Developing Hybrid Metal-Halide Layered perovskites and Derivatives for Optoelectronics

Veleia tra epigrafia, storia, archeologia e topografia: aggiornamenti per un centro dell’Aemilia

Epigraphic, historical and topographical update concerning the Roman city of Veleia and its countryside.

Antonio Begarelli: contesto, formazione e riflessioni sul catalogo.

This research arises from the need for a critical reassessment of the first twenty years of activity of the Modenese sculptor Antonio Begarelli, with a particular focus on the phases of his training and the development of his classicist style, which has often been attributed to an early journey to Rome. The study begins by reconstructing the artistic landscape of early 16th-century Modena, aiming to glean as much information as possible about the environment encountered by a young, aspiring s...

The Beam-Dump eXperiment

Hadronic matter makes about 14% of the known universe. The remaining 86% is Dark Matter (DM). Since it does not interact with the ordinary matter via electromagnetic force, DM is not visible and, to date, it escaped detection. The search for DM is one of the hottest topic in modern physics. Despite the increasing number of astrophysical and cosmological observations proving the existence, so far no particle physics experiment has detected DM yet. In a popular class of models, DM is composed ...

An innovative approach to performance metrics calculus in cloud computing environments: a guest-to-host oriented perspective

In virtualized systems, the task of profiling and resource monitoring is not straight-forward. Many datacenters perform CPU overcommittment using hypervisors, running multiple virtual machines on a single computer where the total number of virtual CPUs exceeds the total number of physical CPUs available. From a customer point of view, it could be indeed interesting to know if the purchased service levels are effectively respected by the cloud provider. The innovative approach to performance ...

Computational and Theoretical Issues of Multiparameter Persistent Homology for Data Analysis

The basic goal of topological data analysis is to apply topology-based descriptors to understand and describe the shape of data. In this context, homology is one of the most relevant topological descriptors, well-appreciated for its discrete nature, computability and dimension independence. A further development is provided by persistent homology, which allows to track homological features along a oneparameter increasing sequence of spaces. Multiparameter persistent homology, also calle...

The paroxysmal disorder gene PRRT2 downregulates NaV channels and neuronal excitability in human neurons

Proline-Rich Transmembrane Protein 2 (PRRT2) has been identified as the single causative gene for a group of paroxysmal syndromes, including benign familial infantile seizures, paroxysmal kinesigenic dyskinesia and migraine. Most of the mutations of this gene lead to a premature stop codon, generating an unstable form of mRNA or a truncated protein that is degraded, pointing out the loss of the PRRT2 function as pathogenic mechanism of action. In this thesis, we have used different approaches...

Investigation of inorganic nanocrystals as electrode material for lithium and sodium ion batteries

The worldwide demand for a clean, safe, high specific capacity and high energy rechargeable batteries systems keeps increasing. Li-ion batteries (LIBs) and Na-ion batteries (NIBs) have been proved to be reliable technologies, for a large variety of applications, ranging from portable high-end electronics, stationary.

Design and HPC implementation of unsupervised Kernel methods in the context of molecular dynamics

The thesis represents an extensive research in the multidisciplinary domain formed by the cross contamination of unsupervised learning and molecular dynamics, two research elds that are coming close creating a breeding ground for valuable new concepts and methods. In this context, at rst, we describe a novel engine to perform large scale kernel k-means clustering. We introduce a two-fold approximation strategy to minimize the kernel k-means cost function in which the trade-off between accurac...