Optimization of bioenergy solutions at different farm scales

RAF is a bio-energetic descriptive model integrates with MAD model to support Integrated Farm Management. RAF model aimed to enhancing economical, social and environmental sustainability of farm production in terms of energy via convert energy crops and animal manure to biogas and digestate (bio-fertilizers) by anaerobic digestion technologies, growing and breeding practices. The user defines farm structure in terms of present crops, livestock and market prices and RAF model investigates the possibilities of establish on-farm biogas system (different anaerobic digestion technologies proposed for different scales of farms in terms of energy requirements) according to budget and sustainability constraints to reduce the dependence on fossil fuels. The objective function of RAF (Z) is optimizing the total net income of farm (maximizing income and minimizing costs) for whole period which is considered by the analysis. The main results of this study refers to the possibility of enhancing the exploitation of the available Italian potentials of biogas production from on-farm production of energy crops and livestock manure feedstock by using the developed mathematical model RAF integrates with MAD to presents reliable reconcile between farm size, farm structure and on-farm biogas systems technologies applied to support selection, applying and operating of appropriate biogas technology at any farm under Italian conditions.

Metodi di ottimizzazione morfologica nel progetto preliminare di propulsori aeronautici avanzati

The aim of this Doctoral Thesis is to develop a genetic algorithm based optimization methods to find the best conceptual design architecture of an aero-piston-engine, for given design specifications. Nowadays, the conceptual design of turbine airplanes starts with the aircraft specifications, then the most suited turbofan or turbo propeller for the specific application is chosen. In the aeronautical piston engines field, which has been dormant for several decades, as interest shifted towards turboaircraft, new materials with increased performance and properties have opened new possibilities for development. Moreover, the engine’s modularity given by the cylinder unit, makes it possible to design a specific engine for a given application. In many real engineering problems the amount of design variables may be very high, characterized by several non-linearities needed to describe the behaviour of the phenomena. In this case the objective function has many local extremes, but the designer is usually interested in the global one. The stochastic and the evolutionary optimization techniques, such as the genetic algorithms method, may offer reliable solutions to the design problems, within acceptable computational time. The optimization algorithm developed here can be employed in the first phase of the preliminary project of an aeronautical piston engine design. It’s a mono-objective genetic algorithm, which, starting from the given design specifications, finds the engine propulsive system configuration which possesses minimum mass while satisfying the geometrical, structural and performance constraints. The algorithm reads the project specifications as input data, namely the maximum values of crankshaft and propeller shaft speed and the maximal pressure value in the combustion chamber. The design variables bounds, that describe the solution domain from the geometrical point of view, are introduced too. In the Matlab® Optimization environment the objective function to be minimized is defined as the sum of the masses of the engine propulsive components. Each individual that is generated by the genetic algorithm is the assembly of the flywheel, the vibration damper and so many pistons, connecting rods, cranks, as the number of the cylinders. The fitness is evaluated for each individual of the population, then the rules of the genetic operators are applied, such as reproduction, mutation, selection, crossover. In the reproduction step the elitist method is applied, in order to save the fittest individuals from a contingent mutation and recombination disruption, making it undamaged survive until the next generation. Finally, as the best individual is found, the optimal dimensions values of the components are saved to an Excel® file, in order to build a CAD-automatic-3D-model for each component of the propulsive system, having a direct pre-visualization of the final product, still in the engine’s preliminary project design phase. With the purpose of showing the performance of the algorithm and validating this optimization method, an actual engine is taken, as a case study: it’s the 1900 JTD Fiat Avio, 4 cylinders, 4T, Diesel. Many verifications are made on the mechanical components of the engine, in order to test their feasibility and to decide their survival through generations. A system of inequalities is used to describe the non-linear relations between the design variables, and is used for components checking for static and dynamic loads configurations. The design variables geometrical boundaries are taken from actual engines data and similar design cases. Among the many simulations run for algorithm testing, twelve of them have been chosen as representative of the distribution of the individuals. Then, as an example, for each simulation, the corresponding 3D models of the crankshaft and the connecting rod, have been automatically built. In spite of morphological differences among the component the mass is almost the same. The results show a significant mass reduction (almost 20% for the crankshaft) in comparison to the original configuration, and an acceptable robustness of the method have been shown. The algorithm here developed is shown to be a valid method for an aeronautical-piston-engine preliminary project design optimization. In particular the procedure is able to analyze quite a wide range of design solutions, rejecting the ones that cannot fulfill the feasibility design specifications. This optimization algorithm could increase the aeronautical-piston-engine development, speeding up the production rate and joining modern computation performances and technological awareness to the long lasting traditional design experiences.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Referee Assignment Problem Case: Italian Volleyball Championships

This thesis addresses the formulation of a referee assignment problem for the Italian Volleyball Serie A Championships. The problem has particular constraints such as a referee must be assigned to different teams in a given period of times, and the minimal/maximal level of workload for each referee is obtained by considering cost and profit in the objective function. The problem has been solved through an exact method by using an integer linear programming formulation and a clique based decomposition for improving the computing time. Extensive computational experiments on real-world instances have been performed to determine the effectiveness of the proposed approach.

Stima dei parametri di modelli idrologici mediante ottimizzazione dell’utilità

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste.

Computational tool for three-point hitch geometry optimization

The weight-transfer effect, consisting of the change in dynamic load distribution between the front and the rear tractor axles, is one of the most impairing phenomena for the performance, comfort, and safety of agricultural operations. Excessive weight transfer from the front to the rear tractor axle can occur during operation or maneuvering of implements connected to the tractor through the three-point hitch (TPH). In this respect, an optimal design of the TPH can ensure better dynamic load distribution and ultimately improve operational performance, comfort, and safety. In this study, a computational design tool (The Optimizer) for the determination of a TPH geometry that minimizes the weight-transfer effect is developed. The Optimizer is based on a constrained minimization algorithm. The objective function to be minimized is related to the tractor front-to-rear axle load transfer during a simulated reference maneuver performed with a reference implement on a reference soil. Simulations are based on a 3-degrees-of-freedom (DOF) dynamic model of the tractor-TPH-implement aggregate. The inertial, elastic, and viscous parameters of the dynamic model were successfully determined through a parameter identification algorithm. The geometry determined by the Optimizer complies with the ISO-730 Standard functional requirements and other design requirements. The interaction between the soil and the implement during the simulated reference maneuver was successfully validated against experimental data. Simulation results show that the adopted reference maneuver is effective in triggering the weight-transfer effect, with the front axle load exhibiting a peak-to-peak value of 27.1 kN during the maneuver. A benchmark test was conducted starting from four geometries of a commercially available TPH. As result, all the configurations were optimized by above 10%. The Optimizer, after 36 iterations, was able to find an optimized TPH geometry which allows to reduce the weight-transfer effect by 14.9%.

Methods for objective and interpretative evaluation of function and motor control: gait in perturbed condition and in the aquatic therapy

Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.

A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Asset management of wastewater networks

Asset Management (AM) is a set of procedures operable at the strategic-tacticaloperational level, for the management of the physical asset’s performance, associated risks and costs within its whole life-cycle. AM combines the engineering, managerial and informatics points of view. In addition to internal drivers, AM is driven by the demands of customers (social pull) and regulators (environmental mandates and economic considerations). AM can follow either a top-down or a bottom-up approach. Considering rehabilitation planning at the bottom-up level, the main issue would be to rehabilitate the right pipe at the right time with the right technique. Finding the right pipe may be possible and practicable, but determining the timeliness of the rehabilitation and the choice of the techniques adopted to rehabilitate is a bit abstruse. It is a truism that rehabilitating an asset too early is unwise, just as doing it late may have entailed extra expenses en route, in addition to the cost of the exercise of rehabilitation per se. One is confronted with a typical ‘Hamlet-isque dilemma’ – ‘to repair or not to repair’; or put in another way, ‘to replace or not to replace’. The decision in this case is governed by three factors, not necessarily interrelated – quality of customer service, costs and budget in the life cycle of the asset in question. The goal of replacement planning is to find the juncture in the asset’s life cycle where the cost of replacement is balanced by the rising maintenance costs and the declining level of service. System maintenance aims at improving performance and maintaining the asset in good working condition for as long as possible. Effective planning is used to target maintenance activities to meet these goals and minimize costly exigencies. The main objective of this dissertation is to develop a process-model for asset replacement planning. The aim of the model is to determine the optimal pipe replacement year by comparing, temporally, the annual operating and maintenance costs of the existing asset and the annuity of the investment in a new equivalent pipe, at the best market price. It is proposed that risk cost provide an appropriate framework to decide the balance between investment for replacing or operational expenditures for maintaining an asset. The model describes a practical approach to estimate when an asset should be replaced. A comprehensive list of criteria to be considered is outlined, the main criteria being a visà- vis between maintenance and replacement expenditures. The costs to maintain the assets should be described by a cost function related to the asset type, the risks to the safety of people and property owing to declining condition of asset, and the predicted frequency of failures. The cost functions reflect the condition of the existing asset at the time the decision to maintain or replace is taken: age, level of deterioration, risk of failure. The process model is applied in the wastewater network of Oslo, the capital city of Norway, and uses available real-world information to forecast life-cycle costs of maintenance and rehabilitation strategies and support infrastructure management decisions. The case study provides an insight into the various definitions of ‘asset lifetime’ – service life, economic life and physical life. The results recommend that one common value for lifetime should not be applied to the all the pipelines in the stock for investment planning in the long-term period; rather it would be wiser to define different values for different cohorts of pipelines to reduce the uncertainties associated with generalisations for simplification. It is envisaged that more criteria the municipality is able to include, to estimate maintenance costs for the existing assets, the more precise will the estimation of the expected service life be. The ability to include social costs enables to compute the asset life, not only based on its physical characterisation, but also on the sensitivity of network areas to social impact of failures. The type of economic analysis is very sensitive to model parameters that are difficult to determine accurately. The main value of this approach is the effort to demonstrate that it is possible to include, in decision-making, factors as the cost of the risk associated with a decline in level of performance, the level of this deterioration and the asset’s depreciation rate, without looking at age as the sole criterion for making decisions regarding replacements.

Supramolecular functional assemblies with photo or chemical addressability

Supramolecular self-assembly represents a key technology for the spontaneous construction of nanoarchitectures and for the fabrication of materials with enhanced physical and chemical properties. In addition, a significant asset of supramolecular self-assemblies rests on their reversible formation, thanks to the kinetic lability of their non-covalent interactions. This dynamic nature can be exploited for the development of “self-healing” and “smart” materials towards the tuning of their functional properties upon various external factors. One particular intriguing objective in the field is to reach a high level of control over the shape and size of the supramolecular architectures, in order to produce well-defined functional nanostructures by rational design. In this direction, many investigations have been pursued toward the construction of self-assembled objects from numerous low-molecular weight scaffolds, for instance by exploiting multiple directional hydrogen-bonding interactions. In particular, nucleobases have been used as supramolecular synthons as a result of their efficiency to code for non-covalent interaction motifs. Among nucleobases, guanine represents the most versatile one, because of its different H-bond donor and acceptor sites which display self-complementary patterns of interactions. Interestingly, and depending on the environmental conditions, guanosine derivatives can form various types of structures. Most of the supramolecular architectures reported in this Thesis from guanosine derivatives require the presence of a cation which stabilizes, via dipole-ion interactions, the macrocyclic G-quartet that can, in turn, stack in columnar G-quadruplex arrangements. In addition, in absence of cations, guanosine can polymerize via hydrogen bonding to give a variety of supramolecular networks including linear ribbons. This complex supramolecular behavior confers to the guanine-guanine interactions their upper interest among all the homonucleobases studied. They have been subjected to intense investigations in various areas ranging from structural biology and medicinal chemistry – guanine-rich sequences are abundant in telomeric ends of chromosomes and promoter regions of DNA, and are capable of forming G-quartet based structures– to material science and nanotechnology. This Thesis, organized into five Chapters, describes mainly some recent advances in the form and function provided by self-assembly of guanine based systems. More generally, Chapter 4 will focus on the construction of supramolecular self-assemblies whose self-assembling process and self-assembled architectures can be controlled by light as external stimulus. Chapter 1 will describe some of the many recent studies of G-quartets in the general area of nanoscience. Natural G- quadruplexes can be useful motifs to build new structures and biomaterials such as self-assembled nanomachines, biosensors, therapeutic aptamer and catalysts. In Chapters 2-4 it is pointed out the core concept held in this PhD Thesis, i.e. the supramolecular organization of lipophilic guanosine derivatives with photo or chemical addressability. Chapter 2 will mainly focus on the use of cation-templated guanosine derivatives as a potential scaffold for designing functional materials with tailored physical properties, showing a new way to control the bottom-up realization of well-defined nanoarchitectures. In section 2.6.7, the self-assembly properties of compound 28a may be considered an example of open-shell moieties ordered by a supramolecular guanosine architecture showing a new (magnetic) property. Chapter 3 will report on ribbon-like structures, supramolecular architectures formed by guanosine derivatives that may be of interest for the fabrication of molecular nanowires within the framework of future molecular electronic applications. In section 3.4 we investigate the supramolecular polymerizations of derivatives dG 1 and G 30 by light scattering technique and TEM experiments. The obtained data reveal the presence of several levels of organization due to the hierarchical self-assembly of the guanosine units in ribbons that in turn aggregate in fibrillar or lamellar soft structures. The elucidation of these structures furnishes an explanation to the physical behaviour of guanosine units which display organogelator properties. Chapter 4 will describe photoresponsive self-assembling systems. Numerous research examples have demonstrated that the use of photochromic molecules in supramolecular self-assemblies is the most reasonable method to noninvasively manipulate their degree of aggregation and supramolecular architectures. In section 4.4 we report on the photocontrolled self-assembly of modified guanosine nucleobase E-42: by the introduction of a photoactive moiety at C8 it is possible to operate a photocontrol over the self-assembly of the molecule, where the existence of G-quartets can be alternately switched on and off. In section 4.5 we focus on the use of cyclodextrins as photoresponsive host-guest assemblies: αCD–azobenzene conjugates 47-48 (section 4.5.3) are synthesized in order to obtain a photoresponsive system exhibiting a fine photocontrollable degree of aggregation and self-assembled architecture. Finally, Chapter 5 contains the experimental protocols used for the research described in Chapters 2-4.

Interaction between APOE4 genotype and environmental risk factors in Alzheimer's disease

Alzheimer's disease (AD) is probably caused by both genetic and environmental risk factors. The major genetic risk factor is the E4 variant of apolipoprotein E gene called apoE4. Several risk factors for developing AD have been identified including lifestyle, such as dietary habits. The mechanisms behind the AD pathogenesis and the onset of cognitive decline in the AD brain are presently unknown. In this study we wanted to characterize the effects of the interaction between environmental risk factors and apoE genotype on neurodegeneration processes, with particular focus on behavioural studies and neurodegenerative processes at molecular level. Towards this aim, we used 6 months-old apoE4 and apoE3 Target Replacement (TR) mice fed on different diets (high intake of cholesterol and high intake of carbohydrates). These mice were evaluated for learning and memory deficits in spatial reference (Morris Water Maze (MWM)) and contextual learning (Passive Avoidance) tasks, which involve the hippocampus and the amygdala, respectively. From these behavioural studies we found that the initial cognitive impairments manifested as a retention deficit in apoE4 mice fed on high carbohydrate diet. Thus, the genetic risk factor apoE4 genotype associated with a high carbohydrate diet seems to affect cognitive functions in young mice, corroborating the theory that the combination of genetic and environmental risk factors greatly increases the risk of developing AD and leads to an earlier onset of cognitive deficits. The cellular and molecular bases of the cognitive decline in AD are largely unknown. In order to determine the molecular changes for the onset of the early cognitive impairment observed in the behavioural studies, we performed molecular studies, with particular focus on synaptic integrity and Tau phosphorylation. The most relevant finding of our molecular studies showed a significant decrease of Brain-derived Neurotrophic Factor (BDNF) in apoE4 mice fed on high carbohydrate diet. Our results may suggest that BDNF decrease found in apoE4 HS mice could be involved in the earliest impairment in long-term reference memory observed in behavioural studies. The second aim of this thesis was to study possible involvement of leptin in AD. There is growing evidence that leptin has neuroprotective properties in the Central Nervous System (CNS). Recent evidence has shown that leptin and its receptors are widespread in the CNS and may provide neuronal survival signals. However, there are still numerous questions, regarding the molecular mechanism by which leptin acts, that remain unanswered. Thus, given to the importance of the involvement of leptin in AD, we wanted to clarify the function of leptin in the pathogenesis of AD and to investigate if apoE genotype affect leptin levels through studies in vitro, in mice and in human. Our findings suggest that apoE4 TR mice showed an increase of leptin in the brain. Leptin levels are also increased in the cerebral spinal fluid of AD patients and apoE4 carriers with AD have higher levels of leptin than apoE3 carriers. Moreover, leptin seems to be expressed by reactive glial cells in AD brains. In vitro, ApoE4 together with Amyloid beta increases leptin production by microglia and astrocytes. Taken together, all these findings suggest that leptin replacement might not be a good strategy for AD therapy. Our results show that high leptin levels were found in AD brains. These findings suggest that, as high leptin levels do not promote satiety in obese individuals, it might be possible that they do not promote neuroprotection in AD patients. Therefore, we hypothesized that AD brain could suffer from leptin resistance. Further studies will be critical to determine whether or not the central leptin resistance in SNC could affect its potential neuroprotective effects.

Sustainability indicators for environmental management and decision making

The general objective of this research is to explore theories and methodologies of sustainability indicators, environmental management and decision making disciplines with the operational purpose of producing scientific, robust and relevant information for supporting system understanding and decision making in real case studies. Several tools have been applied in order to increase the understanding of socio-ecological systems as well as providing relevant information on the choice between alternatives. These tools have always been applied having in mind the complexity of the issues and the uncertainty tied to the partial knowledge of the systems under study. Two case studies with specific application to performances measurement (environmental performances in the case of the K8 approach and sustainable development performances in the case of the EU Sustainable Development Strategy) and a case study about the selection of sustainable development indicators amongst Municipalities in Scotland, are discussed in the first part of the work. In the second part of the work, the common denominator among subjects consists in the application of spatial indices and indicators to address operational problems in land use management within the territory of the Ravenna province (Italy). The main conclusion of the thesis is that a ‘perfect’ methodological approach which always produces the best results in assessing sustainability performances does not exist. Rather, there is a pool of correct approaches answering different evaluation questions, to be used when methodologies fit the purpose of the analysis. For this reason, methodological limits and conceptual assumptions as well as consistency and transparency of the assessment, become the key factors for assessing the quality of the analysis.

Effect of estrogen suppression on lung function in pulmonary Lymphangioleiomyomatosis

Background: Lymphangioleiomyomatosis (LAM), a rare progressive disease, is characterized by the proliferation of abnormal smooth muscle cells (LAM cells) in the lung, which leads to cystic parenchymal destruction and progressive respiratory failure. Estrogen receptors are present in LAM cells. LAM affects almost exclusively women of childbearing age. These findings, along with reports of disease progression during pregnancy or treatment with exogenous estrogens, have led to the assumption that hormonal factors play an important role in the pathogenesis of LAM. So, various therapies aim at preventing estrogen receptors (ER) by lowering circulating estrogen levels, by trying to block ER activity, or by attempting to lower ER expression in LAM. Prior experience have yielded conflicting results. Objective: The goal of this study was to evaluate, retrospectively, the effect of estrogen suppression in 21 patients with LAM. Design: We evaluated hormonal assays, pulmonary function tests and gas-exchange at baseline and after 12, 24 and 36 months after initiating hormonal manipulation. Results: The mean yearly rates of decline in FEV1 and DLCO are lower than those observed in prior studies and just DLCO decline was statistically significant. We also found an improvement of mean value of FVC and PaO2. Conclusions: Estrogen suppression appears to prevent decline in lung function in LAM.

The role of collective action in the provision of agri-environmental public goods: theoretical development through case studies in Italy

The thesis aims at analysing the role of collective action as a viable alternative to the traditional forms of intervention in agriculture in order to encourage the provision of agri-environmental public goods. Which are the main benefits of collective action, in terms of effectiveness and efficiency, compared to traditional market or public intervention policies? What are the drivers that encourage farmers to participate into collective action? To what extent it is possible to incorporate collective aspects into policies aimed at providing agri-environmental public goods? With the objective of addressing these research questions, the thesis is articulated in two levels: a theoretical analysis on the role of collective action in the provision of public goods and a specific investigation of two local initiative,s were an approach collective management of agro-environmental resources was successfully implemented. The first case study concerns a project named “Custodians of the Territory”, developed by the local agency in Tuscany “Comunità Montana Media Valle del Serchio”, which settled for an agreement with local farmers for a collective provision of environmental services related to the hydro-geological management of the district. The second case study is related to the territorial agri-environmental agreement experimented in Valdaso (Marche), where local farmers have adopted integrated pest management practices collectively with the aim of reducing the environmental impact of their farming practices. The analysis of these initiatives, carried out through participatory methods (Rapid Rural Appraisal), allowed developing a theoretical discussion on the role of innovative tools (such as co-production and co-management) in the provision of agri-environmental public goods. The case studies also provided some recommendations on the government intervention and policies needed to promote successful collective action for the provision of agri-environmental public goods.

Relationships between plant diversity and environmental heterogeneity in rupicolous grasslands on gypsum. The case study of Alysso-Sedion albi (Habitat 6110).

Plant communities on weathered rock and outcrops are characterized by high values in species richness (Dengler 2006) and often persist on small and fragmented surfaces. Yet very few studies have examined the relationships between heterogeneity and plant diversity at small scales, in particular in poor-nutrient and low productive environment (Shmida and Wilson 1985, Lundholm 2003). In order to assess these relationships both in space and time in relationship, two different approaches were employed in the present study, in two gypsum outcrops of Northern Apennine. Diachronic and synchronic samplings from April 2012 to March 2013 were performed. A 50x50 cm plot was used in both samplings such as the sampling unit base. The diachronic survey aims to investigate seasonal patterning of plant diversity by the use of images analysis techniques integrated with field data and considering also seasonal climatic trend, the substrate quality and its variation in time. The purpose of the further, synchronic sampling was to describe plant diversity pattern as a function of the environmental heterogeneity meaning in substrate typologies, soil depth and topographic features. Results showed that responses of diversity pattern depend both on the resources availability, environmental heterogeneity and the manner in which the different taxonomic group access to them during the year. Species richness and Shannon diversity were positively affected by increasing in substrate heterogeneity. Furthermore a good turnover in seasonal species occurrence was detected. This vegetation may be described by the coexistence of three groups of species which created a gradient from early colonization stages, characterized by greater slope and predominance of bare rock, gradually to situation of more developed soil.