Greening the city: an ecosystem-based framework to support planning towards urban sustainability and resilience

Cities are small-scale complex socio-ecological systems, that host around 60% of world population. Ecosystem Services (ES) provided by urban ecosystems offer multiple benefits necessary to cope with present and future urban challenges. These ES include microclimate regulation, runoff control, as well as opportunities for mental and physical recreation, affecting citizen’s health and wellbeing. Creating a balance between urban development, land take containment, climate adaptation and availability of Urban Green Areas and their related benefits, can improve the quality of the lives of the inhabitants, the economic performance of the city and the social justice and cohesion aspects. This work starts analysing current literature around the topic of Ecosystem Services (ES), Green and Blue Infrastructure (GBI) and Nature-based Solutions (NBS) and their integration within current European and International sustainability policies. Then, the thesis focuses on the role of ES, GBI and NBS towards urban sustainability and resilience setting the basis to build the core methodological and conceptual approach of this work. The developed ES-based conceptual approach provides guidance on how to map and assess ES, to better inform policy making and to give the proper value to ES within urban context. The proposed interdisciplinary approach navigates the topic of mapping and assessing ES benefits in terms of regulatory services, with a focus on climate mitigation and adaptation, and cultural services, to enhance wellbeing and justice in urban areas. Last, this thesis proposes a trans-disciplinary and participatory approach to build resilience over time around all relevant urban ES. The two case studies that will be presented in this dissertation, the city of Bologna and the city of Barcelona, have been used to implement, tailor and test the proposed conceptual framework, raising valuable inputs for planning, policies and science.

Creazione e sviluppo di un sistema di controllo in tempo reale per un sistema fuel cell

The control of a proton exchange membrane fuel cell system (PEM FC) for domestic heat and power supply requires extensive control measures to handle the complicated process. Highly dynamic and non linear behavior, increase drastically the difficulties to find the optimal design and control strategies. The objective is to design, implement and commission a controller for the entire fuel cell system. The fuel cell process and the control system are engineered simultaneously; therefore there is no access to the process hardware during the control system development. Therefore the method of choice was a model based design approach, following the rapid control prototyping (RCP) methodology. The fuel cell system is simulated using a fuel cell library which allowed thermodynamic calculations. In the course of the development the process model is continuously adapted to the real system. The controller application is designed and developed in parallel and thereby tested and verified against the process model. Furthermore, after the commissioning of the real system, the process model can be also better identified and parameterized utilizing measurement data to perform optimization procedures. The process model and the controller application are implemented in Simulink using Mathworks` Real Time Workshop (RTW) and the xPC development suite for MiL (model-in-theloop) and HiL (hardware-in-the-loop) testing. It is possible to completely develop, verify and validate the controller application without depending on the real fuel cell system, which is not available for testing during the development process. The fuel cell system can be immediately taken into operation after connecting the controller to the process.

Model reduction techniques in flexible multibody dynamics with application to engine cranktrain simulation

The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.

Valutazione della risposta sismica di edifici mediante modelli anelastici equivalenti

Nella presente tesi è proposta una metodologia per lo studio e la valutazione del comportamento sismico di edifici a telaio. Il metodo prevede la realizzazione di analisi non-lineari su modelli equivalenti MDOF tipo stick, in accordo alla classificazione data nel report FEMA 440. Gli step per l’applicazione del metodo sono descritti nella tesi. Per la validazione della metodologia si sono utilizzati confronti con analisi time-history condotte su modelli tridimensionali dettagliati delle strutture studiate (detailed model). I parametri ingegneristici considerati nel confronto, nell’ottica di utilizzare il metodo proposto in un approccio del tipo Displacement-Based Design sono lo spostamento globale in sommità, gli spostamenti di interpiano, le forze di piano e la forza totale alla base. I risultati delle analisi condotte sui modelli stick equivalenti, mostrano una buona corrispondenza, ottima in certi casi, con quelli delle analisi condotte sui modelli tridimensionali dettagliati. Le time-history realizzate sugli stick model permettono però, un consistente risparmio in termini di onere computazionale e di tempo per il post-processing dei risultati ottenuti.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

La consulenza in materia di investimenti

Il lavoro propone un’analisi critica delle disciplina italiana ed europea della consulenza in materia di investimenti. Si considerano innanzitutto le problematiche generali del rapporto tra cliente e intermediario nella prestazione della consulenza, con particolare riferimento ad asimmetrie informative e conflitti di interesse. Si discute, in particolare, il tradizionale paradigma regolamentare fondato sulla trasparenza: le indicazioni della finanza comportamentale suggeriscono, infatti, un intervento normativo più deciso, volto a caratterizzare in maniera fiduciaria la relazione tra cliente e intermediario. Dopo aver analizzato, alla stregua dei modelli teorici illustrati in precedenza, l’evoluzione storica della disciplina della consulenza nell’ordinamento italiano, si sottolinea il ruolo svolto dall’autorità di vigilanza nella sistematizzazione dell’istituto, nel contempo rilevando, tuttavia, la complessiva insufficienza delle norme vigenti al fine di un’adeguata tutela dell’investitore. Si esamina poi la disciplina introdotta dalla MiFID, con specifica attenzione alle implicazioni sistematiche dell’estensione della nozione di consulenza operata dalle autorità di vigilanza: la nuova configurazione del servizio ha determinato un’intensificazione dei doveri fiduciari imposti agli intermediari, testimoniando un superamento del paradigma di trasparenza e un percorso indirizzato verso un approccio maggiormente interventista sul lato dell’offerta. Le conclusioni sono, peraltro, nel senso di uno sviluppo solo parziale di tale processo, risultando dubbio il valore per il cliente di una consulenza non indipendente e potenzialmente esposta, soprattutto negli intermediari polifunzionali, al conflitto di interessi. Particolare enfasi viene posta sulla necessità di introdurre un’effettiva consulenza indipendente, pur nelle difficoltà che la relativa disciplina incontra, anche in ragione delle caratteristiche specifiche del mercato, nell’ordinamento italiano.

Agroecological management of insect pests on sugarbeets and lettuce cultivated in organic farming

Two-year field trials were conducted in northern Italy with the aim of developing a trapcrop-based agroecological approach for the control of flea beetles (Chaetocnema tibialis (Illiger), Phyllotreta spp. (Chevrolat) (Coleoptera: Chrysomelidae)) and Lygus rugulipennis Poppius (Hemiptera: Miridae), key pests of sugar beet and lettuce, respectively. Flea beetle damage trials compared a trap cropping treatment, i.e., a sugar beet plot with a border of Sinapis alba (L.) and Brassica juncea (L.) with a control treatment, i.e., a sugar beet plot with bare soil as field border. Sugar beets grown near trap crops showed a significant decrease (≈40%) in flea beetle damage compared to control. Moreover, flea beetle damage varied with distance from the edge of the trap plants, being highest at 2 m from the edge, then decreasing at higher distances. Regarding L. rugulipennis on lettuce two experiments were conducted. A semiochemical-assisted trap cropping trial was supported by another test evaluating the efficacy of pheromones and trap placement. In this trial, it was found that pheromone baited traps caught significantly more specimens of L. rugulipennis than unbaited traps. It was also found that traps placed at ground level produced larger catches than traps placed at the height of 70 cm. In the semiochemical-assisted trap cropping experiment, a treatment where lettuce was grown next to two Alfa-Alfa borders containing pheromone baited traps was compared with a control treatment, where lettuce was grown near bare soil. This experiment showed that the above-mentioned strategy managed to reduce L. rugulipennis damage to lettuce by ≈30%. From these studies, it appears that trap crop-based strategy, alone or with baited traps, made it possible to reduce crop damage to economically acceptable levels and to minimize the need for insecticide treatments, showing that those strategy could be implemented in organic farming as a means of controlling insect pests.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Analysis of earthquakes predictability

Earthquake prediction is a complex task for scientists due to the rare occurrence of high-intensity earthquakes and their inaccessible depths. Despite this challenge, it is a priority to protect infrastructure, and populations living in areas of high seismic risk. Reliable forecasting requires comprehensive knowledge of seismic phenomena. In this thesis, the development, application, and comparison of both deterministic and probabilistic forecasting methods is shown. Regarding the deterministic approach, the implementation of an alarm-based method using the occurrence of strong (fore)shocks, widely felt by the population, as a precursor signal is described. This model is then applied for retrospective prediction of Italian earthquakes of magnitude M≥5.0,5.5,6.0, occurred in Italy from 1960 to 2020. Retrospective performance testing is carried out using tests and statistics specific to deterministic alarm-based models. Regarding probabilistic models, this thesis focuses mainly on the EEPAS and ETAS models. Although the EEPAS model has been previously applied and tested in some regions of the world, it has never been used for forecasting Italian earthquakes. In the thesis, the EEPAS model is used to retrospectively forecast Italian shallow earthquakes with a magnitude of M≥5.0 using new MATLAB software. The forecasting performance of the probabilistic models was compared to other models using CSEP binary tests. The EEPAS and ETAS models showed different characteristics for forecasting Italian earthquakes, with EEPAS performing better in the long-term and ETAS performing better in the short-term. The FORE model based on strong precursor quakes is compared to EEPAS and ETAS using an alarm-based deterministic approach. All models perform better than a random forecasting model, with ETAS and FORE models showing better performance. However, to fully evaluate forecasting performance, prospective tests should be conducted. The lack of objective tests for evaluating deterministic models and comparing them with probabilistic ones was a challenge faced during the study.

Synthesis and characterization of novel selective NKCC1 inhibitors for the treatment of down syndrome and brain disorders characterized by depolarizing GABAergic transmission.

Proper GABAergic transmission through Cl-permeable GABAA receptors is fundamental for physiological brain development and function. Indeed, defective GABAergic signaling – due to a high NKCC1/KCC2 expression ratio – has been implicated in several neurodevelopmental disorders (e.g., Down syndrome, DS, Autism spectrum disorders, ASD). Interestingly, NKCC1 inhibition by the FDA-approved diuretic drug bumetanide reverts cognitive deficits in the TS65Dn mouse models of DS and core symptoms in other models of brain disorders. However, the required chronic treatment with bumetanide is burdened by its diuretic side effects caused by the antagonization of the kidney Cl importer NKCC2. This may lead to hypokalemia, while jeopardizing drug compliance. Crucially, these issues would be solved by selective NKCC1 inhibitors, thus devoid of the diuretic effect of bumetanide. To this aim, starting from bumetanide’s structure, we applied a ligand-based computational approach to design new molecular entities that we tested in vitro for their capacity to selectively block NKCC1. Extensive synthetic efforts and structure-activity relationships analyses allowed us to improve in vitro potency and overall drug-like properties of the initially identified chemical hits. As a result, we identified a new highly potent NKCC1 inhibitor (ARN23746) that displayed excellent solubility, metabolic stability, and no significant effect on NKCC2 in vitro. Moreover, this novel and selective NKCC1 inhibitor was able to rescue cognitive deficits in DS mice and social/repetitive behaviors in ASD mice, with no diuretic effect and no overt toxicity upon chronic treatment in adult animals. Thus, ARN23746 a selective NKCC1 inhibitor devoid of the diuretic effect – represents a suitable and solid therapeutic strategy for the treatment of Down syndrome and all the brain neurological disorders characterized by depolarizing GABAergic transmission.