44 resultados para Advanced characterization methods
Resumo:
The increase in environmental and healthy concerns, combined with the possibility to exploit waste as a valuable energy resource, has led to explore alternative methods for waste final disposal. In this context, the energy conversion of Municipal Solid Waste (MSW) in Waste-To-Energy (WTE) power plant is increasing throughout Europe, both in terms of plants number and capacity, furthered by legislative directives. Due to the heterogeneous nature of waste, some differences with respect to a conventional fossil fuel power plant have to be considered in the energy conversion process. In fact, as a consequence of the well-known corrosion problems, the thermodynamic efficiency of WTE power plants typically ranging in the interval 25% ÷ 30%. The new Waste Framework Directive 2008/98/EC promotes production of energy from waste introducing an energy efficiency criteria (the so-called “R1 formula”) to evaluate plant recovery status. The aim of the Directive is to drive WTE facilities to maximize energy recovery and utilization of waste heat, in order to substitute energy produced with conventional fossil fuels fired power plants. This calls for novel approaches and possibilities to maximize the conversion of MSW into energy. In particular, the idea of an integrated configuration made up of a WTE and a Gas Turbine (GT) originates, driven by the desire to eliminate or, at least, mitigate limitations affecting the WTE conversion process bounding the thermodynamic efficiency of the cycle. The aim of this Ph.D thesis is to investigate, from a thermodynamic point of view, the integrated WTE-GT system sharing the steam cycle, sharing the flue gas paths or combining both ways. The carried out analysis investigates and defines the logic governing plants match in terms of steam production and steam turbine power output as function of the thermal powers introduced.
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Background. Human small cell lung cancer (SCLC) accounting for approximately 15-20% of all lung cancers, is an aggressive tumor with high propensity for early regional and distant metastases. Although the initial tumor rate response to chemotherapy is very high, SCLC relapses after approximately 4 months in ED and 12 months in LD. Basal cell carcinoma (BCC) is the most prevalent cancer in the western world, and its incidence is increasing worldwide. This type of cancer rarely metastasizes and the death rate is extraordinary low. Surgery is curative for most of the patients, but for those that develop locally advanced or metastatic BCC there is currently no effective treatment. Both types of cancer have been deeply investigated and genetic alterations, MYCN amplification (MA) among the most interesting, have been found. These could become targets of new pharmacological therapies. Procedures. We created and characterized novel BLI xenograft orthotopic mouse models of SCLC to evaluate the tumor onset and progression and the efficacy of new pharmacological strategies. We compared an in vitro model with a transgenic mouse model of BCC, to investigate and delineate the canonical HH signalling pathway and its connections with other molecular pathways. Results and conclusions. The orthotopic models showed latency and progression patterns similar to human disease. Chemotherapy treatments improved survival rates and validated the in vivo model. The presence of MA and overexpression were confirmed in each model and we tested the efficacy of a new MYCN inhibitor in vitro. Preliminar data of BCC models highlighted Hedgehog pathway role and underlined the importance of both in vitro and in vivo strategies to achieve a better understanding of the pathology and to evaluate the applicability of new therapeutic compounds
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The research field of the Thesis is the evaluation of motor variability and the analysis of motor stability for the assessment of fall risk. Since many falls occur during walking, a better understanding of motor stability could lead to the definition of a reliable fall risk index aiming at measuring and assessing the risk of fall in the elderly, in the attempt to prevent traumatic events. Several motor variability and stability measures are proposed in the literature, but still a proper methodological characterization is lacking. Moreover, the relationship between many of these measures and fall history or fall risk is still unknown, or not completely clear. The aim of this thesis is hence to: i) analyze the influence of experimental implementation parameters on variability/stability measures and understand how variations in these parameters affect the outputs; ii) assess the relationship between variability/stability measures and long- short-term fall history. Several implementation issues have been addressed. Following the need for a methodological standardization of gait variability/stability measures, highlighted in particular for orbital stability analysis through a systematic review, general indications about implementation of orbital stability analysis have been showed, together with an analysis of the number of strides and the test-retest reliability of several variability/stability numbers. Indications about the influence of directional changes on measures have been provided. The association between measures and long/short-term fall history has also been assessed. Of all the analyzed variability/stability measures, Multiscale entropy and Recurrence quantification analysis demonstrated particularly good results in terms of reliability, applicability and association with fall history. Therefore, these measures should be taken in consideration for the definition of a fall risk index.
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The brown rot fungi belong to a group of fungal pathogens that causes considerable damage to cultivated fruits trees, particularly stone fruits and apples in the temperate regions of the World and during the postharvest with an important economic impact. In particular in Italy, it is important to monitor the Monilinia population to control economic losses associated to the peach and nectarine market. This motivates the research steps presented in this dissertation on Monilinia Italian isolates. The Monilinia species collected from stone fruits have been identified using molecular analysis based on specific primers. The relevant role of M. fructicola was confirmed and, for the first time, it was found also on apple fruits. To avoid the development of resistant strains and implement valid treatment strategies, the understanding of the fruit natural resistance during different developmental stages and the assessment of the Monilinia sensitivity/resistance to fungicides are required. The relationship between the inhibition spots and the phenolic compounds in peach fruit peel was highlighted in this research. Three methods were used to assess isolate resistance/sensitivity, the amended medium, the Spiral Gradient Endpoint Method (SGD) and the Alamar Blue method. The PCR was used to find possible mutation points in the b-tubulin gene that is responsible for fungicide resistance. Interestingly, no mutation points were observed in resistant M. laxa isolates, suggesting that the resistance could be stimulated by environmental factors. This lead to the study of the effect of the temperature on the resistance and the preliminary results of in vitro tests showed that maximum inhibition was observed at 30°C.
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A first phase of the research activity has been related to the study of the state of art of the infrastructures for cycling, bicycle use and methods for evaluation. In this part, the candidate has studied the "bicycle system" in countries with high bicycle use and in particular in the Netherlands. Has been carried out an evaluation of the questionnaires of the survey conducted within the European project BICY on mobility in general in 13 cities of the participating countries. The questionnaire was designed, tested and implemented, and was later validated by a test in Bologna. The results were corrected with information on demographic situation and compared with official data. The cycling infrastructure analysis was conducted on the basis of information from the OpenStreetMap database. The activity consisted in programming algorithms in Python that allow to extract data from the database infrastructure for a region, to sort and filter cycling infrastructure calculating some attributes, such as the length of the arcs paths. The results obtained were compared with official data where available. The structure of the thesis is as follows: 1. Introduction: description of the state of cycling in several advanced countries, description of methods of analysis and their importance to implement appropriate policies for cycling. Supply and demand of bicycle infrastructures. 2. Survey on mobility: it gives details of the investigation developed and the method of evaluation. The results obtained are presented and compared with official data. 3. Analysis cycling infrastructure based on information from the database of OpenStreetMap: describes the methods and algorithms developed during the PhD. The results obtained by the algorithms are compared with official data. 4. Discussion: The above results are discussed and compared. In particular the cycle demand is compared with the length of cycle networks within a city. 5. Conclusions
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Most of the problems in modern structural design can be described with a set of equation; solutions of these mathematical models can lead the engineer and designer to get info during the design stage. The same holds true for physical-chemistry; this branch of chemistry uses mathematics and physics in order to explain real chemical phenomena. In this work two extremely different chemical processes will be studied; the dynamic of an artificial molecular motor and the generation and propagation of the nervous signals between excitable cells and tissues like neurons and axons. These two processes, in spite of their chemical and physical differences, can be both described successfully by partial differential equations, that are, respectively the Fokker-Planck equation and the Hodgkin and Huxley model. With the aid of an advanced engineering software these two processes have been modeled and simulated in order to extract a lot of physical informations about them and to predict a lot of properties that can be, in future, extremely useful during the design stage of both molecular motors and devices which rely their actions on the nervous communications between active fibres.
Resumo:
The specific energy of lithium-ion batteries (LIBs) is today 200 Wh/kg, a value not sufficient to power fully electric vehicles with a driving range of 400 km which requires a battery pack of 90 kWh. To deliver such energy the battery weight should be higher than 400 kg and the corresponding increase of vehicle mass would narrow the driving range to 280 km. Two main strategies are pursued to improve the energy of the rechargeable lithium batteries up to the transportation targets. The first is the increase of LIBs working voltage by using high-voltage cathode materials. The second is the increase of battery capacity by the development of a cell chemistry where oxygen redox reaction (ORR) occurs at the cathode and metal lithium is the anode (Li/O2 battery). This PhD work is focused on the development of high-voltage safe cathodes for LIBs, and on the investigation of the feasibility of Li/O2 battery operating with ionic liquid(IL)-based electrolytes. The use of LiMn1-xFexPO4 as high-voltage cathode material is discussed. Synthesis and electrochemical tests of three different phosphates, more safe cathode materials than transition metal oxides, are reported. The feasibility of Li/O2 battery operating in IL-based electrolytes is also discussed. Three aspects have been investigated: basic aspects of ORR, synthesis and characterization of porous carbons as positive electrode materials and study of limiting factors to the electrode capacity and cycle-life. Regarding LIBs, the findings on LiMnPO4 prepared by soluble precursors demonstrate that a good performing Mn-based olivine is viable without the coexistence of iron. Regarding Li/O2 battery, the oxygen diffusion coefficient and concentration values in different ILs were obtained. This work highlighted that the O2 mass transport limits the Li/O2 capacity at high currents; it gave indications on how to increase battery capacity by using a flow-cell and a porous carbon as cathode.
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The main aim of this work was the synthesis and applications of functionalized-silica-supported gold nanoparticles. The silica-anchored functionalities employed, e.g. amine, alkynyl carbamate and sulfide moieties, possess a notable affinity with gold, so that they could be able to capture the gold precursor, to spontaneously reduce it (possibly at room temperature), and to stabilize the resulting gold nanoparticles. These new materials, potentially suitable for heterogeneous catalysis applications, could represent a breakthrough among the “green” synthesis of supported gold nanoparticles, since they would circumvent the addition of extra reducing agent and stabilizers, also allowing concomitant absorption of the active catalyst particles on the support immediately after spontaneous formation of gold nanoparticles. In chapter 4 of this thesis is also presented the work developed during a seven-months Marco Polo fellowship stay at the University of Lille (France), regarding nanoparticles nucleation and growth inside a microfluidic system and the study of the corresponding mechanism by in situ XANES spectroscopy. Finally, studies regarding the reparation and reactivity of gold decorated nanodiamonds are also described. Various methods of characterization have been used, such as ultraviolet-visible spectroscopy (UV-Vis), Transmission Electron Microscopy (TEM), Dynamic Light Scattering (DLS), X-ray Fluorescence (XRF), Field Emission Gun Scanning Electron Microscopy (SEM-FEG), X-ray Photoionization (XPS), X ray Absorption Spectroscopy (XAS).
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Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.
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In this thesis the potential risks associated to the application of biochar in soil as well the stability of biochar were investigated. The study was focused on the potential risks arising from the occurrence of polycyclic aromatic hydrocarbons (PAHs) in biochar. An analytical method was developed for the determination of the 16 USEPA-PAHs in the original biochar and soil containing biochar. The method was successfully validated with a certified reference material for the soil matrix and compared with methods in use in other laboratories during a laboratory exercise within the EU-COST TD1107. The concentration of 16 USEPA-PAHs along with the 15 EU-PAHs, priority hazardous substances in food, was determined in a suite of currently available biochars for agricultural field applications derived from a variety of parent materials and pyrolysis conditions. Biochars analyzed contained the USEPA and some of the EU-PAHs at detectable levels ranging from 1.2 to 19 µg g-1. This method allowed investigating changes in PAH content and distribution in a four years study following biochar addition in soils in a vineyard (CNR-IBIMET). The results showed that biochar addition determined an increase of the amount of PAHs. However, the levels of PAHs in the soil remained within the maximum acceptable concentration for European countries. The vineyard soil performed by CNR-IBIMET was exploited to study the environmental stability of biochar and its impact on soil organic carbon. The stability of biochar was investigated by analytical pyrolysis (Py-GC-MS) and pyrolysis in the presence of hydrogen (HyPy). The findings showed that biochar amendment significantly influence soil stable carbon fraction concentration during the incubation period. Moreover, HyPy and Py-GC-MS were applied to biochars deriving from three different feedstock at two different pyrolysis temperatures. The results evidenced the influence of feedstock type and pyrolysis conditions on the degree of carbonisation.
Resumo:
This doctorate was funded by the Regione Emilia Romagna, within a Spinner PhD project coordinated by the University of Parma, and involving the universities of Bologna, Ferrara and Modena. The aim of the project was: - Production of polymorphs, solvates, hydrates and co-crystals of active pharmaceutical ingredients (APIs) and agrochemicals with green chemistry methods; - Optimization of molecular and crystalline forms of APIs and pesticides in relation to activity, bioavailability and patentability. In the last decades, a growing interest in the solid-state properties of drugs in addition to their solution chemistry has blossomed. The achievement of the desired and/or the more stable polymorph during the production process can be a challenge for the industry. The study of crystalline forms could be a valuable step to produce new polymorphs and/or co-crystals with better physical-chemical properties such as solubility, permeability, thermal stability, habit, bulk density, compressibility, friability, hygroscopicity and dissolution rate in order to have potential industrial applications. Selected APIs (active pharmaceutical ingredients) were studied and their relationship between crystal structure and properties investigated, both in the solid state and in solution. Polymorph screening and synthesis of solvates and molecular/ionic co-crystals were performed according to green chemistry principles. Part of this project was developed in collaboration with chemical/pharmaceutical companies such as BASF (Germany) and UCB (Belgium). We focused on on the optimization of conditions and parameters of crystallization processes (additives, concentration, temperature), and on the synthesis and characterization of ionic co-crystals. Moreover, during a four-months research period in the laboratories of Professor Nair Rodriguez-Hormedo (University of Michigan), the stability in aqueous solution at the equilibrium of ionic co-crystals (ICCs) of the API piracetam was investigated, to understand the relationship between their solid-state and solution properties, in view of future design of new crystalline drugs with predefined solid and solution properties.
Resumo:
Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.
Resumo:
The thesis is divided in three chapters, each one covering one topic. Initially, the thermo-mechanical and impact properties of materials used for back protectors have been analysed. Dynamical mechanical analysis (DMTA) has shown that materials used for soft-shell protectors present frequency-sensitive properties. Furthermore, through impact tests, the shock absorbing characteristics of the materials have been investigated proving the differences between soft and hard-shell protectors; moreover it has been demonstrated that the materials used for soft-shell protectors maintain their protective properties after multi-impacts. The second chapter covers the effect of the visco-elastic properties of the thermoplastic polymers on the flexural and rebound behaviours of ski boots. DMTA analysis on the materials and flexural and rebound testing on the boots have been performed. A comparison of the results highlighted a correlation between the visco-elastic properties and the flexural and rebound behaviour of ski boots. The same experimental methods have been used to investigate the influence of the design on the flexural and rebound behaviours. Finally in the third chapter the thermoplastic materials employed for the construction of ski boots soles have been characterized in terms of chemical composition, hardness, crystallinity, surface roughness and coefficient of friction (COF). The results showed a relation between material hardness and grip, in particular softer materials provide more grip with respect to harder materials. On the contrary, the surface roughness has a negative effect on friction because of the decrease in contact area. The measure of grip on inclined wet surfaces showed again a relation between hardness and grip. The performance ranking of the different materials has been the same for the COF and for the slip angle tests, indicating that COF can be used as a parameter for the choice of the optimal material to be used for the soles of ski boots.
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In this thesis, new advances in the development of spectroscopic based methods for the characterization of heritage materials have been achieved. As concern FTIR spectroscopy new approaches aimed at exploiting near and far IR region for the characterization of inorganic or organic materials have been tested. Paint cross-section have been analysed by FTIR spectroscopy in the NIR range and an “ad hoc” chemometric approach has been developed for the elaboration of hyperspectral maps. Moreover, a new method for the characterization of calcite based on the use of grinding curves has been set up both in MIR and in FAR region. Indeed, calcite is a material widely applied in cultural heritage, and this spectroscopic approach is an efficient and rapid tool to distinguish between different calcite samples. Different enhanced vibrational techniques for the characterisation of dyed fibres have been tested. First a SEIRA (Surface Enhanced Infra-Red Absorption) protocol has been optimised allowing the analysis of colorant micro-extracts thanks to the enhancement produced by the addition of gold nanoparticles. These preliminary studies permitted to identify a new enhanced FTIR method, named ATR/RAIRS, which allowed to reach lower detection limits. Regarding Raman microscopy, the research followed two lines, which have in common the aim of avoiding the use of colloidal solutions. AgI based supports obtained after deposition on a gold-coated glass slides have been developed and tested spotting colorant solutions. A SERS spectrum can be obtained thanks to the photoreduction, which the laser may induce on the silver salt. Moreover, these supports can be used for the TLC separation of a mixture of colorants and the analyses by means of both Raman/SERS and ATR-RAIRS can be successfully reached. Finally, a photoreduction method for the “on fiber” analysis of colorant without the need of any extraction have been optimised.