Representation theorems for indefinite quadratic forms and applications

Diese Arbeit widmet sich den Darstellungssätzen für symmetrische indefinite (das heißt nicht-halbbeschränkte) Sesquilinearformen und deren Anwendungen. Insbesondere betrachten wir den Fall, dass der zur Form assoziierte Operator keine Spektrallücke um Null besitzt. Desweiteren untersuchen wir die Beziehung zwischen reduzierenden Graphräumen, Lösungen von Operator-Riccati-Gleichungen und der Block-Diagonalisierung für diagonaldominante Block-Operator-Matrizen. Mit Hilfe der Darstellungssätze wird eine entsprechende Beziehung zwischen Operatoren, die zu indefiniten Formen assoziiert sind, und Form-Riccati-Gleichungen erreicht. In diesem Rahmen wird eine explizite Block-Diagonalisierung und eine Spektralzerlegung für den Stokes Operator sowie eine Darstellung für dessen Kern erreicht. Wir wenden die Darstellungssätze auf durch (grad u, h() grad v) gegebene Formen an, wobei Vorzeichen-indefinite Koeffzienten-Matrizen h() zugelassen sind. Als ein Resultat werden selbstadjungierte indefinite Differentialoperatoren div h() grad mit homogenen Dirichlet oder Neumann Randbedingungen konstruiert. Beispiele solcher Art sind Operatoren die in der Modellierung von optischen Metamaterialien auftauchen und links-indefinite Sturm-Liouville Operatoren.

The Feynman-Kac formula and applications to PDEs

The thesis presents a probabilistic approach to the theory of semigroups of operators, with particular attention to the Markov and Feller semigroups. The first goal of this work is the proof of the fundamental Feynman-Kac formula, which gives the solution of certain parabolic Cauchy problems, in terms of the expected value of the initial condition computed at the associated stochastic diffusion processes. The second target is the characterization of the principal eigenvalue of the generator of a semigroup with Markov transition probability function and of second order elliptic operators with real coefficients not necessarily self-adjoint. The thesis is divided into three chapters. In the first chapter we study the Brownian motion and some of its main properties, the stochastic processes, the stochastic integral and the Itô formula in order to finally arrive, in the last section, at the proof of the Feynman-Kac formula. The second chapter is devoted to the probabilistic approach to the semigroups theory and it is here that we introduce Markov and Feller semigroups. Special emphasis is given to the Feller semigroup associated with the Brownian motion. The third and last chapter is divided into two sections. In the first one we present the abstract characterization of the principal eigenvalue of the infinitesimal generator of a semigroup of operators acting on continuous functions over a compact metric space. In the second section this approach is used to study the principal eigenvalue of elliptic partial differential operators with real coefficients. At the end, in the appendix, we gather some of the technical results used in the thesis in more details. Appendix A is devoted to the Sion minimax theorem, while in appendix B we prove the Chernoff product formula for not necessarily self-adjoint operators.

Fractal sets and their applications in medicine

La geometria euclidea risulta spesso inadeguata a descrivere le forme della natura. I Frattali, oggetti interrotti e irregolari, come indica il nome stesso, sono più adatti a rappresentare la forma frastagliata delle linee costiere o altri elementi naturali. Lo strumento necessario per studiare rigorosamente i frattali sono i teoremi riguardanti la misura di Hausdorff, con i quali possono definirsi gli s-sets, dove s è la dimensione di Hausdorff. Se s non è intero, l'insieme in gioco può riconoscersi come frattale e non presenta tangenti e densità in quasi nessun punto. I frattali più classici, come gli insiemi di Cantor, Koch e Sierpinski, presentano anche la proprietà di auto-similarità e la dimensione di similitudine viene a coincidere con quella di Hausdorff. Una tecnica basata sulla dimensione frattale, detta box-counting, interviene in applicazioni bio-mediche e risulta utile per studiare le placche senili di varie specie di mammiferi tra cui l'uomo o anche per distinguere un melanoma maligno da una diversa lesione della cute.

Mobile phone technologies and advanced data analysis towards the enhancement of diabetes self-management

Advances in the area of mobile and wireless communication for healthcare (m-Health) along with the improvements in information science allow the design and development of new patient-centric models for the provision of personalised healthcare services, increase of patient independence and improvement of patient's self-control and self-management capabilities. This paper comprises a brief overview of the m-Health applications towards the self-management of individuals with diabetes mellitus and the enhancement of their quality of life. Furthermore, the design and development of a mobile phone application for Type 1 Diabetes Mellitus (T1DM) self-management is presented. The technical evaluation of the application, which permits the management of blood glucose measurements, blood pressure measurements, insulin dosage, food/drink intake and physical activity, has shown that the use of the mobile phone technologies along with data analysis methods might improve the self-management of T1DM.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.

PMMA-CNT matrices for vacuum electronic, biosensing and energy applications

Carbon nanotubes (CNTs) are interesting materials with extraordinary properties for various applications. Here, vertically-aligned multiwalled CNTs (VA-MWCNTs) are grown by our dual radio frequency plasma enhanced chemical vapor deposition (PECVD). After optimizing the synthesis processes, these VA-MWCNTs were fabricated in to a series of devices for applications in vacuum electronics, glucose biosensors, glucose biofuel cells, and supercapacitors In particular, we have created the so-called PMMA-CNT matrices (opened-tip CNTs embedded in poly-methyl methacrylate) that are promising components in a novel energy sensing, generation and storage (SGS) system that integrate glucose biosensors, biofuel cells, and supercapacitors. The content of this thesis work is described as follows: 1. We have first optimized the synthesis of VA-MWCNTs by our PECVD technique. The effects of CH4 flow rate and growth duration on the lengths of these CNTs were studied. 2. We have characterized these VA-MWCNTs for electron field emission. We noticed that as grown CNTs suffers from high emission threshold, poor emission density and poor long-term stability. We attempted a series of experiments to understand ways to overcome these problems. First, we decrease the screening effects on VA-MWCNTs by creating arrays of self-assembled CNT bundles that are catalyst-free and opened tips. These bundles are found to enhance the field emission stability and emission density. Subsequently, we have created PMMA-CNT matrices that are excellent electron field emitters with an emission threshold field of more than two-fold lower than that of the as-grown sample. Furthermore, no significant emission degradation was observed after a continuous emission test of 40 hours (versus much shorter tests in reported literatures). Based on the new understanding we learnt from the PMMA-CNT matrices, we further created PMMA-STO-CNT matrices by embedding opened-tip VA-MWCNTs that are coated with strontium titanate (SrTiO3) with PMMA. We found that the PMMA-STO-CNT matrices have all the desired properties of the PMMA-CNT matrices. Furthermore, PMMA-STO-CNT matrices offer much lower emission threshold field, about five-fold lower than that of as grown VA-MWCNTs. The new understandings we obtained are important for practical application of VA-MWCNTs in field emission devices. 3. Subsequently, we have functionalized PMMA-CNT matrices for glucose biosensing. Our biosensor was developed by immobilized glucose oxidase (GOχ) on the opened-tip CNTs exposed on the matrices. The durability, stability and sensitivity of the biosensor were studied. In order to understand the performance of miniaturized glucose biosensors, we have then investigated the effect of working electrode area on the sensitivity and current level of our biosensors. 4. Next, functionalized PMMA-CNT matrices were utilized for energy generation and storage. We found that PMMA-CNT matrices are promising component in glucose/O2 biofuel cells (BFCs) for energy generation. The construction of these BFCs and the effect of the electrode area on the power density of these BFCs were investigated. Then, we have attempted to use PMMA-CNT matrices as supercapacitors for energy storage devices. The performance of these supercapacitors and ways to enhance their performance are discussed. 5. Finally, we further evaluated the concept of energy SGS system that integrated glucose biosensors, biofuel cells, and supercapacitors. This SGS system may be implantable to monitor and control the blood glucose level in our body.

Boron nitride nanotubes : synthesis, characterization, functionalization, and potential applications

Boron nitride nanotubes (BNNTs) are structurally similar to carbon nanotubes (CNTs), but exhibit completely different physical and chemical properties. Thus, BNNTs with various interesting properties may be complementary to CNTs and provide an alternative perspective to be useful in different applications. However, synthesis of high quality of BNNTs is still challenging. Hence, the major goals of this research work focus on the fundamental study of synthesis, characterizations, functionalization, and explorations of potential applications. In this work, we have established a new growth vapor trapping (GVT) approach to produce high quality and quantity BNNTs on a Si substrate, by using a conventional tube furnace. This chemical vapor deposition (CVD) approach was conducted at a growth temperature of 1200 °C. As compared to other known approaches, our GVT technique is much simpler in experimental setup and requires relatively lower growth temperatures. The as-grown BNNTs are fully characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), Energy Filtered Mapping, Raman spectroscopy, Fourier Transform Infra Red spectroscopy (FTIR), UV-Visible (UV-vis) absorption spectroscopy, etc. Following this success, the growth of BNNTs is now as convenient as growing CNTs and ZnO nanowires. Some important parameters have been identified to produce high-quality BNNTs on Si substrates. Furthermore, we have identified a series of effective catalysts for patterned growth of BNNTs at desirable or pre-defined locations. This catalytic CVD technique is achieved based on our finding that MgO, Ni or Fe are the good catalysts for the growth of BNNTs. The success of patterned growth not only explains the role of catalysts in the formation of BNNTs, this technique will also become technologically important for future device fabrication of BNNTs. Following our success in controlled growth of BNNTs on substrates, we have discovered the superhydrophobic behavior of these partially vertically aligned BNNTs. Since BNNTs are chemically inert, resistive to oxidation up to ~1000°C, and transparent to UV-visible light, our discovery suggests that BNNTs could be useful as self-cleaning, insulating and protective coatings under rigorous chemical and thermal conditions. We have also established various approaches to functionalize BNNTs with polymeric molecules and carbon coatings. First, we showed that BNNTs can be functionalized by mPEG-DSPE (Polyethylene glycol-1,2-distearoyl-sn-glycero-3-phosphoethanolamine), a bio-compatible polymer that helps disperse and dissolve BNNTs in water solution. Furthermore, well-dispersed BNNTs in water can be cut from its original length of >10µm to(>20hrs). This success is an essential step to implement BNNTs in biomedical applications. On the other hand, we have also succeeded to functionalize BNNTs with various conjugated polymers. This success enables the dispersion of BNNTs in organic solvents instead of water. Our approaches are useful for applications of BNNTs in high-strength composites. In addition, we have also functionalized BNNTs with carbon decoration. This was performed by introducing methane (CH4) gas into the growth process of BNNT. Graphitic carbon coatings can be deposited on the side wall of BNNTs with thicknesses ranging from 2 to 5 nm. This success can modulate the conductivity of pure BNNTs from insulating to weakly electrically conductive. Finally, efforts were devoted to explore the application of the wide bandgap BNNTs in solar-blind deep UV (DUV) photo-detectors. We found that photoelectric current generated by the DUV light was dominated in the microelectrodes of our devices. The contribution of photocurrent from BNNTs is not significant if there is any. Implication from these preliminary experiments and potential future work are discussed.

Microfluidic hydrogen generator : featuring passive on-demand gas generation and self-circulated reactant for integration with micro fuel cell

A microfluidic hydrogen generator is presented in this work. Its fabrication, characterization, and integration with a micro proton exchange membrane (PEM) fuel cell are described. Hydrogen gas is generated by the hydrolysis of aqueous ammonia borane. Gas generation, as well as the circulation of ammonia borane from a rechargeable fuel reservoir, is performed without any power consumption. To achieve this, directional growth and selective venting of hydrogen gas is maintained in the microchannels, which results in the circulation of fresh reactant from the fuel reservoir. In addition to this self-circulation mechanism, the hydrogen generator has been demonstrated to self-regulate gas generation to meet demands of a connected micro fuel cell. All of this is done without parasitic power consumption from the fuel cell. Results show its feasibility in applications of high-impedance systems. Lastly, recommendations for improvements and suggestions for future work are described

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Self-Reported Capabilities Among Young Male Adults in Switzerland: Translation and Psychometric Evaluation of a German, French and Italian Version of a Closed Survey Instrument

There is a shortage of empirical applications of the capability approach that employ closed survey instruments to assess self-reported capabilities. However, for those few instruments that have been designed and administered through surveys until now, no psychometric properties (reliability, validity, and factor structure) were reported. The purpose of this study is the assessment of the psychometric properties of three new language versions (German, French, and Italian) of an established (English) set of eight self-reported capability items. The set of items is taken from a previously published British study by Anand and van Hees (J Soc Econ 35(2):268–284, 2006). Our sample consists of 17,152 young male adults aged 18–25 years from the three major language regions in Switzerland. The results indicate good reliability of the three language versions. The results from the exploratory factor analyses suggest a one-dimensional factor structure for seven domain specific items. Furthermore, the results from multiple regression analyses suggest that a global summary item on overall capabilities represents a measurement alternative to the set of seven domain specific capability items. Finally, the results confirm the applicability of the closed capability instrument in a large scale survey questionnaire and represent the first attempt to measure self-reported capabilities in Switzerland.

Self-dual continuous processes

The important application of semi-static hedging in financial markets naturally leads to the notion of conditionally quasi self-dual processes which is, for continuous semimartingales, related to conditional symmetry properties of both their ordinary as well as their stochastic logarithms. We provide a structure result for continuous conditionally quasi self-dual processes. Our main result is to give a characterization of continuous Ocone martingales via a strong version of self-duality.

Direct metabolites of Ethanol as biological markers of alcohol use: Basic aspects and applications

In addition to self reports and questionnaires, biomarkers are of relevance in the diagnosis of and therapy for alcohol use disorders. Traditional biomarkers such as gamma-glutamyl transpeptidase or mean corpuscular volume are indirect biomarkers and are subject to the influence of age, gender and non-alcohol related diseases, among others. Direct metabolites of ethanol such as Ethyl glucuronide (EtG), ethyl sulphate (EtS) and phosphatidylethanol (PEth) are direct metabolites of ethanol, that are positive after intake of ethyl alcohol. They represent useful diagnostic tools for identifying alcohol use even more accurately than traditional biomarkers. Each of these drinking indicators remains positive in serum and urine for a characteristic time spectrum after the cessation of ethanol intake - EtG and EtS in urine up to 7 days, EtG in hair for months after ethanol has left the body. Applications include clinical routine use, emergency room settings, proof of abstinence in alcohol rehabilitation programmes, driving under influence offenders, workplace testing, assessment of alcohol intake in the context of liver transplantation and foetal alcohol syndrome. Due to their properties, they open up new perspectives for prevention, interdisciplinary cooperation, diagnosis of and therapy for alcohol-related problems.