Models and methods for power monolithic microwave integrated circuits

Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends critically on active device models that are accurate, computationally efficient, and easily extracted from measurements or device simulators. Empirical models of active electron devices, which are based on actual device measurements, do not provide a detailed description of the electron device physics. However they are numerically efficient and quite accurate. These characteristics make them very suitable for MMIC design in the framework of commercially available CAD tools. In the empirical model formulation it is very important to separate linear memory effects (parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device model is generally described by an extrinsic linear part which accounts for the parasitic passive structures connecting the nonlinear intrinsic electron device to the external world. An important task circuit designers deal with is evaluating the ultimate potential of a device for specific applications. In fact once the technology has been selected, the designer would choose the best device for the particular application and the best device for the different blocks composing the overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices, good scalability properties of the model are necessarily required. Another important aspect of empirical modelling of electron devices is the mathematical (or equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device. Once the model has been defined, the proper measurements for the characterization of the device are performed in order to identify the model. Hence, the correct measurement of the device nonlinear characteristics (in the device characterization phase) and their reconstruction (in the identification or even simulation phase) are two of the more important aspects of empirical modelling. This thesis presents an original contribution to nonlinear electron device empirical modelling treating the issues of model scalability and reconstruction of the device nonlinear characteristics. The scalability of an empirical model strictly depends on the scalability of the linear extrinsic parasitic network, which should possibly maintain the link between technological process parameters and the corresponding device electrical response. Since lumped parasitic networks, together with simple linear scaling rules, cannot provide accurate scalable models, either complicate technology-dependent scaling rules or computationally inefficient distributed models are available in literature. This thesis shows how the above mentioned problems can be avoided through the use of commercially available electromagnetic (EM) simulators. They enable the actual device geometry and material stratification, as well as losses in the dielectrics and electrodes, to be taken into account for any given device structure and size, providing an accurate description of the parasitic effects which occur in the device passive structure. It is shown how the electron device behaviour can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed four-port passive parasitic network, which is identified by means of the EM simulation of the device layout, allowing for better frequency extrapolation and scalability properties than conventional empirical models. Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data approximation algorithm has been developed for the exploitation in the framework of empirical table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain signal reconstruction from a set of samples and the continuous approximation of device nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion, nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain, typical methods of the time-domain sampling theory.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Development of a Computer-Based methodology for tolerance selection and optimization applied to the automotive sector

The design optimization of industrial products has always been an essential activity to improve product quality while reducing time-to-market and production costs. Although cost management is very complex and comprises all phases of the product life cycle, the control of geometrical and dimensional variations, known as Dimensional Management (DM), allows compliance with product and process requirements. Hence, the tolerance-cost optimization becomes the main practice to provide an effective application of Design for Tolerancing (DfT) and Design to Cost (DtC) approaches by enabling a connection between product tolerances and associated manufacturing costs. However, despite the growing interest in this topic, a profitable application in the industry of these techniques is hampered by their complexity: the definition of a systematic framework is the key element to improving design optimization, enhancing the concurrent use of Computer-Aided tools and Model-Based Definition (MBD) practices. The present doctorate research aims to define and develop an integrated methodology for product/process design optimization, to better exploit the new capabilities of advanced simulations and tools. By implementing predictive models and multi-disciplinary optimization, a Computer-Aided Integrated framework for tolerance-cost optimization has been proposed to allow the integration of DfT and DtC approaches and their direct application for the design of automotive components. Several case studies have been considered, with the final application of the integrated framework on a high-performance V12 engine assembly, to achieve both functional targets and cost reduction. From a scientific point of view, the proposed methodology provides an improvement for the tolerance-cost optimization of industrial components. The integration of theoretical approaches and Computer-Aided tools allows to analyse the influence of tolerances on both product performance and manufacturing costs. The case studies proved the suitability of the methodology for its application in the industrial field, providing the identification of further areas for improvement and refinement.

Development and application of a computer-based methodology for design for additive manufacturing of automotive components

The research project aims to improve the Design for Additive Manufacturing of metal components. Firstly, the scenario of Additive Manufacturing is depicted, describing its role in Industry 4.0 and in particular focusing on Metal Additive Manufacturing technologies and the Automotive sector applications. Secondly, the state of the art in Design for Additive Manufacturing is described, contextualizing the methodologies, and classifying guidelines, rules, and approaches. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened together with the Computer-Aided Technologies to support the approaches implementation. Therefore, a general Design for Additive Manufacturing workflow based on product and process optimization has been systematically defined. From the analysis of the state of the art, the use of a holistic approach has been considered fundamental and thus the use of integrated product-process design platforms has been evaluated as a key element for its development. Indeed, a computer-based methodology exploiting integrated tools and numerical simulations to drive the product and process optimization has been proposed. A validation of CAD platform-based approaches has been performed, as well as potentials offered by integrated tools have been evaluated. Concerning product optimization, systematic approaches to integrate topology optimization in the design have been proposed and validated through product optimization of an automotive case study. Concerning process optimization, the use of process simulation techniques to prevent manufacturing flaws related to the high thermal gradients of metal processes is developed, providing case studies to validate results compared to experimental data, and application to process optimization of an automotive case study. Finally, an example of the product and process design through the proposed simulation-driven integrated approach is provided to prove the method's suitability for effective redesigns of Additive Manufacturing based high-performance metal products. The results are then outlined, and further developments are discussed.

New functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb

In case of severe osteoarthritis at the knee causing pain, deformity, and loss of stability and mobility, the clinicians consider that the substitution of these surfaces by means of joint prostheses. The objectives to be pursued by this surgery are: complete pain elimination, restoration of the normal physiological mobility and joint stability, correction of all deformities and, thus, of limping. The knee surgical navigation systems have bee developed in computer-aided surgery in order to improve the surgical final outcome in total knee arthroplasty. These systems provide the surgeon with quantitative and real-time information about each surgical action, like bone cut executions and prosthesis component alignment, by mean of tracking tools rigidly fixed onto the femur and the tibia. Nevertheless, there is still a margin of error due to the incorrect surgical procedures and to the still limited number of kinematic information provided by the current systems. Particularly, patello-femoral joint kinematics is not considered in knee surgical navigation. It is also unclear and, thus, a source of misunderstanding, what the most appropriate methodology is to study the patellar motion. In addition, also the knee ligamentous apparatus is superficially considered in navigated total knee arthroplasty, without taking into account how their physiological behavior is altered by this surgery. The aim of the present research work was to provide new functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb. This was mainly realized by means of the identification and development of new techniques that allow a thorough comprehension of the functioning of the knee joint, with particular attention to the patello-femoral joint and to the main knee soft tissues. A knee surgical navigation system with active markers was used in all research activities presented in this research work. Particularly, preliminary test were performed in order to assess the system accuracy and the robustness of a number of navigation procedures. Four studies were performed in-vivo on patients requiring total knee arthroplasty and randomly implanted by means of traditional and navigated procedures in order to check for the real efficacy of the latter with respect to the former. In order to cope with assessment of patello-femoral joint kinematics in the intact and replaced knees, twenty in-vitro tests were performed by using a prototypal tracking tool also for the patella. In addition to standard anatomical and articular recommendations, original proposals for defining the patellar anatomical-based reference frame and for studying the patello-femoral joint kinematics were reported and used in these tests. These definitions were applied to two further in-vitro tests in which, for the first time, also the implant of patellar component insert was fully navigated. In addition, an original technique to analyze the main knee soft tissues by means of anatomical-based fiber mappings was also reported and used in the same tests. The preliminary instrumental tests revealed a system accuracy within the millimeter and a good inter- and intra-observer repeatability in defining all anatomical reference frames. In in-vivo studies, the general alignments of femoral and tibial prosthesis components and of the lower limb mechanical axis, as measured on radiographs, was more satisfactory, i.e. within ±3°, in those patient in which total knee arthroplasty was performed by navigated procedures. As for in-vitro tests, consistent patello-femoral joint kinematic patterns were observed over specimens throughout the knee flexion arc. Generally, the physiological intact knee patellar motion was not restored after the implant. This restoration was successfully achieved in the two further tests where all component implants, included the patellar insert, were fully navigated, i.e. by means of intra-operative assessment of also patellar component positioning and general tibio-femoral and patello-femoral joint assessment. The tests for assessing the behavior of the main knee ligaments revealed the complexity of the latter and the different functional roles played by the several sub-bundles compounding each ligament. Also in this case, total knee arthroplasty altered the physiological behavior of these knee soft tissues. These results reveal in-vitro the relevance and the feasibility of the applications of new techniques for accurate knee soft tissues monitoring, patellar tracking assessment and navigated patellar resurfacing intra-operatively in the contest of the most modern operative techniques. This present research work gives a contribution to the much controversial knowledge on the normal and replaced of knee kinematics by testing the reported new methodologies. The consistence of these results provides fundamental information for the comprehension and improvements of knee orthopedic treatments. In the future, the reported new techniques can be safely applied in-vivo and also adopted in other joint replacements.

Sviluppo, implementazione e valutazione funzionale di un nuovo modello protesico di caviglia

Total ankle arthroplasty (TAA) is still not as satisfactory as total hip and total knee arthroplasty. For the TAA to be considered a valuable alternative to ankle arthrodesis, an effective range of ankle mobility must be recovered. The disappointing clinical results of the current generation of TAA are mostly related to poor understanding of the structures guiding ankle joint mobility. A new design (BOX Ankle) has been developed, uniquely able to restore physiologic ankle mobility and a natural relationship between the implanted components and the retained ligaments. For the first time the shapes of the tibial and talar components in the sagittal plane were designed to be compatible with the demonstrated ligament isometric rotation. This resulted in an unique motion at the replaced ankle where natural sliding as well as rolling motion occurs while at the same time full conformity is maintained between the three components throughout the flexion arc. According to prior research, the design features a spherical convex tibial component, a talar component with radius of curvature in the sagittal plane longer than that of the natural talus, and a fully conforming meniscal component. After computer-based modelling and preliminary observations in several trial implantation in specimens, 126 patients were implanted in the period July 2003 – December 2008. 75 patients with at least 6 months follow-up are here reported. Mean age was 62,6 years (range 22 – 80), mean follow-up 20,2 months. The AOFAS clinical score systems were used to assess patient outcome. Radiographs at maximal dorsiflexion and maximal plantar flexion confirmed the meniscalbearing component moves anteriorly during dorsiflexion and posteriorly during plantarflexion. Frontal and lateral radiographs in the patients, show good alignment of the components, and no signs of radiolucency or loosening. The mean AOFAS score was observed to go from 41 pre-op to 74,6 at 6 month follow-up, with further improvement at the following follow-up. These early results reveal satisfactory clinical scores, with good recovery of range of motion and reduction of pain. Radiographic assessment reveals good osteointegration. All these preliminary results confirm biomechanical studies and the validity of this novel ligamentcompatible prosthesis design. Surely it will be important to re-evaluate these patients later.

Analysis and modeling techniques for ultrasonic tissue characterization

This thesis introduces new processing techniques for computer-aided interpretation of ultrasound images with the purpose of supporting medical diagnostic. In terms of practical application, the goal of this work is the improvement of current prostate biopsy protocols by providing physicians with a visual map overlaid over ultrasound images marking regions potentially affected by disease. As far as analysis techniques are concerned, the main contributions of this work to the state-of-the-art is the introduction of deconvolution as a pre-processing step in the standard ultrasonic tissue characterization procedure to improve the diagnostic significance of ultrasonic features. This thesis also includes some innovations in ultrasound modeling, in particular the employment of a continuous-time autoregressive moving-average (CARMA) model for ultrasound signals, a new maximum-likelihood CARMA estimator based on exponential splines and the definition of CARMA parameters as new ultrasonic features able to capture scatterers concentration. Finally, concerning the clinical usefulness of the developed techniques, the main contribution of this research is showing, through a study based on medical ground truth, that a reduction in the number of sampled cores in standard prostate biopsy is possible, preserving the same diagnostic power of the current clinical protocol.

Physical models for numerical simulation of Si-based nanoscale FETs and sensors

To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.

Elaborazione di un algoritmo di pianificazione di ricostruzioni del cavo orale, dell'orofaringe, della mandibola.

1.Ricostruzione mandibolare La ricostruzione mandibolare è comunemente eseguita utilizzando un lembo libero perone. Il metodo convenzionale (indiretto) di Computer Aided Design e Computer Aided Manifacturing prevede il modellamento manuale preoperatorio di una placca di osteosintesi standard su un modello stereolitografico della mandibola. Un metodo innovativo CAD CAM diretto comprende 3 fasi: 1) pianificazione virtuale 2) computer aided design della dima di taglio mandibolari, della dima di taglio del perone e della placca di osteosintesi e 3) Computer Aided Manufacturing dei 3 dispositivi chirurgici personalizzati. 7 ricostruzioni mandibolari sono state effettuate con il metodo diretto. I risultati raggiunti e le modalità di pianificazione sono descritte e discusse. La progettazione assistita da computer e la tecnica di fabbricazione assistita da computer facilita un'accurata ricostruzione mandibolare ed apporta un miglioramento statisticamente significativo rispetto al metodo convenzionale. 2. Cavità orale e orofaringe Un metodo ricostruttivo standard per la cavità orale e l'orofaringe viene descritto. 163 pazienti affetti da cancro della cavità orale e dell'orofaringe, sono stati trattati dal 1992 al 2012 eseguendo un totale di 175 lembi liberi. La strategia chirurgica è descritta in termini di scelta del lembo, modellamento ed insetting. I modelli bidimensionali sono utilizzati per pianificare una ricostruzione tridimensionale con il miglior risultato funzionale ed estetico. I modelli, la scelta del lembo e l' insetting sono descritti per ogni regione. Complicazioni e risultati funzionali sono stati valutati sistematicamente. I risultati hanno mostrato un buon recupero funzionale con le tecniche ricostruttive descritte. Viene proposto un algoritmo ricostruttivo basato su template standard.

Design and Synthesis of Novel Kinase Inhibitors for the Treatment of Chronic Respiratory Diseases

In 2017, Chronic Respiratory Diseases accounted for almost four million deaths worldwide. Unfortunately, current treatments are not definitive for such diseases. This unmet medical need forces the scientific community to increase efforts in the identification of new therapeutic solutions. PI3K delta plays a key role in mechanisms that promote airway chronic inflammation underlying Asthma and COPD. The first part of this project was dedicated to the identification of novel PI3K delta inhibitors. A first SAR expansion of a Hit, previously identified by a HTS campaign, was carried out. A library of 43 analogues was synthesised taking advantage of an efficient synthetic approach. This allowed the identification of an improved Hit of nanomolar enzymatic potency and moderate selectivity for PI3K delta over other PI3K isoforms. However, this compound exhibited low potency in cell-based assays. Low cellular potency was related to sub optimal phys-chem and ADME properties. The analysis of the X-ray crystal structure of this compound in human PI3K delta guided a second tailored SAR expansion that led to improved cellular potency and solubility. The second part of the thesis was focused on the rational design and synthesis of new macrocyclic Rho-associated protein kinases (ROCKs) inhibitors. Inhibition of these kinases has been associated with vasodilating effects. Therefore, ROCKs could represent attractive targets for the treatment of pulmonary arterial hypertension (PAH). Known ROCK inhibitors suffer from low selectivity across the kinome. The design of macrocyclic inhibitors was considered a promising strategy to obtain improved selectivity. Known inhibitors from literature were evaluated for opportunities of macrocyclization using a knowledge-based approach supported by Computer Aided Drug Design (CADD). The identification of a macrocyclic ROCK inhibitor with enzymatic activity in the low micro molar range against ROCK II represented a promising result that validated this innovative approach in the design of new ROCKs inhibitors.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

Modelling, simulations and monitoring for sustainable plant and animal production systems through precision technique

Protected crop production is a modern and innovative approach to cultivating plants in a controlled environment to optimize growth, yield, and quality. This method involves using structures such as greenhouses or tunnels to create a sheltered environment. These productive solutions are characterized by a careful regulation of variables like temperature, humidity, light, and ventilation, which collectively contribute to creating an optimal microclimate for plant growth. Heating, cooling, and ventilation systems are used to maintain optimal conditions for plant growth, regardless of external weather fluctuations. Protected crop production plays a crucial role in addressing challenges posed by climate variability, population growth, and food security. Similarly, animal husbandry involves providing adequate nutrition, housing, medical care and environmental conditions to ensure animal welfare. Then, sustainability is a critical consideration in all forms of agriculture, including protected crop and animal production. Sustainability in animal production refers to the practice of producing animal products in a way that minimizes negative impacts on the environment, promotes animal welfare, and ensures the long-term viability of the industry. Then, the research activities performed during the PhD can be inserted exactly in the field of Precision Agriculture and Livestock farming. Here the focus is on the computational fluid dynamic (CFD) approach and environmental assessment applied to improve yield, resource efficiency, environmental sustainability, and cost savings. It represents a significant shift from traditional farming methods to a more technology-driven, data-driven, and environmentally conscious approach to crop and animal production. On one side, CFD is powerful and precise techniques of computer modeling and simulation of airflows and thermo-hygrometric parameters, that has been applied to optimize the growth environment of crops and the efficiency of ventilation in pig barns. On the other side, the sustainability aspect has been investigated and researched in terms of Life Cycle Assessment analyses.