11 resultados para Interaction process

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The impact of plasma technologies is growing both in the academic and in the industrial fields. Nowadays, a great interest is focused in plasma applications in aeronautics and astronautics domains. Plasma actuators based on the Magneto-Hydro-Dynamic (MHD) and Electro- Hydro-Dynamic (EHD) interactions are potentially able to suitably modify the fluid-dynamics characteristics around a flying body without utilizing moving parts. This could lead to the control of an aircraft with negligible response time, more reliability and improvements of the performance. In order to study the aforementioned interactions, a series of experiments and a wide number of diagnostic techniques have been utilized. The EHD interaction, realized by means of a Dielectric Barrier Discharge (DBD) actuator, and its impact on the boundary layer have been evaluated by means of two different experiments. In the first one a three phase multi-electrode flat panel actuator is used. Different external flow velocities (from 1 to 20m/s) and different values of the supplied voltage and frequency have been considered. Moreover a change of the phase sequence has been done to verify the influence of the electric field existing between successive phases. Measurements of the induced speed had shown the effect of the supply voltage and the frequency, and the phase order in the momentum transfer phenomenon. Gains in velocity, inside the boundary layer, of about 5m/s have been obtained. Spectroscopic measurements allowed to determine the rotational and the vibrational temperature of the plasma which lie in the range of 320 ÷ 440°K and of 3000 ÷ 3900°K respectively. A deviation from thermodynamic equilibrium had been found. The second EHD experiment is realized on a single electrode pair DBD actuator driven by nano-pulses superimposed to a DC or an AC bias. This new supply system separates the plasma formation mechanism from the acceleration action on the fluid, leading to an higher degree of the control of the process. Both the voltage and the frequency of the nano-pulses and the amplitude and the waveform of the bias have been varied during the experiment. Plasma jets and vortex behavior had been observed by means of fast Schlieren imaging. This allowed a deeper understanding of the EHD interaction process. A velocity increase in the boundary layer of about 2m/s had been measured. Thrust measurements have been performed by means of a scales and compared with experimental data reported in the literature. For similar voltage amplitudes thrust larger than those of the literature, had been observed. Surface charge measurements led to realize a modified DBD actuator able to obtain similar performances when compared with that of other experiments. However in this case a DC bias replacing the AC bias had been used. MHD interaction experiments had been carried out in a hypersonic wind tunnel in argon with a flow of Mach 6. Before the MHD experiments a thermal, fluid-dynamic and plasma characterization of the hypersonic argon plasma flow have been done. The electron temperature and the electron number density had been determined by means of emission spectroscopy and microwave absorption measurements. A deviation from thermodynamic equilibrium had been observed. The electron number density showed to be frozen at the stagnation region condition in the expansion through the nozzle. MHD experiments have been performed using two axial symmetric test bodies. Similar magnetic configurations were used. Permanent magnets inserted into the test body allowed to generate inside the plasma azimuthal currents around the conical shape of the body. These Faraday currents are responsible of the MHD body force which acts against the flow. The MHD interaction process has been observed by means of fast imaging, pressure and electrical measurements. Images showed bright rings due to the Faraday currents heating and exciting the plasma particles. Pressure measurements showed increases of the pressure in the regions where the MHD interaction is large. The pressure is 10 to 15% larger than when the MHD interaction process is silent. Finally by means of electrostatic probes mounted flush on the test body lateral surface Hall fields of about 500V/m had been measured. These results have been used for the validation of a numerical MHD code.

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Bifidobacterium is an important genus of the human gastrointestinal microbiota, affecting several host physiological features. Despite the numerous Bifidobacterium related health-promoting activities, there is still a dearth of information about the molecular mechanisms at the basis of the interaction between this microorganism and the host. Bacterial surface associated proteins may play an important role in this interaction because of their ability to intervene with host molecules, as recently reported for the host protein plasminogen. Plasminogen is the zymogen of the trypsin-like serine protease plasmin, an enzyme with a broad substrate specificity. Aim of this thesis is to deepen the knowledge about the interaction between Bifidobacterium and the human plasminogen system and its role in the Bifidobacterium-host interaction process. As a bifidobacterial model, B. animalis subsp. lactis BI07 has been used because of its large usage in dairy and pharmaceutical preparations. We started from the molecular characterization of the interaction between plasminogen and one bifidobacterial plasminogen receptor, DnaK, a cell wall protein showing high affinity for plasminogen, and went on with the study of the impact of intestinal environmental factors, such as bile salts and inflammation, on the plasminogen-mediated Bifidobacterium-host interaction. According to our in vitro findings, by enhancing the activation of the bifidobacterial bound plasminogen to plasmin, the host inflammatory response results in the decrease of the bifidobacterial adhesion to the host enterocytes, favouring bacterial migration to the luminal compartment. Conversely, in the absence of inflammation, plasminogen acts as a molecular bridge between host enterocytes and bifidobacteria, enhancing Bifidobacterium adhesion. Furthermore, adaptation to physiological concentrations of bile salts enhances the capability of this microorganism to interact with the host plasminogen system. The host plasminogen system thus represents an important and flexible tool used by bifidobacteria in the cross-talk with the host.

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This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

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Nowadays the development of new Internal Combustion Engines is mainly driven by the need to reduce tailpipe emissions of pollutants, Green-House Gases and avoid the fossil fuels wasting. The design of dimension and shape of the combustion chamber together with the implementation of different injection strategies e.g., injection timing, spray targeting, higher injection pressure, play a key role in the accomplishment of the aforementioned targets. As far as the match between the fuel injection and evaporation and the combustion chamber shape is concerned, the assessment of the interaction between the liquid fuel spray and the engine walls in gasoline direct injection engines is crucial. The use of numerical simulations is an acknowledged technique to support the study of new technological solutions such as the design of new gasoline blends and of tailored injection strategies to pursue the target mixture formation. The current simulation framework lacks a well-defined best practice for the liquid fuel spray interaction simulation, which is a complex multi-physics problem. This thesis deals with the development of robust methodologies to approach the numerical simulation of the liquid fuel spray interaction with walls and lubricants. The accomplishment of this task was divided into three tasks: i) setup and validation of spray-wall impingement three-dimensional CFD spray simulations; ii) development of a one-dimensional model describing the liquid fuel – lubricant oil interaction; iii) development of a machine learning based algorithm aimed to define which mixture of known pure components mimics the physical behaviour of the real gasoline for the simulation of the liquid fuel spray interaction.

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The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

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This thesis analyses problems related to the applicability, in business environments, of Process Mining tools and techniques. The first contribution is a presentation of the state of the art of Process Mining and a characterization of companies, in terms of their "process awareness". The work continues identifying circumstance where problems can emerge: data preparation; actual mining; and results interpretation. Other problems are the configuration of parameters by not-expert users and computational complexity. We concentrate on two possible scenarios: "batch" and "on-line" Process Mining. Concerning the batch Process Mining, we first investigated the data preparation problem and we proposed a solution for the identification of the "case-ids" whenever this field is not explicitly indicated. After that, we concentrated on problems at mining time and we propose the generalization of a well-known control-flow discovery algorithm in order to exploit non instantaneous events. The usage of interval-based recording leads to an important improvement of performance. Later on, we report our work on the parameters configuration for not-expert users. We present two approaches to select the "best" parameters configuration: one is completely autonomous; the other requires human interaction to navigate a hierarchy of candidate models. Concerning the data interpretation and results evaluation, we propose two metrics: a model-to-model and a model-to-log. Finally, we present an automatic approach for the extension of a control-flow model with social information, in order to simplify the analysis of these perspectives. The second part of this thesis deals with control-flow discovery algorithms in on-line settings. We propose a formal definition of the problem, and two baseline approaches. The actual mining algorithms proposed are two: the first is the adaptation, to the control-flow discovery problem, of a frequency counting algorithm; the second constitutes a framework of models which can be used for different kinds of streams (stationary versus evolving).

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Urease is a nickel-dependent enzyme that catalyzes hydrolysis of urea in the last step of organic nitrogen mineralization. Its active site contains a dinuclear center for Ni(II) ions that must be inserted into the apo-enzyme through the action of four accessory proteins (UreD, UreE, UreF, UreG) leading to activation of urease. UreE, acting as a metallo-chaperone, delivers Ni(II) to the preformed complex of apo-urease-UreDFG and has the capability to enhance the GTPase activity of UreG. This study, focused on characterization of UreE from Sporosarcina pasteurii (SpUreE), represents a piece of information on the structure/mobility-function relationships that control nickel binding by SpUreE and its interaction with SpUreG. A calorimetric analysis revealed the occurrence of a binding event between these proteins with positive cooperativity and a stoichiometry consistent with the formation of the (UreE)2-(UreG)2 hetero-oligomer complex. Chemical Shift Perturbations induced by the protein-protein interaction were analyzed using high-resolution NMR spectroscopy, which allowed to characterize the molecular details of the protein surface of SpUreE involved in the complex formation with SpUreG. Moreover, backbone dynamic properties of SpUreE, determined using 15N relaxation analysis, revealed a general mobility in the nanoseconds time-scale, with the fastest motions observed at the C-termini. The latter analysis made it possible for the first time to characterize of the C-terminal portions, known to contain key residues for metal ion binding, that were not observed in the crystal structure of UreE because of disorder. The residues belonging to this portion of SpUreE feature large CSPs upon addition of SpUreG, showing that their chemical environment is directly affected by protein-protein interaction. Metal ion selectivity and affinity of SpUreE for cognate Ni(II) and non cognate Zn(II) metal ions were determined, and the ability of the protein to select Ni(II) over Zn(II), in consistency with the proposed role in Ni(II) cations transport, was established.

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Maleic anhydride is an important chemical intermediate mainly produced by the selective oxidation of n-butane, an industrial process catalyzed by vanadyl pyrophosphate-based materials, (VO)2P2O7. The first topic was investigated in collaboration with a company specialized in the production of organic anhydrides (Polynt SpA), with the aim of improving the performance of the process for the selective oxidation of n-butane to maleic anhydride, comparing the behavior of an industrial vanadyl pyrophosphate catalysts when utilized either in the industrial plant or in lab-scale reactor. The study was focused on how the catalyst characteristics and reactivity are affected by the reaction conditions and how the addition of a dopant can enhance the catalytic performance. Moreover, the ageing of the catalyst was studied, in order to correlate the deactivation process with the modifications occurring in the catalyst. The second topic was produced within the Seventh Framework (FP7) European Project “EuroBioRef”. The study was focused on a new route for the synthesis of maleic anhydride starting from an alternative reactant produced by fermentation of biomass:“bio-1-butanol”. In this field, the different possible catalytic configurations were investigated: the process was divided into two main reactions, the dehydration of 1-butanol to butenes and the selective oxidation of butenes to maleic anhydride. The features needed to catalyze the two steps were analyzed and different materials were proposed as catalysts, namely Keggin-type polyoxometalates, VOPO4∙2H2O and (VO)2P2O7. The reactivity of 1-butanol was tested under different conditions, in order to optimize the performance and understand the nature of the interaction between the alcohol and the catalyst surface. Then, the key intermediates in the mechanism of 1-butanol oxidehydration to MA were studied, with the aim of understanding the possible reaction mechanism. Lastly, the reactivity of the chemically sourced 1-butanol was compared with that one of different types of bio-butanols produced by biomass fermentation.

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This work illustrates a soil-tunnel-structure interaction study performed by an integrated,geotechnical and structural,approach based on 3D finite element analyses and validated against experimental observations.The study aims at analysing the response of reinforced concrete framed buildings on discrete foundations in interaction with metro lines.It refers to the case of the twin tunnels of the Milan (Italy) metro line 5,recently built in coarse grained materials using EPB machines,for which subsidence measurements collected along ground and building sections during tunnelling were available.Settlements measured under freefield conditions are firstly back interpreted using Gaussian empirical predictions. Then,the in situ measurements’ analysis is extended to include the evolving response of a 9 storey reinforced concrete building while being undercrossed by the metro line.In the finite element study,the soil mechanical behaviour is described using an advanced constitutive model. This latter,when combined with a proper simulation of the excavation process, proves to realistically reproduce the subsidence profiles under free field conditions and to capture the interaction phenomena occurring between the twin tunnels during the excavation. Furthermore, when the numerical model is extended to include the building, schematised in a detailed manner, the results are in good agreement with the monitoring data for different stages of the twin tunnelling. Thus, they indirectly confirm the satisfactory performance of the adopted numerical approach which also allows a direct evaluation of the structural response as an outcome of the analysis. Further analyses are also carried out modelling the building with different levels of detail. The results highlight that, in this case, the simplified approach based on the equivalent plate schematisation is inadequate to capture the real tunnelling induced displacement field. The overall behaviour of the system proves to be mainly influenced by the buried portion of the building which plays an essential role in the interaction mechanism, due to its high stiffness.

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This research project is based on the Multimodal Corpus of Chinese Court Interpreting (MUCCCI [mutʃɪ]), a small-scale multimodal corpus on the basis of eight authentic court hearings with Chinese-English interpreting in Mainland China. The corpus has approximately 92,500 word tokens in total. Besides the transcription of linguistic and para-linguistic features, utilizing the facial expression classification rules suggested by Black and Yacoob (1995), MUCCCI also includes approximately 1,200 annotations of facial expressions linked to the six basic types of human emotions, namely, anger, disgust, happiness, surprise, sadness, and fear (Black & Yacoob, 1995). This thesis is an example of conducting qualitative analysis on interpreter-mediated courtroom interactions through a multimodal corpus. In particular, miscommunication events (MEs) and the reasons behind them were investigated in detail. During the analysis, although queries were conducted based on non-verbal annotations when searching for MEs, both verbal and non-verbal features were considered indispensable parts contributing to the entire context. This thesis also includes a detailed description of the compilation process of MUCCCI utilizing ELAN, from data collection to transcription, POS tagging and non-verbal annotation. The research aims at assessing the possibility and feasibility of conducting qualitative analysis through a multimodal corpus of court interpreting. The concept of integrating both verbal and non-verbal features to contribute to the entire context is emphasized. The qualitative analysis focusing on MEs can provide an inspiration for improving court interpreters’ performances. All the constraints and difficulties presented can be regarded as a reference for similar research in the future.

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Different kinds of lesions can occur to DNA, and among them, one of the most dangerous is the double strand breaks (DSBs). Actually, DSBs can result in mutations, chromosome translocation or deletion. For this kind of lesions, depending on cell cycle phase as well as DNA-end resection, cells have developed specific repair pathways. Among these the error-free homologous recombination (HR) plays a crucial role. HR takes place during S/G2 phases, since the sister chromatids can be used as homologous templates. In this process, hRAD51 and BRCA2 are key players. hRAD51 is a recombinase of 339 amino-acids highly conserved through evolution which displays an intrinsic tendency to form oligomeric structures. BRCA2 is a very large protein of 3418 amino-acids, essential for the recruitment and accumulation of hRAD51 in the nucleus repairing-foci. BRCA2 interacts with hRAD51 through eight, so-called, BRC repeats, composed of 35-40 amino-acids. Mutations within this region have been linked to an increased risk of ovarian cancer development. In particular, several reports highlighted that missense mutations within one BRC repeat can hamper BRCA2 activity. Considering the close homology between the BRC repeats, it is striking how these mutations cannot be counterbalanced by the other non-mutated repeats preserving the function and the interactions of BRCA2 with hRAD51. To date the only interaction that has been structurally elucidated, is the one taking place amid the fourth BRC repeat and hRAD51. Only very little biophysical information is available on the interaction of the other BRC repeats with hRAD51. This thesis aims at elucidating the mechanism of hRAD51-BRCA2 interaction, by means of biophysical and structural approaches.