Uniquitous internet middleware: architecture design and prototype evaluation

Technology advances in recent years have dramatically changed the way users exploit contents and services available on the Internet, by enforcing pervasive and mobile computing scenarios and enabling access to networked resources almost from everywhere, at anytime, and independently of the device in use. In addition, people increasingly require to customize their experience, by exploiting specific device capabilities and limitations, inherent features of the communication channel in use, and interaction paradigms that significantly differ from the traditional request/response one. So-called Ubiquitous Internet scenario calls for solutions that address many different challenges, such as device mobility, session management, content adaptation, context-awareness and the provisioning of multimodal interfaces. Moreover, new service opportunities demand simple and effective ways to integrate existing resources into new and value added applications, that can also undergo run-time modifications, according to ever-changing execution conditions. Despite service-oriented architectural models are gaining momentum to tame the increasing complexity of composing and orchestrating distributed and heterogeneous functionalities, existing solutions generally lack a unified approach and only provide support for specific Ubiquitous Internet aspects. Moreover, they usually target rather static scenarios and scarcely support the dynamic nature of pervasive access to Internet resources, that can make existing compositions soon become obsolete or inadequate, hence in need of reconfiguration. This thesis proposes a novel middleware approach to comprehensively deal with Ubiquitous Internet facets and assist in establishing innovative application scenarios. We claim that a truly viable ubiquity support infrastructure must neatly decouple distributed resources to integrate and push any kind of content-related logic outside its core layers, by keeping only management and coordination responsibilities. Furthermore, we promote an innovative, open, and dynamic resource composition model that allows to easily describe and enforce complex scenario requirements, and to suitably react to changes in the execution conditions.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Development and optimization of graphic user interfaces (GUIs) for infrared spectrometers at the Telescopio Nazionale Galileo

This Phd thesis was entirely developed at the Telescopio Nazionale Galileo (TNG, Roque de los Muchachos, La Palma Canary Islands) with the aim of designing, developing and implementing a new Graphical User Interface (GUI) for the Near Infrared Camera Spectrometer (NICS) installed on the Nasmyth A of the telescope. The idea of a new GUI for NICS has risen for optimizing the astronomers work through a set of powerful tools not present in the existing GUI, such as the possibility to move automatically, an object on the slit or do a very preliminary images analysis and spectra extraction. The new GUI also provides a wide and versatile image display, an automatic procedure to find out the astronomical objects and a facility for the automatic image crosstalk correction. In order to test the overall correct functioning of the new GUI for NICS, and providing some information on the atmospheric extinction at the TNG site, two telluric standard stars have been spectroscopically observed within some engineering time, namely Hip031303 and Hip031567. The used NICS set-up is as follows: Large Field (0.25'' /pixel) mode, 0.5'' slit and spectral dispersion through the AMICI prism (R~100), and the higher resolution (R~1000) JH and HK grisms.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Advanced SPM studies on the growth of ultrathin films of organic semiconductors at metal and dielectric interfaces

Many studies on the morphology, molecular orientation, device performance, substrate nature and growth parameter dependence have been carried out since the proposal of Sexithiophene (6T) for organic electronics [ ] However, these studies were mostly performed on films thicker than 20nm and without specifically addressing the relationship between morphology and molecular orientation within the nano and micro structures of ultrathin films of 0-3 monolayers. In 2004, the observation that in OFETs only the first few monolayers at the interface in contact with the gate insulator contribute to the charge transport [ ], underlined the importance to study submonolayer films and their evolution up to a few monolayers of thickness with appropriate experimental techniques. We present here a detailed Non-contact Atomic Force Microscopy and Scanning Tunneling Microscopy study on various substrates aiming at the investigation of growth mechanisms. Most reported similar studies are performed on ideal metals in UHV. However it is important to investigate the details of organic film growth on less ideal and even technological surfaces and device testpatterns. The present work addresses the growth of ultra thin organic films in-situ and quasi real-time by NC-AFM. An organic effusion cell is installed to evaporate the organic material directly onto the SPM sample scanning stage.

Advanced CMOS Interfaces for Bio-Nanosensors

The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

Innovative Man Machine Interfaces In Aeronautics

The research activity focused on the study, design and evaluation of innovative human-machine interfaces based on virtual three-dimensional environments. It is based on the brain electrical activities recorded in real time through the electrical impulses emitted by the brain waves of the user. The achieved target is to identify and sort in real time the different brain states and adapt the interface and/or stimuli to the corresponding emotional state of the user. The setup of an experimental facility based on an innovative experimental methodology for “man in the loop" simulation was established. It allowed involving during pilot training in virtually simulated flights, both pilot and flight examiner, in order to compare the subjective evaluations of this latter to the objective measurements of the brain activity of the pilot. This was done recording all the relevant information versus a time-line. Different combinations of emotional intensities obtained, led to an evaluation of the current situational awareness of the user. These results have a great implication in the current training methodology of the pilots, and its use could be extended as a tool that can improve the evaluation of a pilot/crew performance in interacting with the aircraft when performing tasks and procedures, especially in critical situations. This research also resulted in the design of an interface that adapts the control of the machine to the situation awareness of the user. The new concept worked on, aimed at improving the efficiency between a user and the interface, and gaining capacity by reducing the user’s workload and hence improving the system overall safety. This innovative research combining emotions measured through electroencephalography resulted in a human-machine interface that would have three aeronautical related applications: • An evaluation tool during the pilot training; • An input for cockpit environment; • An adaptation tool of the cockpit automation.

Atomistic simulations of liquid crystals in the bulk and at their interfaces

In this thesis, we have dealt with several problems concerning liquid crystals (LC) phases, either in the bulk or at their interfaces, by the use of atomistic molecular dynamics (MD) simulations. We first focused our attention on simulating and characterizing the bulk smectic phase of 4-n-octyl-4'-cyanobiphenyl (8CB), allowing us to investigate the antiparallel molecular arrangement typical of SmAd smectic phases. A second topic of study was the characterization of the 8CB interface with vacuum by simulating freely suspended thin films, which allowed us to determine the influence of the interface on the orientational and positional order. Then we investigated the LC-water and LC-electrolyte water solution interface. This interface has recently found application in the development of sensors for several compounds, including biological molecules, and here we tried to understand the re-orientation mechanism of LC molecules at the interface which is behind the functioning of these sensors. The characterization of this peculiar interface has incidentally led us to develop a polarizable force field for the pentyl-cyanobiphenyl mesogen, whose process of parametrization and validation is reported here in detail. We have shown that this force field is a significant improvement over its previous, static charge non polarizable version in terms of density, orientational order parameter and translational diffusion.

Multimodal (EEG-fMRI) functional connectivity study of levodopa effect in Parkinson’s disease

Aim: To assess if the intake of levodopa in patients with Parkinson’s Disease (PD) changes cerebral connectivity, as revealed by simultaneous recording of hemodynamic (functional MRI, or fMRI) and electric (electroencephalogram, EEG) signals. Particularly, we hypothesize that the strongest changes in FC will involve the motor network, which is the most impaired in PD. Methods: Eight patients with diagnosis of PD “probable”, therapy with levodopa exclusively, normal cognitive and affective status, were included. Exclusion criteria were: moderate-severe rest tremor, levodopa induced dyskinesia, evidence of gray or white matter abnormalities on structural MRI. Scalp EEG (64 channels) were acquired inside the scanner (1.5 Tesla) before and after the intake of levodopa. fMRI functional connectivity was computed from four regions of interest: right and left supplementary motor area (SMA) and right and left precentral gyrus (primary motor cortex). Weighted partial directed coherence (w-PDC) was computed in the inverse space after the removal of EEG gradient and cardioballistic artifacts. Results and discussion: fMRI group analysis shows that the intake of levodopa increases hemodynamic functional connectivity among the SMAs / primary motor cortex and: sensory-motor network itself, attention network and default mode network. w-PDC analysis shows that EEG connectivity among regions of the motor network has the tendency to decrease after the intake the levodopa; furthermore, regions belonging to the DMN have the tendency to increase their outflow toward the rest of the brain. These findings, even if in a small sample of patients, suggest that other resting state physiological functional networks, beyond the motor one, are affected in patients with PD. The behavioral and cognitive tasks corresponding to the affected networks could benefit from the intake of levodopa.

Language, action, and sensoriality: a multimodal analysis of interactions in inclusive sport climbing with visually impaired athletes

In sport climbing, athletes with vision impairments are constantly accompanied by their guides – usually trainers – both during the preparatory inspection of the routes and whilst climbing. Trainers are, so to speak, the climbers’ eyes, in the sense that they systematically put their vision in the service of the climbers’ mobility and sporting performance. The synergy between trainers and athletes is based on peculiar, strictly multimodal interactive practices that are focused on the body and on its constantly evolving sensory engagement with the materiality of routes. In this context, sensory perception and embodied actions required to plan and execute the climb are configured as genuinely interactive accomplishments. Drawing on the theoretical framework of Embodied and Situated Cognition and on the methodology of Conversation Analysis, this thesis engages in the multimodal analysis of trainer-athlete interactions in paraclimbing. The analysis is based on a corpus of video recorded climbing sessions. The major findings of the study can be summarized as follows. 1) Intercorporeality is key to interactions between trainers and athletes with visual impairments. The participants orient to perceiving the climbing space and acting in it as a ‘We’. 2) The grammar, lexicon, prosody, and timing of the trainers’ instructions are finely tuned to the ongoing corporeal experience of the climbers. 3) Climbers with visual impairments build their actions by using sensory resources that are provided by their trainers. This result is of particular importance as it shows that resources and constraints for action are in a fundamental way constituted in interaction with Others and with specific socio-material ecologies, rather than being defined a priori by the organs and functions of individuals’ body and mind. Individual capabilities are thus enhanced and extended in interaction, which encourages a more ecological view of (dis)ability.

“Nanoglial interfaces: nanostructured materials, interfaces and devices to unveil the role of astrocytes in brain function and dysfunction”

The role of non-neuronal brain cells, called astrocytes, is emerging as crucial in brain function and dysfunction, encompassing the neurocentric concept that was envisioning glia as passive components. Ion and water channels and calcium signalling, expressed in functional micro and nano domains, underpin astrocytes’ homeostatic function, synaptic transmission, neurovascular coupling acting either locally and globally. In this respect, a major issue arises on the mechanism through which astrocytes can control processes across scales. Finally, astrocytes can sense and react to extracellular stimuli such as chemical, physical, mechanical, electrical, photonic ones at the nanoscale. Given their emerging importance and their sensing properties, my PhD research program had the general goal to validate nanomaterials, interfaces and devices approaches that were developed ad-hoc to study astrocytes. The results achieved are reported in the form of collection of papers. Specifically, we demonstrated that i) electrospun nanofibers made of polycaprolactone and polyaniline conductive composites can shape primary astrocytes’ morphology, without affecting their function ii) gold coated silicon nanowires devices enable extracellular recording of unprecedented slow wave in primary differentiated astrocytes iii) colloidal hydrotalcites films allow to get insight in cell volume regulation process in differentiated astrocytes and to describe novel cytoskeletal actin dynamics iv) gold nanoclusters represent nanoprobe to trigger astrocytes structure and function v) nanopillars of photoexcitable organic polymer are potential tool to achieve nanoscale photostimulation of astrocytes. The results were achieved by a multidisciplinary team working with national and international collaborators that are listed and acknowledged in the text. Collectively, the results showed that astrocytes represent a novel opportunity and target for Nanoscience, and that Nanoglial interface might help to unveil clues on brain function or represent novel therapeutic approach to treat brain dysfunctions.

Investigating interpreter-mediated interaction in the Chinese bilingual courtroom: Analysis based on a multimodal corpus

This research project is based on the Multimodal Corpus of Chinese Court Interpreting (MUCCCI [mutʃɪ]), a small-scale multimodal corpus on the basis of eight authentic court hearings with Chinese-English interpreting in Mainland China. The corpus has approximately 92,500 word tokens in total. Besides the transcription of linguistic and para-linguistic features, utilizing the facial expression classification rules suggested by Black and Yacoob (1995), MUCCCI also includes approximately 1,200 annotations of facial expressions linked to the six basic types of human emotions, namely, anger, disgust, happiness, surprise, sadness, and fear (Black & Yacoob, 1995). This thesis is an example of conducting qualitative analysis on interpreter-mediated courtroom interactions through a multimodal corpus. In particular, miscommunication events (MEs) and the reasons behind them were investigated in detail. During the analysis, although queries were conducted based on non-verbal annotations when searching for MEs, both verbal and non-verbal features were considered indispensable parts contributing to the entire context. This thesis also includes a detailed description of the compilation process of MUCCCI utilizing ELAN, from data collection to transcription, POS tagging and non-verbal annotation. The research aims at assessing the possibility and feasibility of conducting qualitative analysis through a multimodal corpus of court interpreting. The concept of integrating both verbal and non-verbal features to contribute to the entire context is emphasized. The qualitative analysis focusing on MEs can provide an inspiration for improving court interpreters’ performances. All the constraints and difficulties presented can be regarded as a reference for similar research in the future.

Theoretical and experimental study of novel hybrid composite and metal-composites interfaces

The growing demand for lightweight solutions in every field of engineering is driving the industry to seek new technological solutions to exploit the full potential of different materials. The combination of dissimilar materials with distinct property ranges embodies a transparent allocation of component functions while allowing an optimal mix of their characteristics. From both technological and design perspectives, the interaction between dissimilar materials can lead to severe defects that compromise a multi-material hybrid component's performance and its structural integrity. This thesis aims to develop methodologies for designing, manufacturing, and monitoring of hybrid metal-composite joints and hybrid composite components. In Chapter 1, a methodology for designing and manufacturing hybrid aluminum/composite co-cured tubes is assessed. In Chapter 2, a full-field methodology for fiber misalignment detection and stiffness prediction for hybrid, long fiber reinforced composite systems is shown and demonstrated. Chapter 3 reports the development of a novel technology for joining short fiber systems and metals in a one-step co-curing process using lattice structures. Chapter 4 is dedicated to a novel analytical framework for the design optimization of two lattice architectures.

Investigation of organic semiconductor/water interfaces for optobioelectronic devices

The thesis investigates the potential of photoactive organic semiconductors as a new class of materials for developing bioelectronic devices that can convert light into biological signals. The materials can be either small molecules or polymers. When these materials interact with aqueous biological fluids, they give rise to various electrochemical phenomena, including photofaradaic or photocapacitive processes, depending on whether photogenerated charges participate in redox processes or accumulate at an interface. The thesis starts by studying the behavior of the H2Pc/PTCDI molecular p/n thin-film heterojunction in contact with aqueous electrolyte. An equivalent circuit model is developed, explaining the measurements and predicting behavior in wireless mode. A systematic study on p-type polymeric thin-films is presented, comparing rr-P3HT with two low bandgap conjugated polymers: PBDB-T and PTB7. The results demonstrate that PTB7 has superior photocurrent performance due to more effective electron-transfer onto acceptor states in solution. Furthermore, the thesis addresses the issue of photovoltage generation for wireless photoelectrodes. An analytical model based on photoactivated charge-transfer across the organic-semiconductor/water interface is developed, explaining the large photovoltages observed for polymeric p-type semiconductor electrodes in water. Then, flash-precipitated nanoparticles made of the same three photoactive polymers are investigated, assessing the influence of fabrication parameters on the stability, structure, and energetics of the nanoparticles. Photocathodic current generation and consequent positive charge accumulation is also investigated. Additionally, newly developed porous P3HT thin-films are tested, showing that porosity increases both the photocurrent and the semiconductor/water interfacial capacity. Finally, the thesis demonstrates the biocompatibility of the materials in in-vitro experiments and shows safe levels of photoinduced intracellular ROS production with p-type polymeric thin-films and nanoparticles. The findings highlight the potential of photoactive organic semiconductors in the development of optobioelectronic devices, demonstrating their ability to convert light into biological signals and interface with biological fluids.