Analysis of the nuclear properties of Brightest Cluster Galaxies and comparison with "normal" radio galaxies.

The aim of this PhD thesis is the study of the nuclear properties of radio loud AGN. Multiple and/or recent mergers in the host galaxy and/or the presence of cool core in galaxy clusters can play a role in the formation and evolution of the radio source. Being a unique class of objects (Lin & Mohr 2004), we focus on Brightest Cluster Galaxies (BCGs). We investigate their parsec scale radio emission with VLBI (Very Long Baseline Interferometer) observations. From literature or new data , we collect and analyse VLBA (Very Long Baseline) observations at 5 GHz of a complete sample of BCGs and ``normal'' radio galaxies (Bologna Complete Sample , BCS). Results on nuclear properties of BCGs are coming from the comparison with the results for the Bologna COmplete Sample (BCS). Our analysis finds a possible dichotomy between BCGs in cool-core clusters and those in non-cool-core clusters. Only one-sided BCGs have similar kinematic properties with FRIs. Furthermore, the dominance of two-sided jet structures only in cooling clusters suggests sub-relativistic jet velocities. The different jet properties can be related to a different jet origin or to the interaction with a different ISM. We larger discuss on possible explanation of this.

Improved ground motion intensity measures for reliability-based demand analysis of structures

In Performance-Based Earthquake Engineering (PBEE), evaluating the seismic performance (or seismic risk) of a structure at a designed site has gained major attention, especially in the past decade. One of the objectives in PBEE is to quantify the seismic reliability of a structure (due to the future random earthquakes) at a site. For that purpose, Probabilistic Seismic Demand Analysis (PSDA) is utilized as a tool to estimate the Mean Annual Frequency (MAF) of exceeding a specified value of a structural Engineering Demand Parameter (EDP). This dissertation focuses mainly on applying an average of a certain number of spectral acceleration ordinates in a certain interval of periods, Sa,avg (T1,…,Tn), as scalar ground motion Intensity Measure (IM) when assessing the seismic performance of inelastic structures. Since the interval of periods where computing Sa,avg is related to the more or less influence of higher vibration modes on the inelastic response, it is appropriate to speak about improved IMs. The results using these improved IMs are compared with a conventional elastic-based scalar IMs (e.g., pseudo spectral acceleration, Sa ( T(¹)), or peak ground acceleration, PGA) and the advanced inelastic-based scalar IM (i.e., inelastic spectral displacement, Sdi). The advantages of applying improved IMs are: (i ) "computability" of the seismic hazard according to traditional Probabilistic Seismic Hazard Analysis (PSHA), because ground motion prediction models are already available for Sa (Ti), and hence it is possibile to employ existing models to assess hazard in terms of Sa,avg, and (ii ) "efficiency" or smaller variability of structural response, which was minimized to assess the optimal range to compute Sa,avg. More work is needed to assess also "sufficiency" and "scaling robustness" desirable properties, which are disregarded in this dissertation. However, for ordinary records (i.e., with no pulse like effects), using the improved IMs is found to be more accurate than using the elastic- and inelastic-based IMs. For structural demands that are dominated by the first mode of vibration, using Sa,avg can be negligible relative to the conventionally-used Sa (T(¹)) and the advanced Sdi. For structural demands with sign.cant higher-mode contribution, an improved scalar IM that incorporates higher modes needs to be utilized. In order to fully understand the influence of the IM on the seismis risk, a simplified closed-form expression for the probability of exceeding a limit state capacity was chosen as a reliability measure under seismic excitations and implemented for Reinforced Concrete (RC) frame structures. This closed-form expression is partuclarly useful for seismic assessment and design of structures, taking into account the uncertainty in the generic variables, structural "demand" and "capacity" as well as the uncertainty in seismic excitations. The assumed framework employs nonlinear Incremental Dynamic Analysis (IDA) procedures in order to estimate variability in the response of the structure (demand) to seismic excitations, conditioned to IM. The estimation of the seismic risk using the simplified closed-form expression is affected by IM, because the final seismic risk is not constant, but with the same order of magnitude. Possible reasons concern the non-linear model assumed, or the insufficiency of the selected IM. Since it is impossibile to state what is the "real" probability of exceeding a limit state looking the total risk, the only way is represented by the optimization of the desirable properties of an IM.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Genomic and transcriptional analysis of allergen genes in apple (Malus x domestica)

Apple consumption is highly recomended for a healthy diet and is the most important fruit produced in temperate climate regions. Unfortunately, it is also one of the fruit that most ofthen provoks allergy in atopic patients and the only treatment available up to date for these apple allergic patients is the avoidance. Apple allergy is due to the presence of four major classes of allergens: Mal d 1 (PR-10/Bet v 1-like proteins), Mal d 2 (Thaumatine-like proteins), Mal d 3 (Lipid transfer protein) and Mal d 4 (profilin). In this work new advances in the characterization of apple allergen gene families have been reached using a multidisciplinary approach. First of all, a genomic approach was used for the characterization of the allergen gene families of Mal d 1 (task of Chapter 1), Mal d 2 and Mal d 4 (task of Chapter 5). In particular, in Chapter 1 the study of two large contiguos blocks of DNA sequences containing the Mal d 1 gene cluster on LG16 allowed to acquire many new findings on number and orientation of genes in the cluster, their physical distances, their regulatory sequences and the presence of other genes or pseudogenes in this genomic region. Three new members were discovered co-localizing with the other Mal d 1 genes of LG16 suggesting that the complexity of the genetic base of allergenicity will increase with new advances. Many retrotranspon elements were also retrieved in this cluster. Due to the developement of molecular markers on the two sequences, the anchoring of the physical and the genetic map of the region has been successfully achieved. Moreover, in Chapter 5 the existence of other loci for the Thaumatine-like protein family in apple (Mal d 2.03 on LG4 and Mal d 2.02 on LG17) respect the one reported up to now was demonstred for the first time. Also one new locus for profilins (Mal d 4.04) was mapped on LG2, close to the Mal d 4.02 locus, suggesting a cluster organization for this gene family, as is well reported for Mal d 1 family. Secondly, a methodological approach was used to set up an highly specific tool to discriminate and quantify the expression of each Mal d 1 allergen gene (task of Chapter 2). In aprticular, a set of 20 Mal d 1 gene specific primer pairs for the quantitative Real time PCR technique was validated and optimized. As a first application, this tool was used on leaves and fruit tissues of the cultivar Florina in order to identify the Mal d 1 allergen genes that are expressed in different tissues. The differential expression retrieved in this study revealed a tissue-specificity for some Mal d 1 genes: 10/20 Mal d 1 genes were expressed in fruits and, indeed, probably more involved in the allergic reactions; while 17/20 Mal d 1 genes were expressed in leaves challenged with the fungus Venturia inaequalis and therefore probably interesting in the study of the plant defense mechanism. In Chapter 3 the specific expression levels of the 10 Mal d 1 isoallergen genes, found to be expressed in fruits, were studied for the first time in skin and flesh of apples of different genotypes. A complex gene expression profile was obtained due to the high gene-, tissue- and genotype-variability. Despite this, Mal d 1.06A and Mal d 1.07 expression patterns resulted particularly associated with the degree of allergenicity of the different cultivars. They were not the most expressed Mal d 1 genes in apple but here it was hypotized a relevant importance in the determination of allergenicity for both qualitative and quantitative aspects of the Mal d 1 gene expression levels. In Chapter 4 a clear modulation for all the 17 PR-10 genes tested in young leaves of Florina after challenging with the fungus V. inaequalis have been reported but with a peculiar expression profile for each gene. Interestingly, all the Mal d 1 genes resulted up-regulated except Mal d 1.10 that was down-regulated after the challenging with the fungus. The differences in direction, timing and magnitude of induction seem to confirm the hypothesis of a subfunctionalization inside the gene family despite an high sequencce and structure similarity. Moreover, a modulation of PR-10 genes was showed both in compatible (Gala-V. inaequalis) and incompatible (Florina-V. inaequalis) interactions contribute to validate the hypothesis of an indirect role for at least some of these proteins in the induced defense responses. Finally, a certain modulation of PR-10 transcripts retrieved also in leaves treated with water confirm their abilty to respond also to abiotic stress. To conclude, the genomic approach used here allowed to create a comprehensive inventory of all the genes of allergen families, especially in the case of extended gene families like Mal d 1. This knowledge can be considered a basal prerequisite for many further studies. On the other hand, the specific transcriptional approach make it possible to evaluate the Mal d 1 genes behavior on different samples and conditions and therefore, to speculate on their involvement on apple allergenicity process. Considering the double nature of Mal d 1 proteins, as apple allergens and as PR-10 proteins, the gene expression analysis upon the attack of the fungus created the base for unravel the Mal d 1 biological functions. In particular, the knowledge acquired in this work about the PR-10 genes putatively more involved in the specific Malus-V. inaequalis interaction will be helpful, in the future, to drive the apple breeding for hypo-allergenicity genotype without compromise the mechanism of response of the plants to stress conditions. For the future, the survey of the differences in allergenicity among cultivars has to be be thorough including other genotypes and allergic patients in the tests. After this, the allelic diversity analysis with the high and low allergenic cultivars on all the allergen genes, in particular on the ones with transcription levels correlated to allergencity, will provide the genetic background of the low ones. This step from genes to alleles will allow the develop of molecular markers for them that might be used to effectively addressed the apple breeding for hypo-allergenicity. Another important step forward for the study of apple allergens will be the use of a specific proteomic approach since apple allergy is a multifactor-determined disease and only an interdisciplinary and integrated approach can be effective for its prevention and treatment.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Analysis of optimal control problems for the incompressible MHD equations and implementation in a finite element multiphysics code

This thesis deals with the study of optimal control problems for the incompressible Magnetohydrodynamics (MHD) equations. Particular attention to these problems arises from several applications in science and engineering, such as fission nuclear reactors with liquid metal coolant and aluminum casting in metallurgy. In such applications it is of great interest to achieve the control on the fluid state variables through the action of the magnetic Lorentz force. In this thesis we investigate a class of boundary optimal control problems, in which the flow is controlled through the boundary conditions of the magnetic field. Due to their complexity, these problems present various challenges in the definition of an adequate solution approach, both from a theoretical and from a computational point of view. In this thesis we propose a new boundary control approach, based on lifting functions of the boundary conditions, which yields both theoretical and numerical advantages. With the introduction of lifting functions, boundary control problems can be formulated as extended distributed problems. We consider a systematic mathematical formulation of these problems in terms of the minimization of a cost functional constrained by the MHD equations. The existence of a solution to the flow equations and to the optimal control problem are shown. The Lagrange multiplier technique is used to derive an optimality system from which candidate solutions for the control problem can be obtained. In order to achieve the numerical solution of this system, a finite element approximation is considered for the discretization together with an appropriate gradient-type algorithm. A finite element object-oriented library has been developed to obtain a parallel and multigrid computational implementation of the optimality system based on a multiphysics approach. Numerical results of two- and three-dimensional computations show that a possible minimum for the control problem can be computed in a robust and accurate manner.

An interdisciplinary analysis of obesity: theory and empirical evidence

The dissertation is structured in three parts. The first part compares US and EU agricultural policies since the end of WWII. There is not enough evidence for claiming that agricultural support has a negative impact on obesity trends. I discuss the possibility of an exchange in best practices to fight obesity. There are relevant economic, societal and legal differences between the US and the EU. However, partnerships against obesity are welcomed. The second part presents a socio-ecological model of the determinants of obesity. I employ an interdisciplinary model because it captures the simultaneous influence of several variables. Obesity is an interaction of pre-birth, primary and secondary socialization factors. To test the significance of each factor, I use data from the National Longitudinal Survey of Adolescent Health. I compare the average body mass index across different populations. Differences in means are statistically significant. In the last part I use the National Survey of Children Health. I analyze the effect that family characteristics, built environment, cultural norms and individual factors have on the body mass index (BMI). I use Ordered Probit models and I calculate the marginal effects. I use State and ethnicity fixed effects to control for unobserved heterogeneity. I find that southern US States tend have on average a higher probability of being obese. On the ethnicity side, White Americans have a lower BMI respect to Black Americans, Hispanics and American Indians Native Islanders; being Asian is associated with a lower probability of being obese. In neighborhoods where trust level and safety perception are higher, children are less overweight and obese. Similar results are shown for higher level of parental income and education. Breastfeeding has a negative impact. Higher values of measures of behavioral disorders have a positive and significant impact on obesity, as predicted by the theory.

An Analysis of Living Conditions in Rural Villages in China. A New Geography of the Country.

Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

Analysis of the Slow Food movement impact on the farmers and rural areas’ sustainable development

The evaluation of the farmers’ communities’ approach to the Slow Food vision, their perception of the Slow Food role in supporting their activity and their appreciation and expectations from participating in the event of Mother Earth were studied. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was adopted in an agro-food sector context. A survey was conducted, 120 questionnaires from farmers attending the Mother Earth in Turin in 2010 were collected. The descriptive statistical analysis showed that both Slow Food membership and participation to Mother Earth Meeting were much appreciated for the support provided to their business and the contribution to a more sustainable and fair development. A positive social, environmental and psychological impact on farmers also resulted. Results showed also an interesting perspective on the possible universality of the Slow Food and Mother Earth values. Farmers declared that Slow Food is supporting them by preserving the biodiversity and orienting them to the use of local resources and reducing the chemical inputs. Many farmers mentioned the language/culture and administration/bureaucratic issues as an obstacle to be a member in the movement and to participate to the event. Participation to Mother Earth gives an opportunity to exchange information with other farmers’ communities and to participate to seminars and debates, helpful for their business development. The absolute majority of positive answers associated to the farmers’ willingness to relate to Slow Food and participate to the next Mother Earth editions negatively influenced the UTAUT model results. A factor analysis showed that the variables associated to the UTAUT model constructs Performance Expectancy and Effort Expectancy were consistent, able to explain the construct variability, and their measurement reliable. Their inclusion in a simplest Technology Acceptance Model could be considered in future researches.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.

Homogeneous analysis of a sample of Open Clusters in the context of the BOCCE project and the Gaia-ESO Survey

The open clusters (OC) are gravitationally bound systems of a few tens or hundreds of stars. In our Galaxy, the Milky Way, we know about 3000 open clusters, of very different ages in the range of a few millions years to about 9 Gyr. OCs are mainly located in the Galactic thin disc, with distances from the Galactic centre in the range 4-22 kpc and a height scale on the disc of about 200 pc. Their chemical properties trace those of the environment in which they formed and the metallicity is in the range -0.5<[Fe/H]<+0.5 dex. Through photometry and spectroscopy it is possible to study relatively easily the properties of the OCs and estimate their age, distance, and chemistry. For these reasons they are considered primary tracers of the chemical properties and chemical evolution of the Galactic disc. The main subject of this thesis is the comprehensive study of several OCs. The research embraces two different projects: the Bologna Open Cluster Chemical Evolution project (BOCCE) and the Gaia-ESO Survey. The first is a long-term programme, aiming at studying the chemical evolution of the Milky Way disc by means of a homogeneous sample of OCs. The latter is a large public spectroscopy survey, conducted with the high-resolution spectrograph FLAMES@VLT and targeting about 10^5 stars in different part of the Galaxy and 10^4 stars in about 100 OCs. The common ground between the two projects is the study of the properties of the OCs as tracers of the disc's characteristics. The impressive scientific outcome of the Gaia-ESO Survey and the unique framework of homogeneity of the BOCCE project can propose, especially once combined together, a much more accurate description of the properties of the OCs. In turn, this will give fundamental constraints for the interpretation of the properties of the Galactic disc.

Displacement Analysis of Under-Constrained Cable-Driven Parallel Robots

This dissertation studies the geometric static problem of under-constrained cable-driven parallel robots (CDPRs) supported by n cables, with n ≤ 6. The task consists of determining the overall robot configuration when a set of n variables is assigned. When variables relating to the platform posture are assigned, an inverse geometric static problem (IGP) must be solved; whereas, when cable lengths are given, a direct geometric static problem (DGP) must be considered. Both problems are challenging, as the robot continues to preserve some degrees of freedom even after n variables are assigned, with the final configuration determined by the applied forces. Hence, kinematics and statics are coupled and must be resolved simultaneously. In this dissertation, a general methodology is presented for modelling the aforementioned scenario with a set of algebraic equations. An elimination procedure is provided, aimed at solving the governing equations analytically and obtaining a least-degree univariate polynomial in the corresponding ideal for any value of n. Although an analytical procedure based on elimination is important from a mathematical point of view, providing an upper bound on the number of solutions in the complex field, it is not practical to compute these solutions as it would be very time-consuming. Thus, for the efficient computation of the solution set, a numerical procedure based on homotopy continuation is implemented. A continuation algorithm is also applied to find a set of robot parameters with the maximum number of real assembly modes for a given DGP. Finally, the end-effector pose depends on the applied load and may change due to external disturbances. An investigation into equilibrium stability is therefore performed.

Risk analysis of tractor rollover in the normal operation in field

Tractor rollover represent a primary cause of death or serious injury in agriculture and despite the mandatory Roll-Over Protective Structures (ROPS), that reduced the number of injuries, tractor accidents are still of great concern. Because of their versatility and wide use many studies on safety are concerned with the stability of tractors, but they often prefer controlled tests or laboratory tests. The evaluation of tractors working in field, instead, is a very complex issue because the rollover could be influenced by the interaction among operator, tractor and environment. Recent studies are oriented towards the evaluation of the actual working conditions developing prototypes for driver assistance and data acquisition. Currently these devices are produced and sold by manufacturers. A warning device was assessed in this study with the aim to evaluate its performance and to collect data on different variables influencing the dynamics of tractors in field by monitoring continuously the working conditions of tractors operating at the experimental farm of the Bologna University. The device consists of accelerometers, gyroscope, GSM/GPRS, GPS for geo-referencing and a transceiver for the automatic recognition of tractor-connected equipment. A microprocessor processes data and provides information, through a dedicated algorithm requiring data on the geometry of the tested tractor, on the level of risk for the operator in terms of probable loss of stability and suggests corrective measures to reduce the potential instability of the tractor.

Analysis of slip distribution of large earthquakes oriented to tsunamigenesis characterisation

The present thesis focuses on the on-fault slip distribution of large earthquakes in the framework of tsunami hazard assessment and tsunami warning improvement. It is widely known that ruptures on seismic faults are strongly heterogeneous. In the case of tsunamigenic earthquakes, the slip heterogeneity strongly influences the spatial distribution of the largest tsunami effects along the nearest coastlines. Unfortunately, after an earthquake occurs, the so-called finite-fault models (FFM) describing the coseismic on-fault slip pattern becomes available over time scales that are incompatible with early tsunami warning purposes, especially in the near field. Our work aims to characterize the slip heterogeneity in a fast, but still suitable way. Using finite-fault models to build a starting dataset of seismic events, the characteristics of the fault planes are studied with respect to the magnitude. The patterns of the slip distribution on the rupture plane, analysed with a cluster identification algorithm, reveal a preferential single-asperity representation that can be approximated by a two-dimensional Gaussian slip distribution (2D GD). The goodness of the 2D GD model is compared to other distributions used in literature and its ability to represent the slip heterogeneity in the form of the main asperity is proven. The magnitude dependence of the 2D GD parameters is investigated and turns out to be of primary importance from an early warning perspective. The Gaussian model is applied to the 16 September 2015 Illapel, Chile, earthquake and used to compute early tsunami predictions that are satisfactorily compared with the available observations. The fast computation of the 2D GD and its suitability in representing the slip complexity of the seismic source make it a useful tool for the tsunami early warning assessments, especially for what concerns the near field.