Analysis of the nuclear properties of Brightest Cluster Galaxies and comparison with "normal" radio galaxies.

The aim of this PhD thesis is the study of the nuclear properties of radio loud AGN. Multiple and/or recent mergers in the host galaxy and/or the presence of cool core in galaxy clusters can play a role in the formation and evolution of the radio source. Being a unique class of objects (Lin & Mohr 2004), we focus on Brightest Cluster Galaxies (BCGs). We investigate their parsec scale radio emission with VLBI (Very Long Baseline Interferometer) observations. From literature or new data , we collect and analyse VLBA (Very Long Baseline) observations at 5 GHz of a complete sample of BCGs and ``normal'' radio galaxies (Bologna Complete Sample , BCS). Results on nuclear properties of BCGs are coming from the comparison with the results for the Bologna COmplete Sample (BCS). Our analysis finds a possible dichotomy between BCGs in cool-core clusters and those in non-cool-core clusters. Only one-sided BCGs have similar kinematic properties with FRIs. Furthermore, the dominance of two-sided jet structures only in cooling clusters suggests sub-relativistic jet velocities. The different jet properties can be related to a different jet origin or to the interaction with a different ISM. We larger discuss on possible explanation of this.

Statistical analysis and simulation techniques in wall-bounded turbulence

The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.

Analysis of the memory B cell response against glycoconjugate vaccines

The development of vaccines directed against polysaccharide capsules of S. pneumoniae, H. influenzae and N. meningitidis have been of great importance in preventing potentially fatal infections. Bacterial capsular polysaccharides are T-cell-independent antigens that induce specific antibody response characterized by IgM immunoglobulins, with a very low IgG class switched response and lack of capability of inducing a booster response. The inability of pure polysaccharides to induce sustained immune responses has required the development of vaccines containing polysaccharides conjugated to a carrier protein, with the aim to generate T cell help. It is clear that the immunogenicity of glycoconjugate vaccines can vary depending on different factors, e.g. chemical nature of the linked polysaccharide, carrier protein, age of the target population, adjuvant used. The present study analyzes the memory B cell (MBC) response to the polysaccharide and to the carrier protein following vaccination with a glycoconjugate vaccine for the prevention of Group B streptococcus (GBS) infection. Not much is known about the role of adjuvants in the development of immunological memory raised against GBS polysaccharides, as well as about the influence of having a pre-existing immunity against the carrier protein on the B cell response raised against the polysaccharide component of the vaccine. We demonstrate in the mouse model that adjuvants can increase the antibody and memory B cell response to the carrier protein and to the conjugated polysaccharide. We also demonstrate that a pre-existing immunity to the carrier protein favors the development of the antibody and memory B cell response to subsequent vaccinations with a glycoconjugate, even in absence of adjuvants. These data provide a useful insight for a better understanding of the mechanism of action of this class of vaccines and for designing the best vaccine that could result in a productive and long lasting memory response.

Pyrolysis-Gas Chromatography-Mass Spectometry and Chemometric Analysis for the Characterization of Complex Matrices

The present PhD thesis was focused on the development and application of chemical methodology (Py-GC-MS) and data-processing method by multivariate data analysis (chemometrics). The chromatographic and mass spectrometric data obtained with this technique are particularly suitable to be interpreted by chemometric methods such as PCA (Principal Component Analysis) as regards data exploration and SIMCA (Soft Independent Models of Class Analogy) for the classification. As a first approach, some issues related to the field of cultural heritage were discussed with a particular attention to the differentiation of binders used in pictorial field. A marker of egg tempera the phosphoric acid esterified, a pyrolysis product of lecithin, was determined using HMDS (hexamethyldisilazane) rather than the TMAH (tetramethylammonium hydroxide) as a derivatizing reagent. The validity of analytical pyrolysis as tool to characterize and classify different types of bacteria was verified. The FAMEs chromatographic profiles represent an important tool for the bacterial identification. Because of the complexity of the chromatograms, it was possible to characterize the bacteria only according to their genus, while the differentiation at the species level has been achieved by means of chemometric analysis. To perform this study, normalized areas peaks relevant to fatty acids were taken into account. Chemometric methods were applied to experimental datasets. The obtained results demonstrate the effectiveness of analytical pyrolysis and chemometric analysis for the rapid characterization of bacterial species. Application to a samples of bacterial (Pseudomonas Mendocina), fungal (Pleorotus ostreatus) and mixed- biofilms was also performed. A comparison with the chromatographic profiles established the possibility to: • Differentiate the bacterial and fungal biofilms according to the (FAMEs) profile. • Characterize the fungal biofilm by means the typical pattern of pyrolytic fragments derived from saccharides present in the cell wall. • Individuate the markers of bacterial and fungal biofilm in the same mixed-biofilm sample.

Analysis of optimal control problems for the incompressible MHD equations and implementation in a finite element multiphysics code

This thesis deals with the study of optimal control problems for the incompressible Magnetohydrodynamics (MHD) equations. Particular attention to these problems arises from several applications in science and engineering, such as fission nuclear reactors with liquid metal coolant and aluminum casting in metallurgy. In such applications it is of great interest to achieve the control on the fluid state variables through the action of the magnetic Lorentz force. In this thesis we investigate a class of boundary optimal control problems, in which the flow is controlled through the boundary conditions of the magnetic field. Due to their complexity, these problems present various challenges in the definition of an adequate solution approach, both from a theoretical and from a computational point of view. In this thesis we propose a new boundary control approach, based on lifting functions of the boundary conditions, which yields both theoretical and numerical advantages. With the introduction of lifting functions, boundary control problems can be formulated as extended distributed problems. We consider a systematic mathematical formulation of these problems in terms of the minimization of a cost functional constrained by the MHD equations. The existence of a solution to the flow equations and to the optimal control problem are shown. The Lagrange multiplier technique is used to derive an optimality system from which candidate solutions for the control problem can be obtained. In order to achieve the numerical solution of this system, a finite element approximation is considered for the discretization together with an appropriate gradient-type algorithm. A finite element object-oriented library has been developed to obtain a parallel and multigrid computational implementation of the optimality system based on a multiphysics approach. Numerical results of two- and three-dimensional computations show that a possible minimum for the control problem can be computed in a robust and accurate manner.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Inverse Static Analysis of Massive Parallel Arrays of Three-State Actuators via Artificial Intelligence

Massive parallel robots (MPRs) driven by discrete actuators are force regulated robots that undergo continuous motions despite being commanded through a finite number of states only. Designing a real-time control of such systems requires fast and efficient methods for solving their inverse static analysis (ISA), which is a challenging problem and the subject of this thesis. In particular, five Artificial intelligence methods are proposed to investigate the on-line computation and the generalization error of ISA problem of a class of MPRs featuring three-state force actuators and one degree of revolute motion.

Hydrodynamic induced by an array of wave energy converters. Experimental and numerical analysis

The thesis analyses the hydrodynamic induced by an array of Wave energy Converters (WECs), under an experimental and numerical point of view. WECs can be considered an innovative solution able to contribute to the green energy supply and –at the same time– to protect the rear coastal area under marine spatial planning considerations. This research activity essentially rises due to this combined concept. The WEC under exam is a floating device belonging to the Wave Activated Bodies (WAB) class. Experimental data were performed at Aalborg University in different scales and layouts, and the performance of the models was analysed under a variety of irregular wave attacks. The numerical simulations performed with the codes MIKE 21 BW and ANSYS-AQWA. Experimental results were also used to calibrate the numerical parameters and/or to directly been compared to numerical results, in order to extend the experimental database. Results of the research activity are summarized in terms of device performance and guidelines for a future wave farm installation. The device length should be “tuned” based on the local climate conditions. The wave transmission behind the devices is pretty high, suggesting that the tested layout should be considered as a module of a wave farm installation. Indications on the minimum inter-distance among the devices are provided. Furthermore, a CALM mooring system leads to lower wave transmission and also larger power production than a spread mooring. The two numerical codes have different potentialities. The hydrodynamics around single and multiple devices is obtained with MIKE 21 BW, while wave loads and motions for a single moored device are derived from ANSYS-AQWA. Combining the experimental and numerical it is suggested –for both coastal protection and energy production– to adopt a staggered layout, which will maximise the devices density and minimize the marine space required for the installation.

A Bayesian changepoint analysis on spatio-temporal point processes

Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.

Potential Analysis for Hypoelliptic Second Order PDEs with Nonnegative Characteristic Form

In this Thesis we consider a class of second order partial differential operators with non-negative characteristic form and with smooth coefficients. Main assumptions on the relevant operators are hypoellipticity and existence of a well-behaved global fundamental solution. We first make a deep analysis of the L-Green function for arbitrary open sets and of its applications to the Representation Theorems of Riesz-type for L-subharmonic and L-superharmonic functions. Then, we prove an Inverse Mean value Theorem characterizing the superlevel sets of the fundamental solution by means of L-harmonic functions. Furthermore, we establish a Lebesgue-type result showing the role of the mean-integal operator in solving the homogeneus Dirichlet problem related to L in the Perron-Wiener sense. Finally, we compare Perron-Wiener and weak variational solutions of the homogeneous Dirichlet problem, under specific hypothesis on the boundary datum.

HLA class II mismatch alleles as targets of the alloreactive CD4 T-cell response

In allogeneic hematopoietic stem cell transplantation (allo-HSCT), alloreactive T lymphocytes of donor origin mediate the beneficial graft-versus-leukemia effect but also induce graft-versus-host disease (GvHD). Since human leukocyte antigens (HLA) mismatch alleles represent major targets of alloreactive T lymphocytes, patient and donor are usually matched for the class I molecules A, B, C, and for the class II molecules DRB1 and DQB1, in order do reduce the risk of GvHD. The HLA-DPB1 locus, however, is still ignored in donor selection. Interestingly, clinical studies have demonstrated that disparities at HLA-DQB1 alleles as well as distinct HLA DPB1 mismatch constellations do not adversely affect the outcome of allo-HSCT. It has also been shown that HLA class II is predominantly expressed on hematopoietic cells under non-inflammatory conditions. Therefore, this PhD thesis focused on the application of CD4 T cells in adoptive immunotherapy of leukemias.rnIn the first part of this thesis we developed a rapid screening approach to detect T-cell reactivity of donors to single HLA class II mismatch alleles. Allo-HLA reactivity was measured in naive, memory, and entire CD4 T cells isolated from PBMC of healthy donors by flow cytometric cell sorting according to expression of the differentiation markers CD45RA, CD45RO, CD62L, and CCR7. T-cell populations were defined by a single marker to facilitate translation into a clinical-grade allo-depletion procedure. Alloreactivity to single HLA-DR/-DQ mismatch alleles was analyzed in short-term mixed lymphocyte reactions (MLR) in vitro. As standard antigen-presenting cells, we used the HLA-deficient cell line K562 upon electroporation with single HLA-DR/-DQ allele mRNA. We observed in IFN-γ ELISpot assays that allo-HLA-reactivity preferentially derived from subsets enriched for naive compared to memory T cells in healthy donors, irrespective of the HLA mismatch allele. This separation was most efficient if CD62L (P=0.008) or CD45RA (P=0.011) were used as marker. Median numbers of allo-HLA-reactive effector cells were 3.5-fold and 16.6-fold lower in CD62Lneg and CD45RAneg memory CD4 T cells than in entire CD4 T cells, respectively. In allele-specific analysis, alloreactivity to single HLA-DR alleles clearly exceeded that to HLA-DQ alleles. In terms of alloproliferation no significant difference could be observed between individual CD4 T-cell subsets. rnThe second part of this thesis dealed with the generation of allo-HLA-DQ/-DP specific CD4 T cells. Naive CD45RApos CD4 T cells isolated from healthy donor PBMC by flow cytometric cell sorting were stimulated in MLR against single allo-HLA-DQ/-DP alleles transfected into autologous mature monocyte-derived dendritic cells by mRNA electroporation. Rapidly expanding HLA-DQ/-DP mismatch reactive T cells significantly recognized and cytolysed primary acute myeloid leukemia (AML) blasts, fibroblasts (FB) and keratinocytes (KC) in IFN-γ ELISpot and 51chromium release assays if the targets carried the HLA DQ/ DP allele used for T cell priming. While AML blasts were recognized independent of pre-incubating them with IFN-γ, recognition of FB and KC required IFN-γ pre treatment. We further investigated HLA class II expression on hematopoietic and non-hematopoietic cells by flow cytometry. HLA class II was not detected on primary FB, KC, and non-malignant kidney cells, but was expressed at significant levels on primary AML blasts and B-LCL. Up-regulation of HLA class II expression was observed on all cell types after pre-incubation with IFN-γ.rnIn summary, the novel K562-HLA based MLR approach revealed that naive-depleted CD4 T-cell subsets of healthy individuals contain decreased allo-HLA reactivity in vitro. We propose the application of CD45RAneg naive-depleted CD4 T cells as memory T cell therapy, which might be beneficial for HLA-mismatched patients at high-risk of GvHD and low-risk of leukemia relapse. Memory T cells might also provide important post-transplant immune functions against infectious agents. Additionally, the screening approach could be employed as test system to detect donors which have low risks for the emergence of GvHD after allo-HSCT. In the second part of this thesis we developed a protocol for the generation of allo-HLA-DQ/-DP specific CD4 T cell lines, which could be applied in situations in which patient and donor are matched in all HLA alleles but one HLA-DQ/-DP allele with low GvHD potential. These T cells showed lytic activity to leukemia cells while presumably sparing non-hematopoietic tissues under non-inflammatory conditions. Therefore, they might be advantageous for allo-HSCT patients with advanced stage AML after reduced-intensity conditioning and T-cell depletion for the replenishment of anti-leukemic reactivity if the risk for disease relapse is high. rn

Negoziazioni intergenerazionali dell'autonomia abitativa in contesti di working class

Nell’ambito della riflessione sui processi di riproduzione e trasmissione intergenerazionale delle disuguaglianze sociali, la presente tesi dottorale propone un’analisi in prospettiva intersezionale dei percorsi verso l’indipendenza abitativa dei giovani bolognesi di origine popolare, e il ruolo svolto dalle loro famiglie in questi percorsi. Nell’approfondimento teorico si offre una ricostruzione del dibattito sociologico nazionale e internazionale sul tema delle disuguaglianze sociali e abitative delle giovani generazioni, nonché dello studio della classe sociale e i principali approcci presenti in letteratura. La ricerca sul campo si concentra, in particolare, sui modi in cui le famiglie appartenenti ad una determinata classe sociale, intesa nel senso conferito al termine da Bourdieu, negoziano e sostengono la transizione all’indipendenza abitativa dei loro figli. L’approfondimento empirico consiste in una ricerca qualitativa longitudinale retrospettiva, condotta nel bolognese nel 2013-2014 su un campione di famiglie working class. Ai giovani-adulti coinvolti e ai loro genitori è stato chiesto di ricostruire le loro biografie attraverso lo strumento delle life histories. La ricerca evidenzia il delinearsi di “micro sistemi economici” familiari specifici e creativi. Le molteplici forme di sostegno genitoriale nei percorsi di autonomizzazione dei figli, individuate nel corso dell’analisi del materiale raccolto, si innestano quindi all’interno di un più ampio sistema di supporto intergenerazionale, che continua anche dopo l’uscita dalla famiglia di origine, a conferma dello stretto legame che caratterizza le famiglie italiane. Nello studio una particolare attenzione viene rivolta alle logiche di legittimazione del sostegno genitoriale, adottate dalle famiglie per orientare i propri interventi di aiuto. Infine, mettendo a confronto la concezione di indipendenza dei giovani adulti con quella dei loro genitori, l’indagine rileva l’esistenza di una apparente contraddizione tra le rappresentazioni dell’indipendenza e dell’autonomia abitativa e i comportamenti attuati nella vita quotidiana, contraddizione che trova una risoluzione nella negoziazione, tra le due diverse generazioni, del concetto stesso di indipendenza.

Approccio network-based alla discriminant analysis mediante HPC per la ricerca di signature ottimali in dati ad alta dimensionalità

Il presente lavoro di tesi si inserisce nell’ambito della classificazione di dati ad alta dimensionalità, sviluppando un algoritmo basato sul metodo della Discriminant Analysis. Esso classifica i campioni attraverso le variabili prese a coppie formando un network a partire da quelle che hanno una performance sufficientemente elevata. Successivamente, l’algoritmo si avvale di proprietà topologiche dei network (in particolare la ricerca di subnetwork e misure di centralità di singoli nodi) per ottenere varie signature (sottoinsiemi delle variabili iniziali) con performance ottimali di classificazione e caratterizzate da una bassa dimensionalità (dell’ordine di 101, inferiore di almeno un fattore 103 rispetto alle variabili di partenza nei problemi trattati). Per fare ciò, l’algoritmo comprende una parte di definizione del network e un’altra di selezione e riduzione della signature, calcolando ad ogni passaggio la nuova capacità di classificazione operando test di cross-validazione (k-fold o leave- one-out). Considerato l’alto numero di variabili coinvolte nei problemi trattati – dell’ordine di 104 – l’algoritmo è stato necessariamente implementato su High-Performance Computer, con lo sviluppo in parallelo delle parti più onerose del codice C++, nella fattispecie il calcolo vero e proprio del di- scriminante e il sorting finale dei risultati. L’applicazione qui studiata è a dati high-throughput in ambito genetico, riguardanti l’espressione genica a livello cellulare, settore in cui i database frequentemente sono costituiti da un numero elevato di variabili (104 −105) a fronte di un basso numero di campioni (101 −102). In campo medico-clinico, la determinazione di signature a bassa dimensionalità per la discriminazione e classificazione di campioni (e.g. sano/malato, responder/not-responder, ecc.) è un problema di fondamentale importanza, ad esempio per la messa a punto di strategie terapeutiche personalizzate per specifici sottogruppi di pazienti attraverso la realizzazione di kit diagnostici per l’analisi di profili di espressione applicabili su larga scala. L’analisi effettuata in questa tesi su vari tipi di dati reali mostra che il metodo proposto, anche in confronto ad altri metodi esistenti basati o me- no sull’approccio a network, fornisce performance ottime, tenendo conto del fatto che il metodo produce signature con elevate performance di classifica- zione e contemporaneamente mantenendo molto ridotto il numero di variabili utilizzate per questo scopo.

Development, characterization, and application of flowing atmospheric-pressure afterglow ionization for mass spectrometric analysis of ambient organic aerosols

Addressing current limitations of state-of-the-art instrumentation in aerosol research, the aim of this work was to explore and assess the applicability of a novel soft ionization technique, namely flowing atmospheric-pressure afterglow (FAPA), for the mass spectrometric analysis of airborne particulate organic matter. Among other soft ionization methods, the FAPA ionization technique was developed in the last decade during the advent of ambient desorption/ionization mass spectrometry (ADI–MS). Based on a helium glow discharge plasma at atmospheric-pressure, excited helium species and primary reagent ions are generated which exit the discharge region through a capillary electrode, forming the so-called afterglow region where desorption and ionization of the analytes occurs. Commonly, fragmentation of the analytes during ionization is reported to occur only to a minimum extent, predominantly resulting in the formation of quasimolecular ions, i.e. [M+H]+ and [M–H]– in the positive and the negative ion mode, respectively. Thus, identification and detection of signals and their corresponding compounds is facilitated in the acquired mass spectra. The focus of the first part of this study lies on the application, characterization and assessment of FAPA–MS in the offline mode, i.e. desorption and ionization of the analytes from surfaces. Experiments in both positive and negative ion mode revealed ionization patterns for a variety of compound classes comprising alkanes, alcohols, aldehydes, ketones, carboxylic acids, organic peroxides, and alkaloids. Besides the always emphasized detection of quasimolecular ions, a broad range of signals for adducts and losses was found. Additionally, the capabilities and limitations of the technique were studied in three proof-of-principle applications. In general, the method showed to be best suited for polar analytes with high volatilities and low molecular weights, ideally containing nitrogen- and/or oxygen functionalities. However, for compounds with low vapor pressures, containing long carbon chains and/or high molecular weights, desorption and ionization is in direct competition with oxidation of the analytes, leading to the formation of adducts and oxidation products which impede a clear signal assignment in the acquired mass spectra. Nonetheless, FAPA–MS showed to be capable of detecting and identifying common limonene oxidation products in secondary OA (SOA) particles on a filter sample and, thus, is considered a suitable method for offline analysis of OA particles. In the second as well as the subsequent parts, FAPA–MS was applied online, i.e. for real time analysis of OA particles suspended in air. Therefore, the acronym AeroFAPA–MS (i.e. Aerosol FAPA–MS) was chosen to refer to this method. After optimization and characterization, the method was used to measure a range of model compounds and to evaluate typical ionization patterns in the positive and the negative ion mode. In addition, results from laboratory studies as well as from a field campaign in Central Europe (F–BEACh 2014) are presented and discussed. During the F–BEACh campaign AeroFAPA–MS was used in combination with complementary MS techniques, giving a comprehensive characterization of the sampled OA particles. For example, several common SOA marker compounds were identified in real time by MSn experiments, indicating that photochemically aged SOA particles were present during the campaign period. Moreover, AeroFAPA–MS was capable of detecting highly oxidized sulfur-containing compounds in the particle phase, presenting the first real-time measurements of this compound class. Further comparisons with data from other aerosol and gas-phase measurements suggest that both particulate sulfate as well as highly oxidized peroxyradicals in the gas phase might play a role during formation of these species. Besides applying AeroFAPA–MS for the analysis of aerosol particles, desorption processes of particles in the afterglow region were investigated in order to gain a more detailed understanding of the method. While during the previous measurements aerosol particles were pre-evaporated prior to AeroFAPA–MS analysis, in this part no external heat source was applied. Particle size distribution measurements before and after the AeroFAPA source revealed that only an interfacial layer of OA particles is desorbed and, thus, chemically characterized. For particles with initial diameters of 112 nm, desorption radii of 2.5–36.6 nm were found at discharge currents of 15–55 mA from these measurements. In addition, the method was applied for the analysis of laboratory-generated core-shell particles in a proof-of-principle study. As expected, predominantly compounds residing in the shell of the particles were desorbed and ionized with increasing probing depths, suggesting that AeroFAPA–MS might represent a promising technique for depth profiling of OA particles in future studies.

Set up of a procedure for correlation analysis between current discharge and dose delivery in a pulsed power plasma device for medical application

This thesis work aims to find a procedure for isolating specific features of the current signal from a plasma focus for medical applications. The structure of the current signal inside a plasma focus is exclusive of this class of machines and a specific analysis procedure has to be developed. The hope is to find one or more features that shows a correlation with the dose erogated. The study of the correlation between the current discharge signal and the dose delivered by a plasma focus could be of some importance not only for the practical application of dose prediction but also for expanding the knowledge anbout the plasma focus physics. Vatious classes of time-frequency analysis tecniques are implemented in order to solve the problem.