Evaluation of green algae deployment for organic pollutant removal in urban wastewater through ERE-CALUX potency assessment

The interest of the scientific community towards organic pollutants in freshwater streams is fairly recent. During the past 50 years, thousands of chemicals have been synthesized and released into the general environment. Nowadays their occurrence and effects on several organism, invertebrates, fish, birds, reptiles and also humans are well documented. Because of their action, some of these chemicals have been defined as Endocrine Disrupters Compounds (EDCs) and the public health implications of these EDCs have been the subject of scientific debate. Most interestingly, among those that were noticed to have some influence and effects on the endocrine system were the estrone, the 17β-estradiol, the 17α-estradiol, the estriol, the 17α-ethinylestradiol, the testosterone and the progesterone. This project focused its attention on the 17β-estradiol. Estradiol, or more precisely, 17β-estradiol (also commonly referred to as E2) is a human sex hormone. It belongs to the class of steroid hormones. In spite of the effort to remove these substances from the effluents, the actual wastewater treatment plants are not able to degrade or inactivate these organic compounds that are continually poured in the ecosystem. Through this work a new system for the wastewater treatment was tested, to assess the decrease of the estradiol in the water. It involved the action of Chlorella vulgaris, a fresh water green microalga belonging to the family of the Chlorellaceae. This microorganism was selected for its adaptability and for its photosynthetic efficiency. To detect the decrease of the target compound in the water a CALUX bioassay analysis was chosen. Three different experiments were carried on to pursue the aim of the project. By analysing their results several aspects emerged. It was assessed the presence of EDCs inside the water used to prepare the culture media. C. vulgaris, under controlled conditions, could be efficient for this purpose, although further researches are essential to deepen the knowledge of this complex phenomenon. Ultimately by assessing the toxicity of the effluent against C. vulgaris, it was clear that at determined concentrations, it could affect the normal growth rate of this microorganism.

Deployment automatico di applicazioni specificate in linguaggio ABS

Da quando è iniziata l'era del Cloud Computing molte cose sono cambiate, ora è possibile ottenere un server in tempo reale e usare strumenti automatizzati per installarvi applicazioni. In questa tesi verrà descritto lo strumento MODDE (Model-Driven Deployment Engine), usato per il deployment automatico, partendo dal linguaggio ABS. ABS è un linguaggio a oggetti che permette di descrivere le classi in una maniera astratta. Ogni componente dichiarato in questo linguaggio ha dei valori e delle dipendenze. Poi si procede alla descrizione del linguaggio di specifica DDLang, col quale vengono espressi tutti i vincoli e le configurazioni finali. In seguito viene spiegata l’architettura di MODDE. Esso usa degli script che integrano i tool Zephyrus e Metis e crea un main ABS dai tre file passati in input, che serve per effettuare l’allocazione delle macchine in un Cloud. Inoltre verranno introdotti i due sotto-strumenti usati da MODDE: Zephyrus e Metis. Il primo si occupa di scegliere quali servizi installare tenendo conto di tutte le loro dipendenze, cercando di ottimizzare il risultato. Il secondo gestisce l’ordine con cui installarli tenendo conto dei loro stati interni e delle dipendenze. Con la collaborazione di questi componenti si ottiene una installazione automatica piuttosto efficace. Infine dopo aver spiegato il funzionamento di MODDE viene spiegato come integrarlo in un servizio web per renderlo disponibile agli utenti. Esso viene installato su un server HTTP Apache all’interno di un container di Docker.

Deployment of a data analysis workflow of the ATLAS experiment on HPC systems

LHC experiments produce an enormous amount of data, estimated of the order of a few PetaBytes per year. Data management takes place using the Worldwide LHC Computing Grid (WLCG) grid infrastructure, both for storage and processing operations. However, in recent years, many more resources are available on High Performance Computing (HPC) farms, which generally have many computing nodes with a high number of processors. Large collaborations are working to use these resources in the most efficient way, compatibly with the constraints imposed by computing models (data distributed on the Grid, authentication, software dependencies, etc.). The aim of this thesis project is to develop a software framework that allows users to process a typical data analysis workflow of the ATLAS experiment on HPC systems. The developed analysis framework shall be deployed on the computing resources of the Open Physics Hub project and on the CINECA Marconi100 cluster, in view of the switch-on of the Leonardo supercomputer, foreseen in 2023.

Deployment and Orchestration in Cloud Native 5G Networks With Kubernetes

Software Defined Networking along with Network Function Virtualisation have brought an evolution in the telecommunications laying out the bases for 5G networks and its softwarisation. The separation between the data plane and the control plane, along with having a decentralisation of the latter, have allowed to have a better scalability and reliability while reducing the latency. A lot of effort has been put into creating a distributed controller, but most of the solutions provided by now have a monolithic approach that reduces the benefits of having a software defined network. Disaggregating the controller and handling it as microservices is the solution to problems faced when working with a monolithic approach. Microservices enable the cloud native approach which is essential to benefit from the architecture of the 5G Core defined by the 3GPP standards development organisation. Applying the concept of NFV allows to have a softwarised version of the entire network structure. The expectation is that the 5G Core will be deployed on an orchestrated cloud infrastructure and in this thesis work we aim to provide an application of this concept by using Kubernetes as an implementation of the MANO standard. This means Kubernetes acts as a Network Function Virtualisation Orchestrator (NFVO), Virtualised Network Function Manager (VNFM) and Virtualised Infrastructure Manager (VIM) rather than just a Network Function Virtualisation Infrastructure. While OSM has been adopted for this purpose in various scenarios, this work proposes Kubernetes opposed to OSM as the MANO standard implementation.