Impact of ocean acidification on phytoplankton growth and aggregation

Since the industrial revolution, the ocean has absorbed around one third of the anthropogenic CO2, which induced a profound alteration of the carbonate system commonly known as ocean acidification. Since the preindustrial times, the average ocean surface water pH has fallen by 0.1 units, from approximately 8.2 to 8.1 and a further decrease of 0.4 pH units is expected for the end of the century. Despite their microscopic size, marine diatoms are bio-geo-chemically a very important group, responsible for the export of massive amount of carbon to deep waters and sediments. The knowledge of the potential effects of ocean acidification on the phytoplankton growth and on biological pump is still at its infancy. This study wants to investigate the effect of ocean acidification on the growth of the diatom Skeletonema marinoi and on its aggregation, using a mechanistic approach. The experiment consisted of two treatments (Present and Future) representing different pCO2 conditions and two sequential experimental phases. During the cell growth phase a culture of S. marinoi was inoculated into transparent bags and the effect of ocean acidification was studied on various growth parameters, including DOC and TEP production. The aggregation phase consisted in the incubation of the cultures into rolling tanks where the sinking of particles through the water column was simulated and aggregation promoted. Since few studies investigated the effect of pH on the growth of S. marinoi and none used pH ranges that are compatible with the OA scenarios, there were no baselines. I have shown here, that OA does not affect the cell growth of S. marinoi, suggesting that the physiology of this species is robust in respect to the changes in the carbonate chemistry expected for the end of the century. Furthermore, according to my results, OA does not affect the aggregation of S. marinoi in a consistent manner, suggesting that this process has a high natural variability but is not influenced by OA in a predictable way. The effect of OA was tested over a variety of factors including the number of aggregates produced, their size and sinking velocity, the algal, bacterial and TEP content. Many of these variables showed significant treatment effects but none of these were consistent between the two experiments.

Data sanitization in a clearing system for public transport operators

In this work we will discuss about a project started by the Emilia-Romagna Regional Government regarding the manage of the public transport. In particular we will perform a data mining analysis on the data-set of this project. After introducing the Weka software used to make our analysis, we will discover the most useful data mining techniques and algorithms; and we will show how these results can be used to violate the privacy of the same public transport operators. At the end, despite is off topic of this work, we will spend also a few words about how it's possible to prevent this kind of attack.

Evaluation of confidence-driven cost aggregation strategies

In this thesis I describe eight new stereo matching algorithms that perform the cost-aggregation step using a guided filter with a confidence map as guidance image, and share the structure of a linear stereo matching algorithm. The results of the execution of the proposed algorithms on four pictures from the Middlebury dataset are shown as well. Finally, based on these results, a ranking of the proposed algorithms is presented.

Mathematical models for cellular aggregation: the chemotactic instability and clustering formation

In this thesis we present a mathematical formulation of the interaction between microorganisms such as bacteria or amoebae and chemicals, often produced by the organisms themselves. This interaction is called chemotaxis and leads to cellular aggregation. We derive some models to describe chemotaxis. The first is the pioneristic Keller-Segel parabolic-parabolic model and it is derived by two different frameworks: a macroscopic perspective and a microscopic perspective, in which we start with a stochastic differential equation and we perform a mean-field approximation. This parabolic model may be generalized by the introduction of a degenerate diffusion parameter, which depends on the density itself via a power law. Then we derive a model for chemotaxis based on Cattaneo's law of heat propagation with finite speed, which is a hyperbolic model. The last model proposed here is a hydrodynamic model, which takes into account the inertia of the system by a friction force. In the limit of strong friction, the model reduces to the parabolic model, whereas in the limit of weak friction, we recover a hyperbolic model. Finally, we analyze the instability condition, which is the condition that leads to aggregation, and we describe the different kinds of aggregates we may obtain: the parabolic models lead to clusters or peaks whereas the hyperbolic models lead to the formation of network patterns or filaments. Moreover, we discuss the analogy between bacterial colonies and self gravitating systems by comparing the chemotactic collapse and the gravitational collapse (Jeans instability).

Simulating the aggregation of DNA oligonucleotides

In this work we have studied, by means of Molecular Dynamics simulations, the process of denaturation and self-assembly of short oligonucleotides. Supramolecular ordering of DNA short strands is a promising field which is constantly enriched with new findings. Examples are provided by micellar and fibrils formations and due to the selectivity of DNA bindings, "intelligent" devices have been developed to perform simple logic operations. It is worth to notice that computer simulations of these DNA nanosystems would complement experiments with detailed insight into processes involved in self-assembly. In order to obtain an accurate description of the interactions involved in the complex structure of DNA we used oxDNA, a coarse-grained model developed by Ouldridge. We simulated the melting transition of 4, 6, and 8 base pair sequences. Sequence and length dependence were analyzed, specifically we compared thermodynamic parameters DeltaH, DeltaS and the melting temperature with literature results. Moreover, we have attempted to reproduce liquid crystal ordering of the ultrashort sequence GCCG at relatively high saline concentration, until now only experimentally observed in Bellini's works. We found that our simple model successfully reproduces the experimental phase sequence (isotropic, nematic, columnar) at T= 5 °C as a function of oligonucleotide concentration, and we fully characterized the microscopic structure of the three phases.

Lipschitz regularity for weak solutions of parabolic p-Laplacian type equations in certain subriemannian structures

The main aim of the thesis is to prove the local Lipschitz regularity of the weak solutions to a class of parabolic PDEs modeled on the parabolic p-Laplacian. This result is well known in the Euclidean case and recently has been extended in the Heisenberg group, while higher regularity results are not known in subriemannian parabolic setting. In this thesis we will consider vector fields more general than those in the Heisenberg setting, introducing some technical difficulties. To obtain our main result we will use a Moser-like iteration. Due to the non linearity of the equation, we replace the usual parabolic cylinders with new ones, whose dimension also depends on the L^p norm of the solution. In addition, we deeply simplify the iterative procedure, using the standard Sobolev inequality, instead of the parabolic one.