Hydrogeochemical monitoring and modelling of saltwater intrusion in lowlands (Ferrara, IT)

Because of the potentially irreversible impact of groundwater quality deterioration in the Ferrara coastal aquifer, answers concerning the assessment of the extent of the salinization problem, the understanding of the mechanisms governing salinization processes, and the sustainability of the current water resources management are urgent. In this light, the present thesis aims to achieve the following objectives: Characterization of the lowland coastal aquifer of Ferrara: hydrology, hydrochemistry and evolution of the system The importance of data acquisition techniques in saltwater intrusion monitoring Predicting salinization trends in the lowland coastal aquifer Ammonium occurrence in a salinized lowland coastal aquifer Trace elements mobility in a saline coastal aquifer

Stream sediments analysis for geochemical mapping of Romagna Apennines (Northern Italy): monitoring and management tool of environmental resources at various scales

Geochemical mapping is a valuable tool for the control of territory that can be used not only in the identification of mineral resources and geological, agricultural and forestry studies but also in the monitoring of natural resources by giving solutions to environmental and economic problems. Stream sediments are widely used in the sampling campaigns carried out by the world's governments and research groups for their characteristics of broad representativeness of rocks and soils, for ease of sampling and for the possibility to conduct very detailed sampling In this context, the environmental role of stream sediments provides a good basis for the implementation of environmental management measures, in fact the composition of river sediments is an important factor in understanding the complex dynamics that develop within catchment basins therefore they represent a critical environmental compartment: they can persistently incorporate pollutants after a process of contamination and release into the biosphere if the environmental conditions change. It is essential to determine whether the concentrations of certain elements, in particular heavy metals, can be the result of natural erosion of rocks containing high concentrations of specific elements or are generated as residues of human activities related to a certain study area. This PhD thesis aims to extract from an extensive database on stream sediments of the Romagna rivers the widest spectrum of informations. The study involved low and high order stream in the mountain and hilly area, but also the sediments of the floodplain area, where intensive agriculture is active. The geochemical signals recorded by the stream sediments will be interpreted in order to reconstruct the natural variability related to bedrock and soil contribution, the effects of the river dynamics, the anomalous sites, and with the calculation of background values be able to evaluate their level of degradation and predict the environmental risk.

Monitoring and Prediction of Thermal Emergencies in High Performance Computing Systems

Modern scientific discoveries are driven by an unsatisfiable demand for computational resources. High-Performance Computing (HPC) systems are an aggregation of computing power to deliver considerably higher performance than one typical desktop computer can provide, to solve large problems in science, engineering, or business. An HPC room in the datacenter is a complex controlled environment that hosts thousands of computing nodes that consume electrical power in the range of megawatts, which gets completely transformed into heat. Although a datacenter contains sophisticated cooling systems, our studies indicate quantitative evidence of thermal bottlenecks in real-life production workload, showing the presence of significant spatial and temporal thermal and power heterogeneity. Therefore minor thermal issues/anomalies can potentially start a chain of events that leads to an unbalance between the amount of heat generated by the computing nodes and the heat removed by the cooling system originating thermal hazards. Although thermal anomalies are rare events, anomaly detection/prediction in time is vital to avoid IT and facility equipment damage and outage of the datacenter, with severe societal and business losses. For this reason, automated approaches to detect thermal anomalies in datacenters have considerable potential. This thesis analyzed and characterized the power and thermal characteristics of a Tier0 datacenter (CINECA) during production and under abnormal thermal conditions. Then, a Deep Learning (DL)-powered thermal hazard prediction framework is proposed. The proposed models are validated against real thermal hazard events reported for the studied HPC cluster while in production. This thesis is the first empirical study of thermal anomaly detection and prediction techniques of a real large-scale HPC system to the best of my knowledge. For this thesis, I used a large-scale dataset, monitoring data of tens of thousands of sensors for around 24 months with a data collection rate of around 20 seconds.

Neonatal outcomes following maternal SARS-CoV-2 infection in pregnancy - longitudinal follow-up and assessment of transplacental antibody transfer

BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in pregnancy has been associated with multiple adverse pregnancy outcomes, including the risk of in utero mother-to-child transmission. Short- and long-term outcomes of SARS-CoV-2 exposed neonates and the extent to which maternal SARS-CoV-2 antibodies are transferred to neonates are still unclear. METHODS: Prospective observational study enrolling neonates born to mothers with SARS-CoV-2 infection in pregnancy, between April 2020-April 2021. Neonates were evaluated at birth and enrolled in a 12-month follow-up. SARS-CoV-2 IgG transplacental transfer ratio was assessed in mother-neonate dyads at birth. Maternal derived IgG were followed in infants until negativizing. RESULTS: Of 2745 neonates, 106 (3.9%) were delivered by mothers with SARS-CoV-2 infection in pregnancy. Seventy-six of 106 (71.7%) mothers were symptomatic. Median gestational age and mean birth weight were 39 weeks (range 25+5-41+4) and 3305 grams (SD 468). Six of 106 (6%) neonates were born preterm, without significant differences between asymptomatic and symptomatic mothers (P=0.67). No confirmed cases of in utero infection were detected. All infants had normal cerebral ultrasound and clinical evaluation at birth and during follow-up, until a median age of 7 months (range 5-12). All mothers and 96/106 (90.5%) neonates had detectable SARS-CoV-2 IgG at birth. Transplacental transfer ratio was higher following second trimester maternal infections (mean 0.940.46 versus 1.070.64 versus 0.750.44, P=0.039), but was not significantly different between asymptomatic and symptomatic women (P=0.20). IgG level in infants progressively decreased after birth: at 3 months 53% (51/96) and at four months 68% (63/96) had lost maternal antibodies respectively. The durability of maternal antibodies was positively correlated to the IgG level at birth (r=0.66; P<0.00001). CONCLUSIONS: Maternal SARS-CoV-2 infection was not associated with increased neonatal or long-term morbidity. No cases of confirmed in utero infection were detected. Efficient transplacental IgG transfer was found following second trimester maternal infections.

Collective actions for environmental monitoring and conservation: citizen science, informal environmental education, and participatory approach

This PhD was driven by an interest for inclusive and participatory approaches. The methodology that bridges science and society is known as 'citizen science' and is experiencing a huge upsurge worldwide, in the scientific and humanities fields. In this thesis, I have focused on three topics: i) assessing the reliability of data collected by volunteers; ii) evaluating the impact of environmental education activities in tourist facilities; and iii) monitoring marine biodiversity through citizen science. In addition to these topics, during my research stay abroad, I developed a questionnaire to investigate people's perceptions of natural areas to promote the implementation of co-management. The results showed that volunteers are not only able to collect sufficiently reliable data, but that during their participation in this type of project, they can also increase their knowledge of marine biology and ecology and their awareness of the impact of human behaviour on the environment. The short-term analysis has shown that volunteers are able to retain what they have learned. In the long term, knowledge is usually forgotten, but awareness is retained. Increased awareness could lead to a change in behaviour and in this case a more environmentally friendly attitude. This aspect could be of interest for the development of environmental education projects in tourism facilities to reduce the impact of tourism on the environment while adding a valuable service to the tourism offer. We also found that nature experiences in childhood are important to connect to nature in adulthood. The results also suggest that membership or volunteering in an environmental education association could be a predictor of people's interest in more participatory approaches to nature management. In most cases, the COVID -19 pandemic had not changed participants' perceptions of the natural environment.

Metrological characterization of sensors and instrumentation for distribution grid monitoring and electrical asset diagnostics

The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.

Planning and assessment techniques for spine surgeries

The rate of diagnosis and treatment of degenerative spine disorders is increasing, increasing the need for surgical intervention. Posterior spine fusion is one surgical intervention used to treat various spine degeneration pathologies To minimize the risk of complications and provide patients with positive outcomes, preoperative planning and postsurgical assessment are necessary. This PhD aimed to investigate techniques for the surgical planning and assessment of spine surgeries. Three main techniques were assessed: stereophotogrammetric motion analysis, 3D printing of complex spine deformities and finite element analysis of the thoracolumbar spine. Upon reviewing the literature on currently available spine kinematics protocol, a comprehensive motion analysis protocol to measure the multi-segmental spine motion was developed. Using this protocol, the patterns of spine motion in patients before and after posterior spine fixation was mapped. The second part investigated the use of virtual and 3D printed spine models for the surgical planning of complex spine deformity correction. Compared to usual radiographic images, the printed model allowed optimal surgical intervention, reduced surgical time and provided better surgeon-patient communication. The third part assessed the use of polyetheretherketone rods auxiliary to titanium rods to reduce the stiffness of posterior spine fusion constructs. Using a finite element model of the thoracolumbar spine, the rods system showed a decrease in the overall stress of the uppermost instrumented vertebra when compared to regular fixation approaches. Finally, a retrospective biomechanical assessment of a lumbopelvic reconstruction technique was investigated to assess the patients' gait following the surgery, the implant deformation over the years and the extent of bony fusion between spine and implant. In conclusion, this thesis highlighted the need to provide surgeons with new planning and assessment techniques to better understand postsurgical complications. The methodologies investigated in this project can be used in the future to establish a patient-specific planning protocol.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.

Mechanical behaviour and durability assessment of Fibre Reinforced Cementitious Matrix (FRCM) strengthening systems.

In recent years, the seismic vulnerability of existing masonry buildings has been underscored by the destructive impacts of earthquakes. Therefore, Fibre Reinforced Cementitious Matrix (FRCM) retrofitting systems have gained prominence due to their high strength-to-weight ratio, compatibility with substrates, and potential reversibility. However, concerns linger regarding the durability of these systems when subjected to long-term environmental conditions. This doctoral dissertation addressed these concerns by studying the effects of mild temperature variations on three FRCM systems, featuring basalt, glass, and aramid fibre textiles with lime-based mortar matrices. The study subjected various specimens, including mortar triplets, bare textile specimens, FRCM coupons, and single-lap direct shear wallets, to thermal exposure. A novel approach utilizing embedded thermocouple sensors facilitated efficient monitoring and active control of the conditioning process. A shift in the failure modes was obtained in the single lap-direct shear tests, alongside a significant impact on tensile capacity for both textiles and FRCM coupons. Subsequently, bond tests results were used to indirectly calibrate an analytical approach based on mode-II fracture mechanics. A comparison between Cohesive Material Law (CML) functions at various temperatures was conducted for each of the three systems, demonstrating a good agreement between the analytical model and experimental curves. Furthermore, the durability in alkaline environment of two additional FRCM systems, characterized by basalt and glass fibre textiles with lime-based mortars, was studied through an extensive experimental campaign. Tests conducted on single yarn and textile specimens after exposure at different durations and temperatures revealed a significant impact on tensile capacity. Additionally, FRCM coupons manufactured with conditioned textile were tested to understand the influence of aged textile and curing environment on the final tensile behavior. These results contributed significantly to the existing knowledge on FRCM systems and could be used to develop a standardized alkaline testing protocol, still lacking in the scientific literature.