Cannabinoid system combined to classic targets for a new MTDL strategy: design and synthesis of natural inspired molecules for Alzheimer's disease

In this thesis is described the design and synthesis of potential agents for the treatment of the multifactorial Alzheimer’s disease (AD). Our multi-target approach was to consider cannabinoid system involved in AD, together with classic targets. In the first project, designed modifications were performed on lead molecule in order to increase potency and obtain balanced activities on fatty acid amide hydrolase and cholinesterases. A small library of compounds was synthesized and biological results showed increased inhibitory activity (nanomolar range) related to selected target. The second project was focused on the benzofuran framework, a privileged structure being a common moiety found in many biologically active natural products and therapeutics. Hybrid molecules were designed and synthesized, focusing on the inhibition of cholinesterases, Aβ aggregation, FAAH and on the interaction with CB receptors. Preliminary results showed that several compounds are potent CB ligands, in particular the high affinity for CB2 receptors, could open new opportunities to modulate neuroinflammation. The third and the fourth project were carried out at the IMS, Aberdeen, under the supervision of Prof. Matteo Zanda. The role of the cannabinoid system in the brain is still largely unexplored and the relationship between the CB1 receptors functional modification, density and distribution and the onset of a pathological state is not well understood. For this reasons, Rimonabant analogues suitable as radioligands were synthesized. The latter, through PET, could provide reliable measurements of density and distribution of CB1 receptors in the brain. In the fifth project, in collaboration with CHyM of York, the goal was to develop arginine analogues that are target specific due to their exclusively location into NOS enzymes and could work as MRI contrasting agents. Synthesized analogues could be suitable substrate for the transfer of polarization by p-H2 molecules through SABRE technique transforming MRI a more sensitive and faster technique.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Design and Control of Robotic Hands

The application of dexterous robotic hands out of research laboratories has been limited by the intrinsic complexity that these devices present. This is directly reflected as an economically unreasonable cost and a low overall reliability. Within the research reported in this thesis it is shown how the problem of complexity in the design of robotic hands can be tackled, taking advantage of modern technologies (i.e. rapid prototyping), leading to innovative concepts for the design of the mechanical structure, the actuation and sensory systems. The solutions adopted drastically reduce the prototyping and production costs and increase the reliability, reducing the number of parts required and averaging their single reliability factors. In order to get guidelines for the design process, the problem of robotic grasp and manipulation by a dual arm/hand system has been reviewed. In this way, the requirements that should be fulfilled at hardware level to guarantee successful execution of the task has been highlighted. The contribution of this research from the manipulation planning side focuses on the redundancy resolution that arise in the execution of the task in a dexterous arm/hand system. In literature the problem of coordination of arm and hand during manipulation of an object has been widely analyzed in theory but often experimentally demonstrated in simplified robotic setup. Our aim is to cover the lack in the study of this topic and experimentally evaluate it in a complex system as a anthropomorphic arm hand system.

Analysis and design of high performance multiphase electric drives for vehicle and aircraft applications

The first part of this thesis has focused on the construction of a twelve-phase asynchronous machine for More Electric Aircraft (MEA) applications. In fact, the aerospace world has found in electrification the way to improve the efficiency, reliability and maintainability of an aircraft. This idea leads to the aircraft a new management and distribution of electrical services. In this way is possible to remove or to reduce the hydraulic, mechanical and pneumatic systems inside the aircraft. The second part of this dissertation is dedicated on the enhancement of the control range of matrix converters (MCs) operating with non-unity input power factor and, at the same time, on the reduction of the switching power losses. The analysis leads to the determination in closed form of a modulation strategy that features a control range, in terms of output voltage and input power factor, that is greater than that of the traditional strategies under the same operating conditions, and a reduction in the switching power losses.

Design of a new harrow type wool transport mechanism to reduce fibre entanglement

The wool is entangled at several stages of its processing. In the conventional scouring machines, the prongs or the rakes agitate the wool and lead the fiber entanglement. Several scouring systems have been commercialized in order to reduce the fiber entanglement. In spite of the existing technologies, the conventional scouring machines are widely used in wool processing. In this thesis, a new approach for the harrow type wool transport mechanism has been introduced. The proposed mechanism has been designed based on the motion of the conventional harrow type wool transport mechanism by exploiting new synthesis concepts. The developed structure has been synthesized based on the Hrones and Nelson's "Atlas of four bar linkages". The four bar linkage has been applied for the desired trajectory of the developed wool transport mechanism. The prongs of the developed mechanism immerse the wool into the scouring liquor and gently propel forward toward the end of the machine with approximately straight line motion in a certain length instead of circular or elliptical motion typical of the conventional machines.