use data from the National Longitudinal Survey of Adolescent Health. I compare the average body mass index across different populations. Differences in means are statistically significant. In the last part I use the National Survey of Children Health. I analyze the effect that family characteristics, built environment, cultural norms and individual factors have on the body mass index (BMI). I use Ordered Probit models and I calculate the marginal effects. I use State and ethnicity fixed effects to control for unobserved heterogeneity. I find that southern US States tend have on average a higher probability of being obese. On the ethnicity side, White Americans have a lower BMI respect to Black Americans, Hispanics and American Indians Native Islanders; being Asian is associated with a lower probability of being obese. In neighborhoods where trust level and safety perception are higher, children are less overweight and obese. Similar results are shown for higher level of parental income and education. Breastfeeding has a negative impact. Higher values of measures of behavioral disorders have a positive and significant impact on obesity, as predicted by the theory.

On the renormalization flow representation of field theory and some applications

In this thesis we discuss a representation of quantum mechanics and quantum and statistical field theory based on a functional renormalization flow equation for the one-particle-irreducible average effective action, and we employ it to get information on some specific systems.

Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.