13 resultados para laboratory data
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.
Resumo:
The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.
Resumo:
Background: The natural history of Myotonic Dystrophy type 1 is largely unclear, longitudinal studies are lacking. Objectives: to collect clinical and laboratory data, to evaluate sleep disorders, somatic and autonomic skin fibres, neuropsychological and neuroradiological aspects in DM1 patients. Methods: 72 DM1 patients underwent a standardized clinical and neuroradiological evaluation performed by a multidisciplinary team during 3 years of follow-up. Results: longer disease duration was associated with higher incidence of conduction disorders and lower ejection fraction; higher CVF values were predictors for a reduced risk of cardiopathy. Lower functional pulmonary values were associated with class of expansion and were negatively associated with disease duration; arterial blood gas parameters were not associated with expansion size, disease duration nor with respiratory function test. Excessive daytime sleepiness was not associated with class of expansion nor with any of the clinical parameters examined. We detected apnoea in a large percentage of patients, without differences between the 3 genetic classes; higher CVF values were predictors for a reduced risk of apnoea. Skin biopsies demonstrated the presence of a subclinical small fibre neuropathy with involvement of the somatic fibres. The pupillometry study showed lower pupil size at baseline and a lower constriction response to light. The most affected neuropsychological domains were executive functions, visuoconstructional, attention and visuospatial tasks, with a worse performance of E1 patients in the visuoperceptual ability and social cognition tasks. MRI study demonstrated a decrease in the volumes of frontal, parietal, temporal, occipital cortices, accumbens, putamen nuclei and a more severe volume reduction of the isthmus cingulate, transverse temporal, superior parietal and temporal gyri in E2 patients. Discussion: only some clinical parameters could predict the risk of cardiopathy, pulmonary syndrome and sleep disorders, while other clinical aspects proved to be unpredictable, confirming the importance of periodic clinical follow-up of these patients.
Resumo:
This thesis investigates mechanisms and boundary conditions that steer the early localisation of deformation and strain in carbonate multilayers involved in thrust systems, under shallow and mid-crustal conditions. Much is already understood about deformation localisation, but some key points remain loosely constrained. They encompass i) the understanding of which structural domains can preserve evidence of early stages of tectonic shortening, ii) the recognition of which mechanisms assist deformation during these stages and iii) the identification of parameters that actually steer the beginning of localisation. To clarify these points, the thesis presents the results of an integrated, multiscale and multi-technique structural study that relied on field and laboratory data to analyse the structural, architectural, mineralogical and geochemical features that govern deformation during compressional tectonics. By focusing on two case studies, the Eastern Southern Alps (northern Italy), where deformation is mainly brittle, and the Oman Mountains (northeastern Oman), where ductile deformation dominates, the thesis shows that the deformation localisation is steered by several mechanisms that mutually interact at different stages during compression. At shallow crustal conditions, derived conceptual and numerical models show that both inherited (e.g., stratigraphic) and acquired (e.g., structural) features play a key role in steering deformation and differentiating the seismic behaviour of the multilayer succession. At the same time, at deeper crustal conditions, strain localises in narrow domains in which fluids, temperature, shear strain and pressure act together during the development of the internal fabric and the chemical composition of mylonitic shear zones, in which localisation took place under high-pressure (HP) and low-temperature (LT) conditions. In particular, results indicate that those shear zones acted as “sheltering structural capsules” in which peculiar processes can happen and where the results of these processes can be successively preserved even over hundreds of millions of years.
Resumo:
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance technique that can quantify in vivo biomarkers of pathology, such as alteration in iron and myelin concentration. It allows for the comparison of magnetic susceptibility properties within and between different subject groups. In this thesis, QSM acquisition and processing pipeline are discussed, together with clinical and methodological applications of QSM to neurodegeneration. In designing the studies, significant emphasis was placed on results reproducibility and interpretability. The first project focuses on the investigation of cortical regions in amyotrophic lateral sclerosis. By examining various histogram susceptibility properties, a pattern of increased iron content was revealed in patients with amyotrophic lateral sclerosis compared to controls and other neurodegenerative disorders. Moreover, there was a correlation between susceptibility and upper motor neuron impairment, particularly in patients experiencing rapid disease progression. Similarly, in the second application, QSM was used to examine cortical and sub-cortical areas in individuals with myotonic dystrophy type 1. The thalamus and brainstem were identified as structures of interest, with relevant correlations with clinical and laboratory data such as neurological evaluation and sleep records. In the third project, a robust pipeline for assessing radiomic susceptibility-based features reliability was implemented within a cohort of patients with multiple sclerosis and healthy controls. Lastly, a deep learning super-resolution model was applied to QSM images of healthy controls. The employed model demonstrated excellent generalization abilities and outperformed traditional up-sampling methods, without requiring a customized re-training. Across the three disorders investigated, it was evident that QSM is capable of distinguishing between patient groups and healthy controls while establishing correlations between imaging measurements and clinical data. These studies lay the foundation for future research, with the ultimate goal of achieving earlier and less invasive diagnoses of neurodegenerative disorders within the context of personalized medicine.
Resumo:
For its particular position and the complex geological history, the Northern Apennines has been considered as a natural laboratory to apply several kinds of investigations. By the way, it is complicated to joint all the knowledge about the Northern Apennines in a unique picture that explains the structural and geological emplacement that produced it. The main goal of this thesis is to put together all information on the deformation - in the crust and at depth - of this region and to describe a geodynamical model that takes account of it. To do so, we have analyzed the pattern of deformation in the crust and in the mantle. In both cases the deformation has been studied using always information recovered from earthquakes, although using different techniques. In particular the shallower deformation has been studied using seismic moment tensors information. For our purpose we used the methods described in Arvidsson and Ekstrom (1998) that allowing the use in the inversion of surface waves [and not only of the body waves as the Centroid Moment Tensor (Dziewonski et al., 1981) one] allow to determine seismic source parameters for earthquakes with magnitude as small as 4.0. We applied this tool in the Northern Apennines and through this activity we have built up the Italian CMT dataset (Pondrelli et al., 2006) and the pattern of seismic deformation using the Kostrov (1974) method on a regular grid of 0.25 degree cells. We obtained a map of lateral variations of the pattern of seismic deformation on different layers of depth, taking into account the fact that shallow earthquakes (within 15 km of depth) in the region occur everywhere while most of events with a deeper hypocenter (15-40 km) occur only in the outer part of the belt, on the Adriatic side. For the analysis of the deep deformation, i.e. that occurred in the mantle, we used the anisotropy information characterizing the structure below the Northern Apennines. The anisotropy is an earth properties that in the crust is due to the presence of aligned fluid filled cracks or alternating isotropic layers with different elastic properties while in the mantle the most important cause of seismic anisotropy is the lattice preferred orientation (LPO) of the mantle minerals as the olivine. This last is a highly anisotropic mineral and tends to align its fast crystallographic axes (a-axis) parallel to the astenospheric flow as a response to finite strain induced by geodynamic processes. The seismic anisotropy pattern of a region is measured utilizing the shear wave splitting phenomenon (that is the seismological analogue to optical birefringence). Here, to do so, we apply on teleseismic earthquakes recorded on stations located in the study region, the Sileny and Plomerova (1996) approach. The results are analyzed on the basis of their lateral and vertical variations to better define the earth structure beneath Northern Apennines. We find different anisotropic domains, a Tuscany and an Adria one, with a pattern of seismic anisotropy which laterally varies in a similar way respect to the seismic deformation. Moreover, beneath the Adriatic region the distribution of the splitting parameters is so complex to request an appropriate analysis. Therefore we applied on our data the code of Menke and Levin (2003) which allows to look for different models of structures with multilayer anisotropy. We obtained that the structure beneath the Po Plain is probably even more complicated than expected. On the basis of the results obtained for this thesis, added with those from previous works, we suggest that slab roll-back, which created the Apennines and opened the Tyrrhenian Sea, evolved in the north boundary of Northern Apennines in a different way from its southern part. In particular, the trench retreat developed primarily south of our study region, with an eastward roll-back. In the northern portion of the orogen, after a first stage during which the retreat was perpendicular to the trench, it became oblique with respect to the structure.
Resumo:
The "sustainability" concept relates to the prolonging of human economic systems with as little detrimental impact on ecological systems as possible. Construction that exhibits good environmental stewardship and practices that conserve resources in a manner that allow growth and development to be sustained for the long-term without degrading the environment are indispensable in a developed society. Past, current and future advancements in asphalt as an environmentally sustainable paving material are especially important because the quantities of asphalt used annually in Europe as well as in the U.S. are large. The asphalt industry is still developing technological improvements that will reduce the environmental impact without affecting the final mechanical performance. Warm mix asphalt (WMA) is a type of asphalt mix requiring lower production temperatures compared to hot mix asphalt (HMA), while aiming to maintain the desired post construction properties of traditional HMA. Lowering the production temperature reduce the fuel usage and the production of emissions therefore and that improve conditions for workers and supports the sustainable development. Even the crumb-rubber modifier (CRM), with shredded automobile tires and used in the United States since the mid 1980s, has proven to be an environmentally friendly alternative to conventional asphalt pavement. Furthermore, the use of waste tires is not only relevant in an environmental aspect but also for the engineering properties of asphalt [Pennisi E., 1992]. This research project is aimed to demonstrate the dual value of these Asphalt Mixes in regards to the environmental and mechanical performance and to suggest a low environmental impact design procedure. In fact, the use of eco-friendly materials is the first phase towards an eco-compatible design but it cannot be the only step. The eco-compatible approach should be extended also to the design method and material characterization because only with these phases is it possible to exploit the maximum potential properties of the used materials. Appropriate asphalt concrete characterization is essential and vital for realistic performance prediction of asphalt concrete pavements. Volumetric (Mix design) and mechanical (Permanent deformation and Fatigue performance) properties are important factors to consider. Moreover, an advanced and efficient design method is necessary in order to correctly use the material. A design method such as a Mechanistic-Empirical approach, consisting of a structural model capable of predicting the state of stresses and strains within the pavement structure under the different traffic and environmental conditions, was the application of choice. In particular this study focus on the CalME and its Incremental-Recursive (I-R) procedure, based on damage models for fatigue and permanent shear strain related to the surface cracking and to the rutting respectively. It works in increments of time and, using the output from one increment, recursively, as input to the next increment, predicts the pavement conditions in terms of layer moduli, fatigue cracking, rutting and roughness. This software procedure was adopted in order to verify the mechanical properties of the study mixes and the reciprocal relationship between surface layer and pavement structure in terms of fatigue and permanent deformation with defined traffic and environmental conditions. The asphalt mixes studied were used in a pavement structure as surface layer of 60 mm thickness. The performance of the pavement was compared to the performance of the same pavement structure where different kinds of asphalt concrete were used as surface layer. In comparison to a conventional asphalt concrete, three eco-friendly materials, two warm mix asphalt and a rubberized asphalt concrete, were analyzed. The First Two Chapters summarize the necessary steps aimed to satisfy the sustainable pavement design procedure. In Chapter I the problem of asphalt pavement eco-compatible design was introduced. The low environmental impact materials such as the Warm Mix Asphalt and the Rubberized Asphalt Concrete were described in detail. In addition the value of a rational asphalt pavement design method was discussed. Chapter II underlines the importance of a deep laboratory characterization based on appropriate materials selection and performance evaluation. In Chapter III, CalME is introduced trough a specific explanation of the different equipped design approaches and specifically explaining the I-R procedure. In Chapter IV, the experimental program is presented with a explanation of test laboratory devices adopted. The Fatigue and Rutting performances of the study mixes are shown respectively in Chapter V and VI. Through these laboratory test data the CalME I-R models parameters for Master Curve, fatigue damage and permanent shear strain were evaluated. Lastly, in Chapter VII, the results of the asphalt pavement structures simulations with different surface layers were reported. For each pavement structure, the total surface cracking, the total rutting, the fatigue damage and the rutting depth in each bound layer were analyzed.
Resumo:
The aim of this thesis is to study how explosive behavior and geophysical signals in a volcanic conduit are related to the development of overpressure in slug-driven eruptions. A first suite of laboratory experiments of gas slugs ascending in analogue conduits was performed. Slugs ascended into a range of analogue liquids and conduit diameters to allow proper scaling to the natural volcanoes. The geometrical variation of the slug in response to the explored variables was parameterised. Volume of gas slug and rheology of the liquid phase revealed the key parameters in controlling slug overpressure at bursting. Founded on these results, a theoretical model to calculate burst overpressure for slug-driven eruptions was developed. The dimensionless approach adopted allowed to apply the model to predict bursting pressure of slugs at Stromboli. Comparison of predicted values with measured data from Stromboli volcano showed that the model can explain the entire spectrum of observed eruptive styles at Stromboli – from low-energy puffing, through normal Strombolian eruptions, up to paroxysmal explosions – as manifestations of a single underlying physical process. Finally, another suite of laboratory experiments was performed to observe oscillatory pressure and forces variations generated during the expansion and bursting of gas slugs ascending in a conduit. Two end-member boundary conditions were imposed at the base of the pipe, simulating slug ascent in closed base (zero magma flux) and open base (constant flux) conduit. At the top of the pipe, a range of boundary conditions that are relevant at a volcanic vent were imposed, going from open to plugged vent. The results obtained illustrate that a change in boundary conditions in the conduit concur to affect the dynamic of slug expansion and burst: an upward flux at the base of the conduit attenuates the magnitude of the pressure transients, while a rheological stiffening in the top-most region of conduit changes dramatically the magnitude of the observed pressure transients, favoring a sudden, and more energetic pressure release into the overlying atmosphere. Finally, a discussion on the implication of changing boundary on the oscillatory processes generated at the volcanic scale is also given.
Resumo:
Biomedical analyses are becoming increasingly complex, with respect to both the type of the data to be produced and the procedures to be executed. This trend is expected to continue in the future. The development of information and protocol management systems that can sustain this challenge is therefore becoming an essential enabling factor for all actors in the field. The use of custom-built solutions that require the biology domain expert to acquire or procure software engineering expertise in the development of the laboratory infrastructure is not fully satisfactory because it incurs undesirable mutual knowledge dependencies between the two camps. We propose instead an infrastructure concept that enables the domain experts to express laboratory protocols using proper domain knowledge, free from the incidence and mediation of the software implementation artefacts. In the system that we propose this is made possible by basing the modelling language on an authoritative domain specific ontology and then using modern model-driven architecture technology to transform the user models in software artefacts ready for execution in a multi-agent based execution platform specialized for biomedical laboratories.
Resumo:
Herbicides are becoming emergent contaminants in Italian surface, coastal and ground waters, due to their intensive use in agriculture. In marine environments herbicides have adverse effects on non-target organisms, as primary producers, resulting in oxygen depletion and decreased primary productivity. Alterations of species composition in algal communities can also occur due to the different sensitivity among the species. In the present thesis the effects of herbicides, widely used in the Northern Adriatic Sea, on different algal species were studied. The main goal of this work was to study the influence of temperature on algal growth in the presence of the triazinic herbicide terbuthylazine (TBA), and the cellular responses adopted to counteract the toxic effects of the pollutant (Chapter 1 and 2). The development of simulation models to be applied in environmental management are needed to organize and track information in a way that would not be possible otherwise and simulate an ecological prospective. The data collected from laboratory experiments were used to simulate algal responses to the TBA exposure at increasing temperature conditions (Chapter 3). Part of the thesis was conducted in foreign countries. The work presented in Chapter 4 was focused on the effect of high light on growth, toxicity and mixotrophy of the ichtyotoxic species Prymnesium parvum. In addition, a mesocosm experiment was conducted in order to study the synergic effect of the pollutant emamectin benzoate with other anthropogenic stressors, such as oil pollution and induced phytoplankton blooms (Chapter 5).
Resumo:
The evaluation of chronic activity of the hypothalamic-pituitary-adrenal (HPA) axis is critical for determining the impact of chronic stressful situations. The potential use of hair glucocorticoids as a non-invasive, retrospective, biomarker of long term HPA activity is of great interest, and it is gaining acceptance in humans and animals. However, there are still no studies in literature examining hair cortisol concentration in pigs and corticosterone concentration in laboratory rodents. Therefore, we developed and validated, for the first time, a method for measuring hair glucocorticoids concentration in commercial sows and in Sprague-Dawley rats. Our preliminary data demonstrated: 1) a validated and specific washing protocol and extraction assay method with a good sensitivity in both species; 2) the effect of the reproductive phase, housing conditions and seasonality on hair cortisol concentration in sows; 3) similar hair corticosterone concentration in male and female rats; 4) elevated hair corticosterone concentration in response to chronic stress manipulations and chronic ACTH administration, demonstrating that hair provides a good direct index of HPA activity over long periods than other indirect parameters, such adrenal or thymus weight. From these results we believe that this new non-invasive tool needs to be applied to better characterize the overall impact in livestock animals and in laboratory rodents of chronic stressful situations that negatively affect animals welfare. Nevertheless, further studies are needed to improve this methodology and maybe to develop animal models for chronic stress of high interest and translational value in human medicine.
Resumo:
Simkania negevensis is a bacterium belonging to the order Chlamydiales but with certain biological characteristics different from those of chlamydia, according to which it was classified in the family Simkaniaceae. It is widespread in the environment, due to its ability to survive in amoebae also in phase cystic, for which it was hypothesized a possible transmission after contact with water in which they are present amoebae. So far it is known its role in diseases of the lower respiratory tract, such as childhood bronchiolitis and pneumonia in adults of the community, following its transmission through infected aerosols. A recent American study showed, by PCR, a high prevalence of S. negevensis in patients with lung transplant than other transplant recipients, assuming an association between the presence of the bacterium in these patients, and transplant rejection, were more frequent in lung transplant recipients infected compared to uninfected. There are no data so far analyzed in Italy relative to the population of dialysis and kidney transplant recipients relative to simkania negevensis why this study was undertaken in order to start a specific location and evaluate the scientific implications. Because its ability to assume persistent forms of infection, which may lead to a prolonged inflammatory response, Simkania negevensis, similar to other persistent bacteria or viruses, may be ivolved in pathologic complication. Sn may be a factor in graft rejection in mmunesuppressed lung transplant recipients, and further studies are planned to explore the posible association of Sn infections with various in vivo pathologies.
Resumo:
The idea behind the project is to develop a methodology for analyzing and developing techniques for the diagnosis and the prediction of the state of charge and health of lithium-ion batteries for automotive applications. For lithium-ion batteries, residual functionality is measured in terms of state of health; however, this value cannot be directly associated with a measurable value, so it must be estimated. The development of the algorithms is based on the identification of the causes of battery degradation, in order to model and predict the trend. Therefore, models have been developed that are able to predict the electrical, thermal and aging behavior. In addition to the model, it was necessary to develop algorithms capable of monitoring the state of the battery, online and offline. This was possible with the use of algorithms based on Kalman filters, which allow the estimation of the system status in real time. Through machine learning algorithms, which allow offline analysis of battery deterioration using a statistical approach, it is possible to analyze information from the entire fleet of vehicles. Both systems work in synergy in order to achieve the best performance. Validation was performed with laboratory tests on different batteries and under different conditions. The development of the model allowed to reduce the time of the experimental tests. Some specific phenomena were tested in the laboratory, and the other cases were artificially generated.