Cache-aware development of high integrity real-time systems

Cost, performance and availability considerations are forcing even the most conservative high-integrity embedded real-time systems industry to migrate from simple hardware processors to ones equipped with caches and other acceleration features. This migration disrupts the practices and solutions that industry had developed and consolidated over the years to perform timing analysis. Industry that are confident with the efficiency/effectiveness of their verification and validation processes for old-generation processors, do not have sufficient insight on the effects of the migration to cache-equipped processors. Caches are perceived as an additional source of complexity, which has potential for shattering the guarantees of cost- and schedule-constrained qualification of their systems. The current industrial approach to timing analysis is ill-equipped to cope with the variability incurred by caches. Conversely, the application of advanced WCET analysis techniques on real-world industrial software, developed without analysability in mind, is hardly feasible. We propose a development approach aimed at minimising the cache jitters, as well as at enabling the application of advanced WCET analysis techniques to industrial systems. Our approach builds on:(i) identification of those software constructs that may impede or complicate timing analysis in industrial-scale systems; (ii) elaboration of practical means, under the model-driven engineering (MDE) paradigm, to enforce the automated generation of software that is analyzable by construction; (iii) implementation of a layout optimisation method to remove cache jitters stemming from the software layout in memory, with the intent of facilitating incremental software development, which is of high strategic interest to industry. The integration of those constituents in a structured approach to timing analysis achieves two interesting properties: the resulting software is analysable from the earliest releases onwards - as opposed to becoming so only when the system is final - and more easily amenable to advanced timing analysis by construction, regardless of the system scale and complexity.

Enabling a direct path from end-user specifications to executable protocols in a biology laboratory environment

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.

Development of control-oriented models of Dual Clutch Transmission systems

A control-oriented model of a Dual Clutch Transmission was developed for real-time Hardware In the Loop (HIL) applications, to support model-based development of the DCT controller. The model is an innovative attempt to reproduce the fast dynamics of the actuation system while maintaining a step size large enough for real-time applications. The model comprehends a detailed physical description of hydraulic circuit, clutches, synchronizers and gears, and simplified vehicle and internal combustion engine sub-models. As the oil circulating in the system has a large bulk modulus, the pressure dynamics are very fast, possibly causing instability in a real-time simulation; the same challenge involves the servo valves dynamics, due to the very small masses of the moving elements. Therefore, the hydraulic circuit model has been modified and simplified without losing physical validity, in order to adapt it to the real-time simulation requirements. The results of offline simulations have been compared to on-board measurements to verify the validity of the developed model, that was then implemented in a HIL system and connected to the TCU (Transmission Control Unit). Several tests have been performed: electrical failure tests on sensors and actuators, hydraulic and mechanical failure tests on hydraulic valves, clutches and synchronizers, and application tests comprehending all the main features of the control performed by the TCU. Being based on physical laws, in every condition the model simulates a plausible reaction of the system. The first intensive use of the HIL application led to the validation of the new safety strategies implemented inside the TCU software. A test automation procedure has been developed to permit the execution of a pattern of tests without the interaction of the user; fully repeatable tests can be performed for non-regression verification, allowing the testing of new software releases in fully automatic mode.

Preparation and characterization of multifunctional bio-based polymers exhibiting enhanced properties

Driven by environmental reasons and the expected depletion of crude oil, bio-based polymers are currently undergoing a renaissance in the attempt to replace fossil-based ones. The present work aims at contributing in the development of the steps that start from biomass and move to new polymeric multifunctional materials. The study focuses on two bio-based building blocks (itaconic and vanillic acids) characterized by exploitable functionalities, i.e. a lateral double bond and a substituted aromatic ring respectively, able to confer interesting properties to the final polymers. The lateral double bond of dimethyl itaconate was functionalized via thia-Michael addition reaction obtaining a thermo-stable building block that can undergo polycondensation under classical conditions of reaction. The addition of a long lateral chain allows the polymer to express antimicrobial activity against Staphylococcus aureus making it attractive for packaging and targeting antimicrobial applications. Moreover, the architecture of the homopolymer was modified by means of copolymerization with dimethyl 2,5-furandicarboxylate thus improving the rigidity and obtaining a thermo-processable material. Potential applications as thermoset or thermoplastic material have been discussed. As concerns vanillic acid, the presence of aromatic rings on the polymer backbone imparts high thermal stability, but brittle behaviour in the homopolymer. Therefore, the architecture of the polyester was successfully tuned by means of copolymerization with a flexible bio-based comonomer, i.e. ω-pentadecalactone, providing processable random copolymers. An in depth investigation of water transport mechanism has been undertaken on the synthesized polyesters. Since the copolymers present a succession of aromatic and aliphatic units, as a consequence of the chemical structure water vapor permeability interposes between polyethylene and poly(ethylene terephthalate) proving that the copolyesters are suitable for packaging applications. Moving towards a sustainable model of development, novel sustainable synthetic pathways for the eco-design of new bio-based polymeric structures with high value functionalities and different potential applications have been successfully developed.

Techniques for Lagrangian modelling of dispersion in geophysical flows

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.

Variational and learning models for image and time series inverse problems

Inverse problems are at the core of many challenging applications. Variational and learning models provide estimated solutions of inverse problems as the outcome of specific reconstruction maps. In the variational approach, the result of the reconstruction map is the solution of a regularized minimization problem encoding information on the acquisition process and prior knowledge on the solution. In the learning approach, the reconstruction map is a parametric function whose parameters are identified by solving a minimization problem depending on a large set of data. In this thesis, we go beyond this apparent dichotomy between variational and learning models and we show they can be harmoniously merged in unified hybrid frameworks preserving their main advantages. We develop several highly efficient methods based on both these model-driven and data-driven strategies, for which we provide a detailed convergence analysis. The arising algorithms are applied to solve inverse problems involving images and time series. For each task, we show the proposed schemes improve the performances of many other existing methods in terms of both computational burden and quality of the solution. In the first part, we focus on gradient-based regularized variational models which are shown to be effective for segmentation purposes and thermal and medical image enhancement. We consider gradient sparsity-promoting regularized models for which we develop different strategies to estimate the regularization strength. Furthermore, we introduce a novel gradient-based Plug-and-Play convergent scheme considering a deep learning based denoiser trained on the gradient domain. In the second part, we address the tasks of natural image deblurring, image and video super resolution microscopy and positioning time series prediction, through deep learning based methods. We boost the performances of supervised, such as trained convolutional and recurrent networks, and unsupervised deep learning strategies, such as Deep Image Prior, by penalizing the losses with handcrafted regularization terms.

Crashworthiness and composite materials: development of an experimental test method for the energy absorption determination and implementation of the relative numerical model

In this PhD thesis the crashworthiness topic is studied with the perspective of the development of a small-scale experimental test able to characterize a material in terms of energy absorption. The material properties obtained are then used to validate a nu- merical model of the experimental test itself. Consequently, the numerical model, calibrated on the specific ma- terial, can be extended to more complex structures and used to simulate their energy absorption behavior. The experimental activity started at University of Washington in Seattle, WA (USA) and continued at Second Faculty of Engi- neering, University of Bologna, Forl`ı (Italy), where the numerical model for the simulation of the experimental test was implemented and optimized.

Effect of loss of CDKL5 on brain development in a new Cdkl5 knockout mouse model

Rett's Syndrome (RTT) is a severe neurodevelopmental disorder, characterized by cognitive disability that appears in the first months/years of life. Recently, mutations in the X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have been detected in RTT patients characterized by early-onset seizures. CDKL5 is highly expressed in the brain starting from early postnatal stages to adulthood, suggesting the importance of this kinase for proper brain maturation and function. However, the role/s of CDKL5 in brain development and the molecular mechanisms whereby CDKL5 exerts its effects are still largely unknown. In order to characterize the role of CDKL5 on brain development, we created a mice carrying a targeted conditional knockout allele of Cdkl5. A first behavioral characterization shows that Cdkl5 knockout mice recapitulate several features that mimic the clinical features described in CDKL5 patients and are a useful tool to investigate phenotypic and functional aspects of Cdkl5 loss. We used the Cdkl5 knockout mouse model to dissect the role of CDKL5 on hippocampal development and to establish the mechanism/s underlying its actions. We found that Cdkl5 knockout mice showed increased precursor cell proliferation in the hippocampal dentate gyrus. Interestingly, this region was also characterized by an increased rate of apoptotic cell death that caused a reduction in the final neuron number in spite of the proliferation increase. Moreover, loss of Cdkl5 led to decreased dendritic development of new generated granule cells. Finally, we identified the Akt/GSK3-beta signaling as a target of Cdkl5 in the regulation of neuronal precursor proliferation, survival and maturation. Overall our findings highlight a critical role of CDKL5/AKT/GSK3-beta signaling in the control of neuron proliferation, survival and differentiation and suggest that CDKL5-related alterations of these processes during brain development underlie the neurological symptoms of the CDKL5 variant of RTT.

The porcine animal model goes through the 3Rs: development of in vitro and ex vivo system to study vascular biology

Since the publication of the book of Russell and Burch in 1959, scientific research has never stopped improving itself with regard to the important issue of animal experimentation. The European Directive 2010/63/EU “On the protection of animals used for scientific purposes” focuses mainly on the animal welfare, fixing the Russell and Burch’s 3Rs principles as the foundations of the document. In particular, the legislator clearly states the responsibility of the scientific community to improve the number of alternative methods to animal experimentation. The swine is considered a species of relevant interest for translational research and medicine due to its biological similarities with humans. The surgical community has, in fact, recognized the swine as an excellent model replicating the human cardiovascular system. There have been several wild-type and transgenic porcine models which were produced for biomedicine and translational research. Among these, the cardiovascular ones are the most represented. The continuous involvement of the porcine animal model in the biomedical research, as the continuous advances achieved using swine in translational medicine, support the need for alternative methods to animal experimentation involving pigs. The main purpose of the present work was to develop and characterize novel porcine alternative methods for cardiovascular translational biology/medicine. The work was mainly based on two different models: the first consisted in an ex vivo culture of porcine aortic cylinders and the second consisted in an in vitro culture of porcine aortic derived progenitor cells. Both the models were properly characterized and results indicated that they could be useful to the study of vascular biology. Nevertheless, both the models aim to reduce the use of experimental animals and to refine animal based-trials. In conclusion, the present research aims to be a small, but significant, contribution to the important and necessary field of study of alternative methods to animal experimentation.

Kinematics and statics of cable-driven parallel robots by interval-analysis-based methods

In the past two decades the work of a growing portion of researchers in robotics focused on a particular group of machines, belonging to the family of parallel manipulators: the cable robots. Although these robots share several theoretical elements with the better known parallel robots, they still present completely (or partly) unsolved issues. In particular, the study of their kinematic, already a difficult subject for conventional parallel manipulators, is further complicated by the non-linear nature of cables, which can exert only efforts of pure traction. The work presented in this thesis therefore focuses on the study of the kinematics of these robots and on the development of numerical techniques able to address some of the problems related to it. Most of the work is focused on the development of an interval-analysis based procedure for the solution of the direct geometric problem of a generic cable manipulator. This technique, as well as allowing for a rapid solution of the problem, also guarantees the results obtained against rounding and elimination errors and can take into account any uncertainties in the model of the problem. The developed code has been tested with the help of a small manipulator whose realization is described in this dissertation together with the auxiliary work done during its design and simulation phases.