Empirical and fundamental mechanical tests in the evaluation of dough and bread rheological properties

Bread dough and particularly wheat dough, due to its viscoelastic behaviour, is probably the most dynamic and complicated rheological system and its characteristics are very important since they highly affect final products’ textural and sensorial properties. The study of dough rheology has been a very challenging task for many researchers since it can provide numerous information about dough formulation, structure and processing. This explains why dough rheology has been a matter of investigation for several decades. In this research rheological assessment of doughs and breads was performed by using empirical and fundamental methods at both small and large deformation, in order to characterize different types of doughs and final products such as bread. In order to study the structural aspects of food products, image analysis techniques was used for the integration of the information coming from empirical and fundamental rheological measurements. Evaluation of dough properties was carried out by texture profile analysis (TPA), dough stickiness (Chen and Hoseney cell) and uniaxial extensibility determination (Kieffer test) by using a Texture Analyser; small deformation rheological measurements, were performed on a controlled stress–strain rheometer; moreover the structure of different doughs was observed by using the image analysis; while bread characteristics were studied by using texture profile analysis (TPA) and image analysis. The objective of this research was to understand if the different rheological measurements were able to characterize and differentiate the different samples analysed. This in order to investigate the effect of different formulation and processing conditions on dough and final product from a structural point of view. For this aim the following different materials were performed and analysed: - frozen dough realized without yeast; - frozen dough and bread made with frozen dough; - doughs obtained by using different fermentation method; - doughs made by Kamut® flour; - dough and bread realized with the addition of ginger powder; - final products coming from different bakeries. The influence of sub-zero storage time on non-fermented and fermented dough viscoelastic performance and on final product (bread) was evaluated by using small deformation and large deformation methods. In general, the longer the sub-zero storage time the lower the positive viscoelastic attributes. The effect of fermentation time and of different type of fermentation (straight-dough method; sponge-and-dough procedure and poolish method) on rheological properties of doughs were investigated using empirical and fundamental analysis and image analysis was used to integrate this information throughout the evaluation of the dough’s structure. The results of fundamental rheological test showed that the incorporation of sourdough (poolish method) provoked changes that were different from those seen in the others type of fermentation. The affirmative action of some ingredients (extra-virgin olive oil and a liposomic lecithin emulsifier) to improve rheological characteristics of Kamut® dough has been confirmed also when subjected to low temperatures (24 hours and 48 hours at 4°C). Small deformation oscillatory measurements and large deformation mechanical tests performed provided useful information on the rheological properties of samples realized by using different amounts of ginger powder, showing that the sample with the highest amount of ginger powder (6%) had worse rheological characteristics compared to the other samples. Moisture content, specific volume, texture and crumb grain characteristics are the major quality attributes of bread products. The different sample analyzed, “Coppia Ferrarese”, “Pane Comune Romagnolo” and “Filone Terra di San Marino”, showed a decrease of crumb moisture and an increase in hardness over the storage time. Parameters such as cohesiveness and springiness, evaluated by TPA that are indicator of quality of fresh bread, decreased during the storage. By using empirical rheological tests we found several differences among the samples, due to the different ingredients used in formulation and the different process adopted to prepare the sample, but since these products are handmade, the differences could be account as a surplus value. In conclusion small deformation (in fundamental units) and large deformation methods showed a significant role in monitoring the influence of different ingredients used in formulation, different processing and storage conditions on dough viscoelastic performance and on final product. Finally the knowledge of formulation, processing and storage conditions together with the evaluation of structural and rheological characteristics is fundamental for the study of complex matrices like bakery products, where numerous variable can influence their final quality (e.g. raw material, bread-making procedure, time and temperature of the fermentation and baking).

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.

Multiresolution spherical wavelet analysis in global seismic tomography

Every seismic event produces seismic waves which travel throughout the Earth. Seismology is the science of interpreting measurements to derive information about the structure of the Earth. Seismic tomography is the most powerful tool for determination of 3D structure of deep Earth's interiors. Tomographic models obtained at the global and regional scales are an underlying tool for determination of geodynamical state of the Earth, showing evident correlation with other geophysical and geological characteristics. The global tomographic images of the Earth can be written as a linear combinations of basis functions from a specifically chosen set, defining the model parameterization. A number of different parameterizations are commonly seen in literature: seismic velocities in the Earth have been expressed, for example, as combinations of spherical harmonics or by means of the simpler characteristic functions of discrete cells. With this work we are interested to focus our attention on this aspect, evaluating a new type of parameterization, performed by means of wavelet functions. It is known from the classical Fourier theory that a signal can be expressed as the sum of a, possibly infinite, series of sines and cosines. This sum is often referred as a Fourier expansion. The big disadvantage of a Fourier expansion is that it has only frequency resolution and no time resolution. The Wavelet Analysis (or Wavelet Transform) is probably the most recent solution to overcome the shortcomings of Fourier analysis. The fundamental idea behind this innovative analysis is to study signal according to scale. Wavelets, in fact, are mathematical functions that cut up data into different frequency components, and then study each component with resolution matched to its scale, so they are especially useful in the analysis of non stationary process that contains multi-scale features, discontinuities and sharp strike. Wavelets are essentially used in two ways when they are applied in geophysical process or signals studies: 1) as a basis for representation or characterization of process; 2) as an integration kernel for analysis to extract information about the process. These two types of applications of wavelets in geophysical field, are object of study of this work. At the beginning we use the wavelets as basis to represent and resolve the Tomographic Inverse Problem. After a briefly introduction to seismic tomography theory, we assess the power of wavelet analysis in the representation of two different type of synthetic models; then we apply it to real data, obtaining surface wave phase velocity maps and evaluating its abilities by means of comparison with an other type of parametrization (i.e., block parametrization). For the second type of wavelet application we analyze the ability of Continuous Wavelet Transform in the spectral analysis, starting again with some synthetic tests to evaluate its sensibility and capability and then apply the same analysis to real data to obtain Local Correlation Maps between different model at same depth or between different profiles of the same model.

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.

Fundamental Dimensions of Social Judgment: Sociability and Morality as Distinct Characteristics of Social Warmth

The present dissertation focuses on the two basic dimensions of social judgment, i.e., warmth and competence. Previous research has shown that warmth and competence emerge as fundamental dimensions both at the interpersonal level and at the group level. Moreover, warmth judgments appear to be primary, reflecting the importance of first assessing others’ intentions before determining the other’s ability to carry out those intentions. Finally, it has been shown that warmth and competence judgments are predicted by perceived economic competition and status, respectively (for a review, see Cuddy, Fiske, & Glick, 2008). Building on this evidence, the present work intends to further explore the role of warmth and competence in social judgment, adopting a finer-grained level of analysis. Specifically, we consider warmth to be a dimension of evaluation that encompasses two distinct characteristics (i.e., sociability and morality) rather than as an undifferentiated dimension (see Leach, Ellemers, & Barreto, 2007). In a similar vein, both economic competition and symbolic competition are taken into account (see Stephan, Ybarra, & Morrison, 2009). In order to highlight the relevance of our empirical research, the first chapter reviews the literature in social psychology that has studied the warmth and competence dimensions. In the second chapter, across two studies, we examine the role of realistic and symbolic threats (akin economic and symbolic competition, respectively) in predicting the perception of sociability and morality of social groups. In study 1, we measure perceived realistic threat, symbolic threat, sociability, and morality with respect to 8 social groups. In study 2, we manipulate the level and type of threat of a fictitious group and measure perceived sociability and morality. The findings show that realistic threat and symbolic threat are differentially related to the sociability and morality components of warmth. Specifically, whereas realistic threat seems to be a stronger predictor of sociability than symbolic threat, symbolic threat emerges as better predictor of morality than realistic threat. Thus, extending prior research, we show that the types of threat are linked to different warmth stereotypes. In the third and the fourth chapter, we examine whether the sociability and morality components of warmth play distinct roles at different stages of group impression formation. More specifically, the third chapter focuses on the information-gathering process. Two studies experimentally investigate which traits are mostly selected when forming impressions about either ingroup or outgroup members. The results clearly show that perceivers are more interested in obtaining information about morality than about sociability when asked to form a global impression about others. The fourth chapter considers more properly the formulation of an evaluative impression. Thus, in the first study participants rate real groups on sociability, morality, and competence. In the second study, participants read an immigration scenario depicting an unfamiliar social group in terms of high (vs. low) morality, sociability, and competence. In both studies, participants are also asked to report their global impression of the group. The results show that global evaluations are better predicted by morality than by sociability and competence trait ascriptions. Taken together the third and the fourth chapters show that the dominance of warmth suggested by previous studies on impression formation might be better explained in terms of a greater effect of one of the two subcomponents (i.e., morality) over the other (i.e., sociability). In the general discussion, we discuss the relevance of our findings for intergroup relation and group perception, as well as for impression formation.

Analysis of eruptive and seismic sequences to improve the short-and long-term eruption forecasting

Forecasting the time, location, nature, and scale of volcanic eruptions is one of the most urgent aspects of modern applied volcanology. The reliability of probabilistic forecasting procedures is strongly related to the reliability of the input information provided, implying objective criteria for interpreting the historical and monitoring data. For this reason both, detailed analysis of past data and more basic research into the processes of volcanism, are fundamental tasks of a continuous information-gain process; in this way the precursor events of eruptions can be better interpreted in terms of their physical meanings with correlated uncertainties. This should lead to better predictions of the nature of eruptive events. In this work we have studied different problems associated with the long- and short-term eruption forecasting assessment. First, we discuss different approaches for the analysis of the eruptive history of a volcano, most of them generally applied for long-term eruption forecasting purposes; furthermore, we present a model based on the characteristics of a Brownian passage-time process to describe recurrent eruptive activity, and apply it for long-term, time-dependent, eruption forecasting (Chapter 1). Conversely, in an effort to define further monitoring parameters as input data for short-term eruption forecasting in probabilistic models (as for example, the Bayesian Event Tree for eruption forecasting -BET_EF-), we analyze some characteristics of typical seismic activity recorded in active volcanoes; in particular, we use some methodologies that may be applied to analyze long-period (LP) events (Chapter 2) and volcano-tectonic (VT) seismic swarms (Chapter 3); our analysis in general are oriented toward the tracking of phenomena that can provide information about magmatic processes. Finally, we discuss some possible ways to integrate the results presented in Chapters 1 (for long-term EF), 2 and 3 (for short-term EF) in the BET_EF model (Chapter 4).

Biomass Gasification - Process analysis and dimensioning aspects for downdraft units and gas cleaning lines

In such territories where food production is mostly scattered in several small / medium size or even domestic farms, a lot of heterogeneous residues are produced yearly, since farmers usually carry out different activities in their properties. The amount and composition of farm residues, therefore, widely change during year, according to the single production process periodically achieved. Coupling high efficiency micro-cogeneration energy units with easy handling biomass conversion equipments, suitable to treat different materials, would provide many important advantages to the farmers and to the community as well, so that the increase in feedstock flexibility of gasification units is nowadays seen as a further paramount step towards their wide spreading in rural areas and as a real necessity for their utilization at small scale. Two main research topics were thought to be of main concern at this purpose, and they were therefore discussed in this work: the investigation of fuels properties impact on gasification process development and the technical feasibility of small scale gasification units integration with cogeneration systems. According to these two main aspects, the present work was thus divided in two main parts. The first one is focused on the biomass gasification process, that was investigated in its theoretical aspects and then analytically modelled in order to simulate thermo-chemical conversion of different biomass fuels, such as wood (park waste wood and softwood), wheat straw, sewage sludge and refuse derived fuels. The main idea is to correlate the results of reactor design procedures with the physical properties of biomasses and the corresponding working conditions of gasifiers (temperature profile, above all), in order to point out the main differences which prevent the use of the same conversion unit for different materials. At this scope, a gasification kinetic free model was initially developed in Excel sheets, considering different values of air to biomass ratio and the downdraft gasification technology as particular examined application. The differences in syngas production and working conditions (process temperatures, above all) among the considered fuels were tried to be connected to some biomass properties, such elementary composition, ash and water contents. The novelty of this analytical approach was the use of kinetic constants ratio in order to determine oxygen distribution among the different oxidation reactions (regarding volatile matter only) while equilibrium of water gas shift reaction was considered in gasification zone, by which the energy and mass balances involved in the process algorithm were linked together, as well. Moreover, the main advantage of this analytical tool is the easiness by which the input data corresponding to the particular biomass materials can be inserted into the model, so that a rapid evaluation on their own thermo-chemical conversion properties is possible to be obtained, mainly based on their chemical composition A good conformity of the model results with the other literature and experimental data was detected for almost all the considered materials (except for refuse derived fuels, because of their unfitting chemical composition with the model assumptions). Successively, a dimensioning procedure for open core downdraft gasifiers was set up, by the analysis on the fundamental thermo-physical and thermo-chemical mechanisms which are supposed to regulate the main solid conversion steps involved in the gasification process. Gasification units were schematically subdivided in four reaction zones, respectively corresponding to biomass heating, solids drying, pyrolysis and char gasification processes, and the time required for the full development of each of these steps was correlated to the kinetics rates (for pyrolysis and char gasification processes only) and to the heat and mass transfer phenomena from gas to solid phase. On the basis of this analysis and according to the kinetic free model results and biomass physical properties (particles size, above all) it was achieved that for all the considered materials char gasification step is kinetically limited and therefore temperature is the main working parameter controlling this step. Solids drying is mainly regulated by heat transfer from bulk gas to the inner layers of particles and the corresponding time especially depends on particle size. Biomass heating is almost totally achieved by the radiative heat transfer from the hot walls of reactor to the bed of material. For pyrolysis, instead, working temperature, particles size and the same nature of biomass (through its own pyrolysis heat) have all comparable weights on the process development, so that the corresponding time can be differently depending on one of these factors according to the particular fuel is gasified and the particular conditions are established inside the gasifier. The same analysis also led to the estimation of reaction zone volumes for each biomass fuel, so as a comparison among the dimensions of the differently fed gasification units was finally accomplished. Each biomass material showed a different volumes distribution, so that any dimensioned gasification unit does not seem to be suitable for more than one biomass species. Nevertheless, since reactors diameters were found out quite similar for all the examined materials, it could be envisaged to design a single units for all of them by adopting the largest diameter and by combining together the maximum heights of each reaction zone, as they were calculated for the different biomasses. A total height of gasifier as around 2400mm would be obtained in this case. Besides, by arranging air injecting nozzles at different levels along the reactor, gasification zone could be properly set up according to the particular material is in turn gasified. Finally, since gasification and pyrolysis times were found to considerably change according to even short temperature variations, it could be also envisaged to regulate air feeding rate for each gasified material (which process temperatures depend on), so as the available reactor volumes would be suitable for the complete development of solid conversion in each case, without even changing fluid dynamics behaviour of the unit as well as air/biomass ratio in noticeable measure. The second part of this work dealt with the gas cleaning systems to be adopted downstream the gasifiers in order to run high efficiency CHP units (i.e. internal engines and micro-turbines). Especially in the case multi–fuel gasifiers are assumed to be used, weightier gas cleaning lines need to be envisaged in order to reach the standard gas quality degree required to fuel cogeneration units. Indeed, as the more heterogeneous feed to the gasification unit, several contaminant species can simultaneously be present in the exit gas stream and, as a consequence, suitable gas cleaning systems have to be designed. In this work, an overall study on gas cleaning lines assessment is carried out. Differently from the other research efforts carried out in the same field, the main scope is to define general arrangements for gas cleaning lines suitable to remove several contaminants from the gas stream, independently on the feedstock material and the energy plant size The gas contaminant species taken into account in this analysis were: particulate, tars, sulphur (in H2S form), alkali metals, nitrogen (in NH3 form) and acid gases (in HCl form). For each of these species, alternative cleaning devices were designed according to three different plant sizes, respectively corresponding with 8Nm3/h, 125Nm3/h and 350Nm3/h gas flows. Their performances were examined on the basis of their optimal working conditions (efficiency, temperature and pressure drops, above all) and their own consumption of energy and materials. Successively, the designed units were combined together in different overall gas cleaning line arrangements, paths, by following some technical constraints which were mainly determined from the same performance analysis on the cleaning units and from the presumable synergic effects by contaminants on the right working of some of them (filters clogging, catalysts deactivation, etc.). One of the main issues to be stated in paths design accomplishment was the tars removal from the gas stream, preventing filters plugging and/or line pipes clogging At this scope, a catalytic tars cracking unit was envisaged as the only solution to be adopted, and, therefore, a catalytic material which is able to work at relatively low temperatures was chosen. Nevertheless, a rapid drop in tars cracking efficiency was also estimated for this same material, so that an high frequency of catalysts regeneration and a consequent relevant air consumption for this operation were calculated in all of the cases. Other difficulties had to be overcome in the abatement of alkali metals, which condense at temperatures lower than tars, but they also need to be removed in the first sections of gas cleaning line in order to avoid corrosion of materials. In this case a dry scrubber technology was envisaged, by using the same fine particles filter units and by choosing for them corrosion resistant materials, like ceramic ones. Besides these two solutions which seem to be unavoidable in gas cleaning line design, high temperature gas cleaning lines were not possible to be achieved for the two larger plant sizes, as well. Indeed, as the use of temperature control devices was precluded in the adopted design procedure, ammonia partial oxidation units (as the only considered methods for the abatement of ammonia at high temperature) were not suitable for the large scale units, because of the high increase of reactors temperature by the exothermic reactions involved in the process. In spite of these limitations, yet, overall arrangements for each considered plant size were finally designed, so that the possibility to clean the gas up to the required standard degree was technically demonstrated, even in the case several contaminants are simultaneously present in the gas stream. Moreover, all the possible paths defined for the different plant sizes were compared each others on the basis of some defined operational parameters, among which total pressure drops, total energy losses, number of units and secondary materials consumption. On the basis of this analysis, dry gas cleaning methods proved preferable to the ones including water scrubber technology in al of the cases, especially because of the high water consumption provided by water scrubber units in ammonia adsorption process. This result is yet connected to the possibility to use activated carbon units for ammonia removal and Nahcolite adsorber for chloride acid. The very high efficiency of this latter material is also remarkable. Finally, as an estimation of the overall energy loss pertaining the gas cleaning process, the total enthalpy losses estimated for the three plant sizes were compared with the respective gas streams energy contents, these latter obtained on the basis of low heating value of gas only. This overall study on gas cleaning systems is thus proposed as an analytical tool by which different gas cleaning line configurations can be evaluated, according to the particular practical application they are adopted for and the size of cogeneration unit they are connected to.

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Structural and functional analysis of centromeric chromatin

Animal neocentromeres are defined as ectopic centromeres that have formed in non-centromeric locations and avoid some of the features, like the DNA satellite sequence, that normally characterize canonical centromeres. Despite this, they are stable functional centromeres inherited through generations. The only existence of neocentromeres provide convincing evidence that centromere specification is determined by epigenetic rather than sequence-specific mechanisms. For all this reasons, we used them as simplified models to investigate the molecular mechanisms that underlay the formation and the maintenance of functional centromeres. We collected human cell lines carrying neocentromeres in different positions. To investigate the region involved in the process at the DNA sequence level we applied a recent technology that integrates Chromatin Immuno-Precipitation and DNA microarrays (ChIP-on-chip) using rabbit polyclonal antibodies directed against CENP-A or CENP-C human centromeric proteins. These DNA binding-proteins are required for kinetochore function and are exclusively targeted to functional centromeres. Thus, the immunoprecipitation of DNA bound by these proteins allows the isolation of centromeric sequences, including those of the neocentromeres. Neocentromeres arise even in protein-coding genes region. We further analyzed if the increased scaffold attachment sites and the corresponding tighter chromatin of the region involved in the neocentromerization process still were permissive or not to transcription of within encoded genes. Centromere repositioning is a phenomenon in which a neocentromere arisen without altering the gene order, followed by the inactivation of the canonical centromere, becomes fixed in population. It is a process of chromosome rearrangement fundamental in evolution, at the bases of speciation. The repeat-free region where the neocentromere initially forms, progressively acquires extended arrays of satellite tandem repeats that may contribute to its functional stability. In this view our attention focalized to the repositioned horse ECA11 centromere. ChIP-on-chip analysis was used to define the region involved and SNPs studies, mapping within the region involved into neocentromerization, were carried on. We have been able to describe the structural polymorphism of the chromosome 11 centromeric domain of Caballus population. That polymorphism was seen even between homologues chromosome of the same cells. That discovery was the first described ever. Genomic plasticity had a fundamental role in evolution. Centromeres are not static packaged region of genomes. The key question that fascinates biologists is to understand how that centromere plasticity could be combined to the stability and maintenance of centromeric function. Starting from the epigenetic point of view that underlies centromere formation, we decided to analyze the RNA content of centromeric chromatin. RNA, as well as secondary chemically modifications that involve both histones and DNA, represents a good candidate to guide somehow the centromere formation and maintenance. Many observations suggest that transcription of centromeric DNA or of other non-coding RNAs could affect centromere formation. To date has been no thorough investigation addressing the identity of the chromatin-associated RNAs (CARs) on a global scale. This prompted us to develop techniques to identify CARs in a genome-wide approach using high-throughput genomic platforms. The future goal of this study will be to focalize the attention on what strictly happens specifically inside centromere chromatin.

Genetic analysis of tumour initiation and progression in a Drosophila model of epithelial cancer

Neoplastic overgrowth depends on the cooperation of several mutations ultimately leading to major rearrangements in cellular behaviour. The molecular crosstalk occurring between precancerous and normal cells strongly influences the early steps of the tumourigenic process as well as later stages of the disease. Precancerous cells are often removed by cell death from normal tissues but the mechanisms responsible for such fundamental safeguard processes remain in part elusive. To gain insight into these phenomena I took advantage of the clonal analysis methods available in Drosophila for studying the phenotypes due to loss of function of the neoplastic tumour suppressor lethal giant larvae (lgl). I found that lgl mutant cells growing in wild-type imaginal wing discs are subject to the phenomenon of cell competition and are eliminated by JNK-dependent cell death because they express very low levels of dMyc oncoprotein compared to those in the surrounding tissue. Indeed, in non-competitive backgrounds lgl mutant clones are able to overgrow and upregulate dMyc, overwhelming the neighbouring tissue and forming tumourous masses that display several cancer hallmarks. These phenotypes are completely abolished by reducing dMyc abundance within mutant cells while increasing it in lgl clones growing in a competitive context re-establishes their tumourigenic potential. Similarly, the neoplastic growth observed upon the oncogenic cooperation between lgl mutation and activated Ras/Raf/MAPK signalling was found to be characterised by and dependent on the ability of cancerous cells to upregulate dMyc with respect to the adjacent normal tissue, through both transcriptional and post-transcriptional mechanisms, thereby confirming its key role in lgl-induced tumourigenesis. These results provide first evidence that the dMyc oncoprotein is required in lgl mutant tissue to promote invasive overgrowth in developing and adult epithelial tissues and that dMyc abundance inside versus outside lgl mutant clones plays a key role in driving neoplastic overgrowth.

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 charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

Integrated analysis and design of optimization and up-scaling of inductively coupled plasma synthesis of nanoparticles

This study is focused on radio-frequency inductively coupled thermal plasma (ICP) synthesis of nanoparticles, combining experimental and modelling approaches towards process optimization and industrial scale-up, in the framework of the FP7-NMP SIMBA European project (Scaling-up of ICP technology for continuous production of Metallic nanopowders for Battery Applications). First the state of the art of nanoparticle production through conventional and plasma routes is summarized, then results for the characterization of the plasma source and on the investigation of the nanoparticle synthesis phenomenon, aiming at highlighting fundamental process parameters while adopting a design oriented modelling approach, are presented. In particular, an energy balance of the torch and of the reaction chamber, employing a calorimetric method, is presented, while results for three- and two-dimensional modelling of an ICP system are compared with calorimetric and enthalpy probe measurements to validate the temperature field predicted by the model and used to characterize the ICP system under powder-free conditions. Moreover, results from the modeling of critical phases of ICP synthesis process, such as precursor evaporation, vapour conversion in nanoparticles and nanoparticle growth, are presented, with the aim of providing useful insights both for the design and optimization of the process and on the underlying physical phenomena. Indeed, precursor evaporation, one of the phases holding the highest impact on industrial feasibility of the process, is discussed; by employing models to describe particle trajectories and thermal histories, adapted from the ones originally developed for other plasma technologies or applications, such as DC non-transferred arc torches and powder spherodization, the evaporation of micro-sized Si solid precursor in a laboratory scale ICP system is investigated. Finally, a discussion on the role of thermo-fluid dynamic fields on nano-particle formation is presented, as well as a study on the effect of the reaction chamber geometry on produced nanoparticle characteristics and process yield.

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.

Development of new tools and devices for CMB and foreground data analysis and future experiments

The discovery of the Cosmic Microwave Background (CMB) radiation in 1965 is one of the fundamental milestones supporting the Big Bang theory. The CMB is one of the most important source of information in cosmology. The excellent accuracy of the recent CMB data of WMAP and Planck satellites confirmed the validity of the standard cosmological model and set a new challenge for the data analysis processes and their interpretation. In this thesis we deal with several aspects and useful tools of the data analysis. We focus on their optimization in order to have a complete exploitation of the Planck data and contribute to the final published results. The issues investigated are: the change of coordinates of CMB maps using the HEALPix package, the problem of the aliasing effect in the generation of low resolution maps, the comparison of the Angular Power Spectrum (APS) extraction performances of the optimal QML method, implemented in the code called BolPol, and the pseudo-Cl method, implemented in Cromaster. The QML method has been then applied to the Planck data at large angular scales to extract the CMB APS. The same method has been applied also to analyze the TT parity and the Low Variance anomalies in the Planck maps, showing a consistent deviation from the standard cosmological model, the possible origins for this results have been discussed. The Cromaster code instead has been applied to the 408 MHz and 1.42 GHz surveys focusing on the analysis of the APS of selected regions of the synchrotron emission. The new generation of CMB experiments will be dedicated to polarization measurements, for which are necessary high accuracy devices for separating the polarizations. Here a new technology, called Photonic Crystals, is exploited to develop a new polarization splitter device and its performances are compared to the devices used nowadays.