Light energy management in peach: utilization, photoprotection , photodamage and recovery. Maximizing light absorption in orchard is not always the best solution

The relation between the intercepted light and orchard productivity was considered linear, although this dependence seems to be more subordinate to planting system rather than light intensity. At whole plant level not always the increase of irradiance determines productivity improvement. One of the reasons can be the plant intrinsic un-efficiency in using energy. Generally in full light only the 5 – 10% of the total incoming energy is allocated to net photosynthesis. Therefore preserving or improving this efficiency becomes pivotal for scientist and fruit growers. Even tough a conspicuous energy amount is reflected or transmitted, plants can not avoid to absorb photons in excess. The chlorophyll over-excitation promotes the reactive species production increasing the photoinhibition risks. The dangerous consequences of photoinhibition forced plants to evolve a complex and multilevel machine able to dissipate the energy excess quenching heat (Non Photochemical Quenching), moving electrons (water-water cycle , cyclic transport around PSI, glutathione-ascorbate cycle and photorespiration) and scavenging the generated reactive species. The price plants must pay for this equipment is the use of CO2 and reducing power with a consequent decrease of the photosynthetic efficiency, both because some photons are not used for carboxylation and an effective CO2 and reducing power loss occurs. Net photosynthesis increases with light until the saturation point, additional PPFD doesn’t improve carboxylation but it rises the efficiency of the alternative pathways in energy dissipation but also ROS production and photoinhibition risks. The wide photo-protective apparatus, although is not able to cope with the excessive incoming energy, therefore photodamage occurs. Each event increasing the photon pressure and/or decreasing the efficiency of the described photo-protective mechanisms (i.e. thermal stress, water and nutritional deficiency) can emphasize the photoinhibition. Likely in nature a small amount of not damaged photosystems is found because of the effective, efficient and energy consuming recovery system. Since the damaged PSII is quickly repaired with energy expense, it would be interesting to investigate how much PSII recovery costs to plant productivity. This PhD. dissertation purposes to improve the knowledge about the several strategies accomplished for managing the incoming energy and the light excess implication on photo-damage in peach. The thesis is organized in three scientific units. In the first section a new rapid, non-intrusive, whole tissue and universal technique for functional PSII determination was implemented and validated on different kinds of plants as C3 and C4 species, woody and herbaceous plants, wild type and Chlorophyll b-less mutant and monocot and dicot plants. In the second unit, using a “singular” experimental orchard named “Asymmetric orchard”, the relation between light environment and photosynthetic performance, water use and photoinhibition was investigated in peach at whole plant level, furthermore the effect of photon pressure variation on energy management was considered on single leaf. In the third section the quenching analysis method suggested by Kornyeyev and Hendrickson (2007) was validate on peach. Afterwards it was applied in the field where the influence of moderate light and water reduction on peach photosynthetic performances, water requirements, energy management and photoinhibition was studied. Using solar energy as fuel for life plant is intrinsically suicidal since the high constant photodamage risk. This dissertation would try to highlight the complex relation existing between plant, in particular peach, and light analysing the principal strategies plants developed to manage the incoming light for deriving the maximal benefits as possible minimizing the risks. In the first instance the new method proposed for functional PSII determination based on P700 redox kinetics seems to be a valid, non intrusive, universal and field-applicable technique, even because it is able to measure in deep the whole leaf tissue rather than the first leaf layers as fluorescence. Fluorescence Fv/Fm parameter gives a good estimate of functional PSII but only when data obtained by ad-axial and ab-axial leaf surface are averaged. In addition to this method the energy quenching analysis proposed by Kornyeyev and Hendrickson (2007), combined with the photosynthesis model proposed by von Caemmerer (2000) is a forceful tool to analyse and study, even in the field, the relation between plant and environmental factors such as water, temperature but first of all light. “Asymmetric” training system is a good way to study light energy, photosynthetic performance and water use relations in the field. At whole plant level net carboxylation increases with PPFD reaching a saturating point. Light excess rather than improve photosynthesis may emphasize water and thermal stress leading to stomatal limitation. Furthermore too much light does not promote net carboxylation improvement but PSII damage, in fact in the most light exposed plants about 50-60% of the total PSII is inactivated. At single leaf level, net carboxylation increases till saturation point (1000 – 1200 μmolm-2s-1) and light excess is dissipated by non photochemical quenching and non net carboxylative transports. The latter follows a quite similar pattern of Pn/PPFD curve reaching the saturation point at almost the same photon flux density. At middle-low irradiance NPQ seems to be lumen pH limited because the incoming photon pressure is not enough to generate the optimum lumen pH for violaxanthin de-epoxidase (VDE) full activation. Peach leaves try to cope with the light excess increasing the non net carboxylative transports. While PPFD rises the xanthophyll cycle is more and more activated and the rate of non net carboxylative transports is reduced. Some of these alternative transports, such as the water-water cycle, the cyclic transport around the PSI and the glutathione-ascorbate cycle are able to generate additional H+ in lumen in order to support the VDE activation when light can be limiting. Moreover the alternative transports seems to be involved as an important dissipative way when high temperature and sub-optimal conductance emphasize the photoinhibition risks. In peach, a moderate water and light reduction does not determine net carboxylation decrease but, diminishing the incoming light and the environmental evapo-transpiration request, stomatal conductance decreases, improving water use efficiency. Therefore lowering light intensity till not limiting levels, water could be saved not compromising net photosynthesis. The quenching analysis is able to partition absorbed energy in the several utilization, photoprotection and photo-oxidation pathways. When recovery is permitted only few PSII remained un-repaired, although more net PSII damage is recorded in plants placed in full light. Even in this experiment, in over saturating light the main dissipation pathway is the non photochemical quenching; at middle-low irradiance it seems to be pH limited and other transports, such as photorespiration and alternative transports, are used to support photoprotection and to contribute for creating the optimal trans-thylakoidal ΔpH for violaxanthin de-epoxidase. These alternative pathways become the main quenching mechanisms at very low light environment. Another aspect pointed out by this study is the role of NPQ as dissipative pathway when conductance becomes severely limiting. The evidence that in nature a small amount of damaged PSII is seen indicates the presence of an effective and efficient recovery mechanism that masks the real photodamage occurring during the day. At single leaf level, when repair is not allowed leaves in full light are two fold more photoinhibited than the shaded ones. Therefore light in excess of the photosynthetic optima does not promote net carboxylation but increases water loss and PSII damage. The more is photoinhibition the more must be the photosystems to be repaired and consequently the energy and dry matter to allocate in this essential activity. Since above the saturation point net photosynthesis is constant while photoinhibition increases it would be interesting to investigate how photodamage costs in terms of tree productivity. An other aspect of pivotal importance to be further widened is the combined influence of light and other environmental parameters, like water status, temperature and nutrition on peach light, water and phtosyntate management.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Influence of climate changes on cross allergies: possible involvement of pollen transglutaminase

Allergies are a complex of symptoms derived from altered IgE-mediated reactions of the immune system towards substances known as allergens. Allergic sensibilization can be of food or respiratory origin and, in particular, apple and hazelnut allergens have been identified in pollens or fruits. Allergic cross-reactivity can occur in a patient reacting to similar allergens from different origins, justifying the research in both systems as in Europe a greater number of people suffers from apple fruit allergy, but little evidence exists about pollen. Apple fruit allergies are due to four different classes of allergens (Mal d 1, 2, 3, 4), whose allergenicity is related both to genotype and tissue specificity; therefore I have investigated their presence also in pollen at different time of germination to clarify the apple pollen allergenic potential. I have observed that the same four classes of allergens found in fruit are expressed at different levels also in pollen, and their presence might support that the apple pollen can be considered allergenic as the fruit, deducing that apple allergy could also be indirectly caused by sensitization to pollen. Climate changes resulting from increases in temperature and air pollution influence pollen allergenicity, responsible for the dramatic raise in respiratory allergies (hay fever, bronchial asthma, conjunctivitis). Although the link between climate change and pollen allergenicity is proven, the underlying mechanism is little understood. Transglutaminases (TGases), a class of enzymes able to post-translationally modify proteins, are activated under stress and involved in some inflammatory responses, enhancing the activity of pro-inflammatory phospholipase A2, suggesting a role in allergies. Recently, a calcium-dependent TGase activity has been identified in the pollen cell wall, raising the possibility that pollen TGase may have a role in the modification of pollen allergens reported above, thus stabilizing them against proteases. This enzyme can be involved also in the transamidation of proteins present in the human mucosa interacting with surface pollen or, finally, the enzyme itself can represent an allergen, as suggested by studies on celiac desease. I have hypothesized that this pollen enzyme can be affected by climate changes and be involved in exhacerbating allergy response. The data presented in this thesis represent a scientific basis for future development of studies devoted to verify the hypothesis set out here. First, I have demonstrated the presence of an extracellular TGase on the surface of the grain observed either at the apical or the proximal parts of the pollen-tube by laser confocal microscopy (Iorio et al., 2008), that plays an essential role in apple pollen-tube growth, as suggested by the arrest of tube elongation by TGase inhibitors, such as EGTA or R281. Its involvement in pollen tube growth is mainly confirmed by the data of activity and gene expression, because TGase showed a peak between 15 min and 30 min of germination, when this process is well established, and an optimal pH around 6.5, which is close to that recorded for the germination medium. Moreover, data show that pollen TGase can be a glycoprotein as the glycosylation profile is linked both with the activation of the enzyme and with its localization at the pollen cell wall during germination, because from the data presented seems that the active form of TGase involved in pollen tube growth and pollen-stylar interaction is more exposed and more weakly bound to the cell wall. Interestingly, TGase interacts with fibronectin (FN), a putative SAMs or psECM component, inducing possibly intracellular signal transduction during the interaction between pollen-stylar occuring in the germination process, since a protein immunorecognised by anti-FN antibody is also present in pollen, in particular at the level of pollen grain cell wall in a punctuate pattern, but also along the shank of the pollen tube wall, in a similar pattern that recalls the signal obtained with the antibody anti TGase. FN represents a good substrate for the enzyme activity, better than DMC usually used as standard substrate for animal TGase. Thus, this pollen enzyme, necessary for its germination, is exposed on the pollen surface and consequently can easily interact with mucosal proteins, as it has been found germinated pollen in studies conducted on human mucus (Forlani, personal communication). I have obtained data that TGase activity increases in a very remarkable way when pollen is exposed to stressful conditions, such as climate changes and environmental pollution. I have used two different species of pollen, an aero allergenic (hazelnut, Corylus avellana) pollen, whose allergenicity is well documented, and an enthomophylus (apple, Malus domestica) pollen, which is not yet well characterized, to compare data on their mechanism of action in response to stressors. The two pollens have been exposed to climate changes (different temperatures, relative humidity (rH), acid rain at pH 5.6 and copper pollution (3.10 µg/l)) and showed an increase in pollen surface TGase activity that is not accompanied to an induced expression of TGase immunoreactive protein with AtPNG1p. Probably, climate change induce an alteration or damage to pollen cell wall that carries the pollen grains to release their content in the medium including TGase enzyme, that can be free to carry out its function as confirmed by the immunolocalisation and by the in situ TGase activity assay data; morphological examination indicated pollen damage, viability significantly reduced and in acid rain conditions an early germination of apple pollen, thus possibly enhancing the TGase exposure on pollen surface. Several pollen proteins were post-translationally modified, as well as mammalian sPLA2 especially with Corylus pollen, which results in its activation, potentially altering pollen allergenicity and inflammation. Pollen TGase activity mimicked the behaviour of gpl TGase and AtPNG1p in the stimulation of sPLA2, even if the regulatory mechanism seems different to gpl TGase, because pollen TGase favours an intermolecular cross-linking between various molecules of sPLA2, giving rise to high-molecular protein networks normally more stable. In general, pollens exhibited a significant endogenous phospholipase activity and it has been observed differences according to the allergenic (Corylus) or not-well characterized allergenic (Malus) attitude of the pollen. However, even if with a different intensity level in activation, pollen enzyme share the ability to activate the sPLA2, thus suggesting an important regulatory role for the activation of a key enzyme of the inflammatory response, among which my interest was addressed to pollen allergy. In conclusion, from all the data presented, mainly presence of allergens, presence of an extracellular TGase, increasing in its activity following exposure to environmental pollution and PLA2 activation, I can conclude that also Malus pollen can behave as potentially allergenic. The mechanisms described here that could affect the allergenicity of pollen, maybe could be the same occurring in fruit, paving the way for future studies in the identification of hyper- and hypo- allergenic cultivars, in preventing environmental stressor effects and, possibly, in the production of transgenic plants.

Circulating Fibrocytes, their role in renal fibrosis and molecular pathways involved. Possible biomarkers of fibrogenesis in chronic kidney disease

Circulating Fibrocytes (CFs) are bone marrow-derived mesenchymal progenitor cells that express a similar pattern of surface markers related to leukocytes, hematopoietic progenitor cells and fibroblasts. CFs precursor display an ability to differentiate into fibroblasts and Myofibroblasts, as well as adipocytes. Fibrocytes have been shown to contribute to tissue fibrosis in the end-stage renal disease (ESRD), as well as in other fibrotic diseases, leading to fibrogenic process in other organs including lung, cardiac, gut and liver. This evidence has been confirmed by several experimental proofs in mice models of kidney injury. In the present study, we developed a protocol for the study of CFs, by using peripheral blood monocytes cells (PBMCs) samples collected from healthy human volunteers. Thanks to a flow cytometry method, in vitro culture assays and the gene expression assays, we are able to study and characterize this CFs population. Moreover, results confirmed that these approaches are reliable and reproducible for the investigation of the circulating fibrocytes population in whole blood samples. Our final aim is to confirm the presence of a correlation between the renal fibrosis progression, and the different circulating fibrocyte levels in Chronic Kidney Disease (CKD) patients. Thanks to a protocol study presented and accepted by the Ethic Committee we are continuing the study of CFs induction in a cohort of sixty patients affected by CKD, divided in three distinct groups for different glomerular filtration rate (GFR) levels, plus a control group of thirty healthy subjects. Ongoing experiments will determine whether circulating fibrocytes represent novel biomarkers for the study of CKD progression, in the early and late phases of this disease.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Development of processes for the valorization of lignocellulosic biomass based on renewable energies

The world grapples with climate change from fossil fuel reliance, prompting Europe to pivot to renewable energy. Among renewables, biomass is a bioenergy and bio-carbon source, used to create high-value biomolecules, replacing fossil-based products. Alkyl levulinates, derived from biomass, hold promise as bio-additives and biofuels, especially via acid solvolysis of hexose sugars, necessitating further exploration. Alkyl levulinate's potential extends to converting into γ-valerolactone (GVL), a bio-solvent produced via hydrogenation with molecular-hydrogen. Hydrogen, a key reagent and energy carrier, aids renewable energy integration. This thesis delves into a biorefinery system study, aligning with sustainability goals, integrating biomass valorization, energy production, and hydrogen generation. It investigates optimizing technologies for butyl levulinate production and subsequent GVL hydrogenation. Sustainability remains pivotal, reflecting the global shift towards renewable and carbon bio-resources. The research initially focuses on experimenting with the optimal technology for producing butyl levulinate from biomass-derived hexose fructose. It examines the solvolysis process, investigating optimal conditions, kinetic modeling, and the impact of solvents on fructose conversion. The subsequent part concentrates on the technological aspect of hydrogenating butyl levulinate into GVL. It includes conceptual design, simulation, and optimization of the fructose-to-GVL process scheme based on process intensification. In the final part, the study applies the process to a real case study in Normandy, France, adapting it to local biomass availability and wind energy. It defines a methodology for designing and integrating the energy-supply system, evaluating different scenarios. Sustainability assessment using economic, environmental, and social indicators culminates in an overall sustainability index, indicating scenarios integrating the GVL biorefinery system with wind power and hydrogen energy storage as promising due to high profitability and reduced environmental impact. Sensitivity analyses validate the methodology's reliability, potentially extending to other technological systems.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Study of Venturia inaequalis sensitivity to fungicides through molecular and biological methodologies

This study was aimed to correlate the results of relative germination from in vitro tests by trifloxystrobin with those of qPCR on a wide range of V. inaequalis populations and monoconidial isolates. Samples were collected in Italian and Turkish distinct locations from orchards with different scab management. In this study, an allele-specific qPCR with primer sets designed was successfully developed to quantitatively determine the frequency of QoI-resistant allele G143A in populations and monoconidial isolates of V. inaequalis. qPCR followed a similar pattern to that obtained using in vitro conidial germination test in very sensitive and very resistant populations. However, the variability between two test results was observed in hetereogenous populations. Therefore, the results of correlations between in vitro and qPCR showed a positive but not very high correlation for Venturia inaequalis populations (R2=0.70). On the contrary, this correlation between two assessment methods was very high for monoconidial isolates (R2=0.92). Results obtained in quantitative PCR and from traditional spore germination assay differed for the same fungal population and in some cases, it is difficult to assess the resistance in the field by only qPCR. It was concluded that it is not always possible to correlate the frequency of detection of the mutation with biological assessment. In such situations, monitoring by molecular techniques must be supported by standard in vitro resistance assessments and observation of field performance in order to have correct conclusions.

Prestazioni energetico-ambientali di sistemi cogenerativi avanzati e analisi di casi applicativi

Lo scopo di questa tesi è quello di analizzare dapprima l’impatto ambientale di tali impianti e poi analizzare il contributo effettivo che oggi la tecnologia innovativa dei cicli Rankine organici può dare nella valorizzazione elettrica del calore di scarto di processi industriali, focalizzando l’obiettivo principalmente sulle turbine a gas ed eseguendo un caso di studio in un settore ancora poco esplorato da questa tecnologia, quello Oil&Gas. Dopo aver effettuato il censimento degli impianti a fonti fossili e rinnovabili, cogenerativi e non, presenti in Emilia-Romagna, è stato sviluppato un software chiamato MiniBref che permette di simulare il funzionamento di una qualsiasi centrale termoelettrica grazie alla possibilità di combinare la tecnologia dell’impianto con il tipo di combustibile consentendo la valutazione delle emissioni inquinanti ed i potenziali di inquinamento. Successivamente verranno illustrati gli ORC, partendo dalle caratteristiche impiantistiche e termodinamiche fino ad arrivare alla scelta del fluido organico, fondamentale per le performance del ciclo. Dopo aver effettuato una ricognizione dello stato dell’arte delle applicazioni industriali degli ORC nel recupero termico, verranno eseguite simulazioni numeriche per ricostruire gli ORC ed avere una panoramica il più completa ed attendibile delle prestazioni effettive di questi sistemi. In ultimo verranno illustrati i risultati di un caso di studio che vede l’adozione di recupero mediante ciclo organico in un’installazione esistente del settore Oil&Gas. Si effettuerà uno studio delle prestazione dell’impianto al variare delle pressioni massime e minime del ciclo ed al variare del fluido impiegato al fine di mostrare come questi parametri influenzino non solo le performance ma anche le caratteristiche impiantistiche da adottare. A conclusione del lavoro si riporteranno i risultati relativi all’analisi condotte considerando l’impianto ai carichi parziali ed in assetto cogenerativo.

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

Strategies for lowering the environmental impact of different electrochemical energy storage system

The continuous growth of global population brings an exponential increase on energy consumption and greenhouse gas emission in the atmosphere contributing to the increase of the planet temperature. Therefore, it is mandatory to adopt renewable energy production systems like photovoltaic or wind power: unfortunately, the main limit of these technologies is the natural intermittence of the energy sources that limits their applicability. The key enabling technology for a widespread usage of clean power sources are electrochemical energy storage systems, most commonly known as batteries. Batteries will enable the storage of energy during overproduction period and the release during low production period stabilizing the power outcome, allowing the connection to the main grid and increasing the applicability of renewable energy sources. Despite the high number of benefits that the widespread use of batteries will bring, starting from the reduction of CO2 emitted in the atmosphere, it is necessary also to take care of the environmental impact of processes and materials used for the production of electrochemical storage systems. In addition, there are many different battery systems, with different chemistries and designs that require specific strategies. Nowadays, the most part of the materials and chemicals used for battery production are toxic for humans and the environment. For this reason, this Ph.D. thesis addresses the challenging scope of lowering the environmental impact of manufacturing processes of different electrochemical energy storage systems using natural derived or low carbon footprint materials while increasing the performances with respect to commercial devices. The activities carried out during my Ph.D. cover a high number of different electrochemical storage systems involving a wide range of electrochemical processes from capacitive to faradic. New materials, different production processes and new battery design, all in view of sustainability and low environmental impact, increased the innovative and challenging aspects of this work.

Essays On CEO Compensation: New Evidence On The Managerial-Power Vs. Optimal Contracting Debate

This dissertation analyzes the effect of market analysts’ expectations of share prices (price targets) on executive compensation. It examines how well the estimated effects of price targets on compensation fit with two competing views on determining executive compensation: the arm’s length bargaining model, which assumes that a board seeks to maximize shareholders’ interests, and the managerial power model, which assumes that a board seeks to maximize managers’ compensation (Bebchuk et al. 2005). The first chapter documents the pattern of CEO pay from fiscal year 1996 to 2010. The second chapter analyzes the Institutional Broker Estimate System Detail History Price Target data file, which that reports analysts’ price targets for firms. I show that the number of price target announcements is positively associated with company share price’s volatility, that price targets are predictive of changes in the value of stocks, and that when analysts announce positive (negative) expectations of future stock price, share prices change in the same direction in the short run. The third chapter analyzes the effect of price targets on executive compensation. I find that analysts' price targets alter the composition of executive pay between cash-based compensation and stock-based compensation. When analysts forecast a rise (fall) in the share price for a firm, the compensation package tilts toward stock-based (cash-based) compensation. The substitution effect is stronger in companies that have weaker corporate governance. The fourth chapter explores the effect of the introduction of the Sarbanes-Oxley Act (SOX) in 2002 and its reinforcement in 2006 on the options granting process. I show that the introduction of SOX and its reinforcement eliminated the practice of backdating options but increased “spring-loading” of option grants around price targets announcements. Overall, the dissertation shows that price targets provide insights into the determinants of executive pay in favor of the managerial power model.