892 resultados para Development Models, territory
Resumo:
Supply chain starts with a demand arisen and ends with material transport and delivery at its final destination. With this in mind, most of manufacturing, processors or distribution companies of consumer goods, spare parts and components for production, processing and finished goods, within national or international markets, may not have information and control over its supply chain performance. This article presents concept and logistics models evolution, purchase order and international supplier management, control tower and its logistics information systems. This also presents a real process implementation for a global high tech manufacturer company.
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Paracoccidoides brasiliensis adhesion to lung epithelial cells is considered an essential event for the establishment of infection and different proteins participate in this process. One of these proteins is a 30 kDa adhesin, pI 4.9 that was described as a laminin ligand in previous studies, and it was more highly expressed in more virulent P. brasiliensis isolates. This protein may contribute to the virulence of this important fungal pathogen. Using Edman degradation and mass spectrometry analysis, this 30 kDa adhesin was identified as a 14-3-3 protein. These proteins are a conserved group of small acidic proteins involved in a variety of processes in eukaryotic organisms. However, the exact function of these proteins in some processes remains unknown. Thus, the goal of the present study was to characterize the role of this protein during the interaction between the fungus and its host. To achieve this goal, we cloned, expressed the 14-3-3 protein in a heterologous system and determined its subcellular localization in in vitro and in vivo infection models. Immunocytochemical analysis revealed the ubiquitous distribution of this protein in the yeast form of P. brasiliensis, with some concentration in the cytoplasm. Additionally, this 14-3-3 protein was also present in P. brasiliensis cells at the sites of infection in C57BL/6 mice intratracheally infected with P. brasiliensis yeast cells for 72 h (acute infections) and 30 days (chronic infection). An apparent increase in the levels of the 14-3-3 protein in the cell wall of the fungus was also noted during the interaction between P. brasiliensis and A549 cells, suggesting that this protein may be involved in host-parasite interactions, since inhibition assays with the protein and this antibody decreased P. brasiliensis adhesion to A549 epithelial cells. Our data may lead to a better understanding of P. brasiliensis interactions with host tissues and paracoccidioidomycosis pathogenesis.
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In electronic commerce, systems development is based on two fundamental types of models, business models and process models. A business model is concerned with value exchanges among business partners, while a process model focuses on operational and procedural aspects of business communication. Thus, a business model defines the what in an e-commerce system, while a process model defines the how. Business process design can be facilitated and improved by a method for systematically moving from a business model to a process model. Such a method would provide support for traceability, evaluation of design alternatives, and seamless transition from analysis to realization. This work proposes a unified framework that can be used as a basis to analyze, to interpret and to understand different concepts associated at different stages in e-Commerce system development. In this thesis, we illustrate how UN/CEFACT’s recommended metamodels for business and process design can be analyzed, extended and then integrated for the final solutions based on the proposed unified framework. Also, as an application of the framework, we demonstrate how process-modeling tasks can be facilitated in e-Commerce system design. The proposed methodology, called BP3 stands for Business Process Patterns Perspective. The BP3 methodology uses a question-answer interface to capture different business requirements from the designers. It is based on pre-defined process patterns, and the final solution is generated by applying the captured business requirements by means of a set of production rules to complete the inter-process communication among these patterns.
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The increasing aversion to technological risks of the society requires the development of inherently safer and environmentally friendlier processes, besides assuring the economic competitiveness of the industrial activities. The different forms of impact (e.g. environmental, economic and societal) are frequently characterized by conflicting reduction strategies and must be holistically taken into account in order to identify the optimal solutions in process design. Though the literature reports an extensive discussion of strategies and specific principles, quantitative assessment tools are required to identify the marginal improvements in alternative design options, to allow the trade-off among contradictory aspects and to prevent the “risk shift”. In the present work a set of integrated quantitative tools for design assessment (i.e. design support system) was developed. The tools were specifically dedicated to the implementation of sustainability and inherent safety in process and plant design activities, with respect to chemical and industrial processes in which substances dangerous for humans and environment are used or stored. The tools were mainly devoted to the application in the stages of “conceptual” and “basic design”, when the project is still open to changes (due to the large number of degrees of freedom) which may comprise of strategies to improve sustainability and inherent safety. The set of developed tools includes different phases of the design activities, all through the lifecycle of a project (inventories, process flow diagrams, preliminary plant lay-out plans). The development of such tools gives a substantial contribution to fill the present gap in the availability of sound supports for implementing safety and sustainability in early phases of process design. The proposed decision support system was based on the development of a set of leading key performance indicators (KPIs), which ensure the assessment of economic, societal and environmental impacts of a process (i.e. sustainability profile). The KPIs were based on impact models (also complex), but are easy and swift in the practical application. Their full evaluation is possible also starting from the limited data available during early process design. Innovative reference criteria were developed to compare and aggregate the KPIs on the basis of the actual sitespecific impact burden and the sustainability policy. Particular attention was devoted to the development of reliable criteria and tools for the assessment of inherent safety in different stages of the project lifecycle. The assessment follows an innovative approach in the analysis of inherent safety, based on both the calculation of the expected consequences of potential accidents and the evaluation of the hazards related to equipment. The methodology overrides several problems present in the previous methods proposed for quantitative inherent safety assessment (use of arbitrary indexes, subjective judgement, build-in assumptions, etc.). A specific procedure was defined for the assessment of the hazards related to the formations of undesired substances in chemical systems undergoing “out of control” conditions. In the assessment of layout plans, “ad hoc” tools were developed to account for the hazard of domino escalations and the safety economics. The effectiveness and value of the tools were demonstrated by the application to a large number of case studies concerning different kinds of design activities (choice of materials, design of the process, of the plant, of the layout) and different types of processes/plants (chemical industry, storage facilities, waste disposal). An experimental survey (analysis of the thermal stability of isomers of nitrobenzaldehyde) provided the input data necessary to demonstrate the method for inherent safety assessment of materials.
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Traditional software engineering approaches and metaphors fall short when applied to areas of growing relevance such as electronic commerce, enterprise resource planning, and mobile computing: such areas, in fact, generally call for open architectures that may evolve dynamically over time so as to accommodate new components and meet new requirements. This is probably one of the main reasons that the agent metaphor and the agent-oriented paradigm are gaining momentum in these areas. This thesis deals with the engineering of complex software systems in terms of the agent paradigm. This paradigm is based on the notions of agent and systems of interacting agents as fundamental abstractions for designing, developing and managing at runtime typically distributed software systems. However, today the engineer often works with technologies that do not support the abstractions used in the design of the systems. For this reason the research on methodologies becomes the basic point in the scientific activity. Currently most agent-oriented methodologies are supported by small teams of academic researchers, and as a result, most of them are in an early stage and still in the first context of mostly \academic" approaches for agent-oriented systems development. Moreover, such methodologies are not well documented and very often defined and presented only by focusing on specific aspects of the methodology. The role played by meta- models becomes fundamental for comparing and evaluating the methodologies. In fact a meta-model specifies the concepts, rules and relationships used to define methodologies. Although it is possible to describe a methodology without an explicit meta-model, formalising the underpinning ideas of the methodology in question is valuable when checking its consistency or planning extensions or modifications. A good meta-model must address all the different aspects of a methodology, i.e. the process to be followed, the work products to be generated and those responsible for making all this happen. In turn, specifying the work products that must be developed implies dening the basic modelling building blocks from which they are built. As a building block, the agent abstraction alone is not enough to fully model all the aspects related to multi-agent systems in a natural way. In particular, different perspectives exist on the role that environment plays within agent systems: however, it is clear at least that all non-agent elements of a multi-agent system are typically considered to be part of the multi-agent system environment. The key role of environment as a first-class abstraction in the engineering of multi-agent system is today generally acknowledged in the multi-agent system community, so environment should be explicitly accounted for in the engineering of multi-agent system, working as a new design dimension for agent-oriented methodologies. At least two main ingredients shape the environment: environment abstractions - entities of the environment encapsulating some functions -, and topology abstractions - entities of environment that represent the (either logical or physical) spatial structure. In addition, the engineering of non-trivial multi-agent systems requires principles and mechanisms for supporting the management of the system representation complexity. These principles lead to the adoption of a multi-layered description, which could be used by designers to provide different levels of abstraction over multi-agent systems. The research in these fields has lead to the formulation of a new version of the SODA methodology where environment abstractions and layering principles are exploited for en- gineering multi-agent systems.
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The motivation for the work presented in this thesis is to retrieve profile information for the atmospheric trace constituents nitrogen dioxide (NO2) and ozone (O3) in the lower troposphere from remote sensing measurements. The remote sensing technique used, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), is a recent technique that represents a significant advance on the well-established DOAS, especially for what it concerns the study of tropospheric trace consituents. NO2 is an important trace gas in the lower troposphere due to the fact that it is involved in the production of tropospheric ozone; ozone and nitrogen dioxide are key factors in determining the quality of air with consequences, for example, on human health and the growth of vegetation. To understand the NO2 and ozone chemistry in more detail not only the concentrations at ground but also the acquisition of the vertical distribution is necessary. In fact, the budget of nitrogen oxides and ozone in the atmosphere is determined both by local emissions and non-local chemical and dynamical processes (i.e. diffusion and transport at various scales) that greatly impact on their vertical and temporal distribution: thus a tool to resolve the vertical profile information is really important. Useful measurement techniques for atmospheric trace species should fulfill at least two main requirements. First, they must be sufficiently sensitive to detect the species under consideration at their ambient concentration levels. Second, they must be specific, which means that the results of the measurement of a particular species must be neither positively nor negatively influenced by any other trace species simultaneously present in the probed volume of air. Air monitoring by spectroscopic techniques has proven to be a very useful tool to fulfill these desirable requirements as well as a number of other important properties. During the last decades, many such instruments have been developed which are based on the absorption properties of the constituents in various regions of the electromagnetic spectrum, ranging from the far infrared to the ultraviolet. Among them, Differential Optical Absorption Spectroscopy (DOAS) has played an important role. DOAS is an established remote sensing technique for atmospheric trace gases probing, which identifies and quantifies the trace gases in the atmosphere taking advantage of their molecular absorption structures in the near UV and visible wavelengths of the electromagnetic spectrum (from 0.25 μm to 0.75 μm). Passive DOAS, in particular, can detect the presence of a trace gas in terms of its integrated concentration over the atmospheric path from the sun to the receiver (the so called slant column density). The receiver can be located at ground, as well as on board an aircraft or a satellite platform. Passive DOAS has, therefore, a flexible measurement configuration that allows multiple applications. The ability to properly interpret passive DOAS measurements of atmospheric constituents depends crucially on how well the optical path of light collected by the system is understood. This is because the final product of DOAS is the concentration of a particular species integrated along the path that radiation covers in the atmosphere. This path is not known a priori and can only be evaluated by Radiative Transfer Models (RTMs). These models are used to calculate the so called vertical column density of a given trace gas, which is obtained by dividing the measured slant column density to the so called air mass factor, which is used to quantify the enhancement of the light path length within the absorber layers. In the case of the standard DOAS set-up, in which radiation is collected along the vertical direction (zenith-sky DOAS), calculations of the air mass factor have been made using “simple” single scattering radiative transfer models. This configuration has its highest sensitivity in the stratosphere, in particular during twilight. This is the result of the large enhancement in stratospheric light path at dawn and dusk combined with a relatively short tropospheric path. In order to increase the sensitivity of the instrument towards tropospheric signals, measurements with the telescope pointing the horizon (offaxis DOAS) have to be performed. In this circumstances, the light path in the lower layers can become very long and necessitate the use of radiative transfer models including multiple scattering, the full treatment of atmospheric sphericity and refraction. In this thesis, a recent development in the well-established DOAS technique is described, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). The MAX-DOAS consists in the simultaneous use of several off-axis directions near the horizon: using this configuration, not only the sensitivity to tropospheric trace gases is greatly improved, but vertical profile information can also be retrieved by combining the simultaneous off-axis measurements with sophisticated RTM calculations and inversion techniques. In particular there is a need for a RTM which is capable of dealing with all the processes intervening along the light path, supporting all DOAS geometries used, and treating multiple scattering events with varying phase functions involved. To achieve these multiple goals a statistical approach based on the Monte Carlo technique should be used. A Monte Carlo RTM generates an ensemble of random photon paths between the light source and the detector, and uses these paths to reconstruct a remote sensing measurement. Within the present study, the Monte Carlo radiative transfer model PROMSAR (PROcessing of Multi-Scattered Atmospheric Radiation) has been developed and used to correctly interpret the slant column densities obtained from MAX-DOAS measurements. In order to derive the vertical concentration profile of a trace gas from its slant column measurement, the AMF is only one part in the quantitative retrieval process. One indispensable requirement is a robust approach to invert the measurements and obtain the unknown concentrations, the air mass factors being known. For this purpose, in the present thesis, we have used the Chahine relaxation method. Ground-based Multiple AXis DOAS, combined with appropriate radiative transfer models and inversion techniques, is a promising tool for atmospheric studies in the lower troposphere and boundary layer, including the retrieval of profile information with a good degree of vertical resolution. This thesis has presented an application of this powerful comprehensive tool for the study of a preserved natural Mediterranean area (the Castel Porziano Estate, located 20 km South-West of Rome) where pollution is transported from remote sources. Application of this tool in densely populated or industrial areas is beginning to look particularly fruitful and represents an important subject for future studies.
Resumo:
The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.
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In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.
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The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.
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Magnetic resonance imaging (MRI) is today precluded to patients bearing active implantable medical devices AIMDs). The great advantages related to this diagnostic modality, together with the increasing number of people benefiting from implantable devices, in particular pacemakers(PM)and carioverter/defibrillators (ICD), is prompting the scientific community the study the possibility to extend MRI also to implanted patients. The MRI induced specific absorption rate (SAR) and the consequent heating of biological tissues is one of the major concerns that makes patients bearing metallic structures contraindicated for MRI scans. To date, both in-vivo and in-vitro studies have demonstrated the potentially dangerous temperature increase caused by the radiofrequency (RF) field generated during MRI procedures in the tissues surrounding thin metallic implants. On the other side, the technical evolution of MRI scanners and of AIMDs together with published data on the lack of adverse events have reopened the interest in this field and suggest that, under given conditions, MRI can be safely performed also in implanted patients. With a better understanding of the hazards of performing MRI scans on implanted patients as well as the development of MRI safe devices, we may soon enter an era where the ability of this imaging modality may be more widely used to assist in the appropriate diagnosis of patients with devices. In this study both experimental measures and numerical analysis were performed. Aim of the study is to systematically investigate the effects of the MRI RF filed on implantable devices and to identify the elements that play a major role in the induced heating. Furthermore, we aimed at developing a realistic numerical model able to simulate the interactions between an RF coil for MRI and biological tissues implanted with a PM, and to predict the induced SAR as a function of the particular path of the PM lead. The methods developed and validated during the PhD program led to the design of an experimental framework for the accurate measure of PM lead heating induced by MRI systems. In addition, numerical models based on Finite-Differences Time-Domain (FDTD) simulations were validated to obtain a general tool for investigating the large number of parameters and factors involved in this complex phenomenon. The results obtained demonstrated that the MRI induced heating on metallic implants is a real risk that represents a contraindication in extending MRI scans also to patient bearing a PM, an ICD, or other thin metallic objects. On the other side, both experimental data and numerical results show that, under particular conditions, MRI procedures might be consider reasonably safe also for an implanted patient. The complexity and the large number of variables involved, make difficult to define a unique set of such conditions: when the benefits of a MRI investigation cannot be obtained using other imaging techniques, the possibility to perform the scan should not be immediately excluded, but some considerations are always needed.
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Since the birth of the European Union on 1957, the development of a single market through the integration of national freight transport networks has been one of the most important points in the European Union agenda. Increasingly congested motorways, rising oil prices and concerns about environment and climate change require the optimization of transport systems and transport processes. The best solution should be the intermodal transport, in which the most efficient transport options are used for the different legs of transport. This thesis examines the problem of defining innovative strategies and procedures for the sustainable development of intermodal freight transport in Europe. In particular, the role of maritime transport and railway transport in the intermodal chain are examined in depth, as these modes are recognized to be environmentally friendly and energy efficient. Maritime transport is the only mode that has kept pace with the fast growth in road transport, but it is necessary to promote the full exploitation of it by involving short sea shipping as an integrated service in the intermodal door-to-door supply chain and by improving port accessibility. The role of Motorways of the Sea services as part of the Trans-European Transport Network is is taken into account: a picture of the European policy and a state of the art of the Italian Motorways of the Sea system are reported. Afterwards, the focus shifts from line to node problems: the role of intermodal railway terminals in the transport chain is discussed. In particular, the last mile process is taken into account, as it is crucial in order to exploit the full capacity of an intermodal terminal. The difference between the present last mile planning models of Bologna Interporto and Verona Quadrante Europa is described and discussed. Finally, a new approach to railway intermodal terminal planning and management is introduced, by describing the case of "Terminal Gate" at Verona Quadrante Europa. Some proposals to favour the integrate management of "Terminal Gate" and the allocation of its capacity are drawn up.
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High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.
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Triplex cell vaccine is a cancer immunopreventive cell vaccine that can prevent almost completely mammary tumor onset in HER-2/neu transgenic mice. A future translation of cancer immunoprevention from preclinical to clinical studies should take into account several aspects. The work reported in this thesis deals with the study of three of these aspects: vaccine schedule, activity in a therapeutic set-up and second-generation DNA vaccines. An important element in determining human acceptance and compliance of a treatment protocol is the number of vaccinations. In order to improve the vaccination schedule a minimal protocol was searched, i.e. a schedule consisting of a lower number of administrations than standard protocol but with a similar efficacy. A candidate optimal protocol was identified by the use of an in silico model, SimTriplex simulator. The in vivo test of this schedule in HER-2/neu transgenic mice only partially confirmed in silico predictions. This result shows that in silico models have the potential ability to aid in searching of optimal treatment protocols, provided that they will be further tuned on experimental data. As a further result this preclinical study highlighted that kinetic of antibody response plays a major role in determining cancer prevention, leading to the hypothesis of a threshold that must be reached rapidly and maintained lifetime. Early clinical trials would be performed in a therapeutic, rather than preventive, setting. Thus, the activity of Triplex vaccine was investigated against experimental lung metastases in HER-2/neu transgenic mice in order to evaluate if the immunopreventive Triplex vaccine could be effective also against a pre-existing tumor mass. This preclinical model of aggressive metastatic development showed that the vaccine was an efficient treatment also 4 for the cure of micrometastases. However the immune mechanisms activated against tumor mass were not antibody dependent, i.e. different from those preventing the onset of primary mammary carcinoma. DNA vaccines could be more easily used than cellular ones. A second generation of Triplex vaccine based on DNA plasmids was evaluated in an aggressive preclinical model (BALBp53neu female mice) and compared with the preventive ability of cellular Triplex vaccine. It was observed that Triplex DNA vaccine was as effective as Triplex cell vaccine, exploiting a more restricted immune stimulation.
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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.
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Synthetic biology is a young field of applicative research aiming to design and build up artificial biological devices, useful for human applications. How synthetic biology emerged in past years and how the development of the Registry of Standard Biological Parts aimed to introduce one practical starting solution to apply the basics of engineering to molecular biology is presented in chapter 1 in the thesis The same chapter recalls how biological parts can make up a genetic program, the molecular cloning tecnique useful for this purpose, and an overview of the mathematical modeling adopted to describe gene circuit behavior. Although the design of gene circuits has become feasible the increasing complexity of gene networks asks for a rational approach to design gene circuits. A bottom-up approach was proposed, suggesting that the behavior of a complicated system can be predicted from the features of its parts. The option to use modular parts in large-scale networks will be facilitated by a detailed and shared characterization of their functional properties. Such a prediction, requires well-characterized mathematical models of the parts and of how they behave when assembled together. In chapter 2, the feasibility of the bottom-up approach in the design of a synthetic program in Escherichia coli bacterial cells is described. The rational design of gene networks is however far from being established. The synthetic biology approach can used the mathematical formalism to identify biological information not assessable with experimental measurements. In this context, chapter 3 describes the design of a synthetic sensor for identifying molecules of interest inside eukaryotic cells. The Registry of Standard parts collects standard and modular biological parts. To spread the use of BioBricks the iGEM competition was started. The ICM Laboratory, where Francesca Ceroni completed her Ph.D, partecipated with teams of students and Chapter 4 summarizes the projects developed.