Enhancement of optical absorption by modulation of the oxygen flow of TiO2 films deposited by reactive sputtering

Oxygen-deficient TiO2 films with enhanced visible and near-infrared optical absorption have been deposited by reactive sputtering using a planar diode radio frequency magnetron configuration. It is observed that the increase in the absorption coefficient is more effective when the O-2 gas supply is periodically interrupted rather than by a decrease of the partial O-2 gas pressure in the deposition plasma. The optical absorption coefficient at 1.5 eV increases from about 1 x 10(2) cm(-1) to more than 4 x 10(3) cm(-1) as a result of the gas flow discontinuity. A red-shift of similar to 0.24 eV in the optical absorption edge is also observed. High resolution transmission electron microscopy with composition analysis shows that the films present a dense columnar morphology, with estimated mean column width of 40nm. Moreover, the interruptions of the O-2 gas flow do not produce detectable variations in the film composition along its growing direction. X-ray diffraction and micro-Raman experiments indicate the presence of the TiO2 anatase, rutile, and brookite phases. The anatase phase is dominant, with a slight increment of the rutile and brookite phases in films deposited under discontinued O-2 gas flow. The increase of optical absorption in the visible and near-infrared regions has been attributed to a high density of defects in the TiO2 films, which is consistent with density functional theory calculations that place oxygen-related vacancy states in the upper third of the optical bandgap. The electronic structure calculation results, along with the adopted deposition method and experimental data, have been used to propose a mechanism to explain the formation of the observed oxygen-related defects in TiO2 thin films. The observed increase in sub-bandgap absorption and the modeling of the corresponding changes in the electronic structure are potentially useful concerning the optimization of efficiency of the photocatalytic activity and the magnetic doping of TiO2 films. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4724334]

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.

Automatic initialization for facial analysis in interactive robotics

[EN]This paper focuses on four different initialization methods for determining the initial shape for the AAM algorithm and their particular performance in two different classification tasks with respect to either the facial expression DaFEx database and to the real world data obtained from a robot’s point of view.

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.

Statistical methods for biomedical signal analysis and processing

Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.

Spectrum Management and Cognitive Radios

The ever increasing demand for new services from users who want high-quality broadband services while on the move, is straining the efficiency of current spectrum allocation paradigms, leading to an overall feeling of spectrum scarcity. In order to circumvent this problem, two possible solutions are being investigated: (i) implementing new technologies capable of accessing the temporarily/locally unused bands, without interfering with the licensed services, like Cognitive Radios; (ii) release some spectrum bands thanks to new services providing higher spectral efficiency, e.g., DVB-T, and allocate them to new wireless systems. These two approaches are promising, but also pose novel coexistence and interference management challenges to deal with. In particular, the deployment of devices such as Cognitive Radio, characterized by the inherent unplanned, irregular and random locations of the network nodes, require advanced mathematical techniques in order to explicitly model their spatial distribution. In such context, the system performance and optimization are strongly dependent on this spatial configuration. On the other hand, allocating some released spectrum bands to other wireless services poses severe coexistence issues with all the pre-existing services on the same or adjacent spectrum bands. In this thesis, these methodologies for better spectrum usage are investigated. In particular, using Stochastic Geometry theory, a novel mathematical framework is introduced for cognitive networks, providing a closed-form expression for coverage probability and a single-integral form for average downlink rate and Average Symbol Error Probability. Then, focusing on more regulatory aspects, interference challenges between DVB-T and LTE systems are analysed proposing a versatile methodology for their proper coexistence. Moreover, the studies performed inside the CEPT SE43 working group on the amount of spectrum potentially available to Cognitive Radios and an analysis of the Hidden Node problem are provided. Finally, a study on the extension of cognitive technologies to Hybrid Satellite Terrestrial Systems is proposed.

Design and implementation of a fft pruning engine for DSA-enabled cognitive radios.

This research work presents the design and implementation of a FFT pruning block, which is an extension to the FFT core for OFDM demodulation, enabling run-time 8 pruning of the FFT algorithm, without any restrictions on the distribution pattern of the active/inactive sub-carriers. The design and implementation of FFT processor core is not the part of this work. The whole design was prototyped on an ALTERA STRATIX V FPGA to evaluate the performance of the pruning engine. Synthesis and simulation results showed that the logic overhead introduced by the pruning block is limited to a 10% of the total resources utilization. Moreover, in presence of a medium-high scattering of the sub-carriers, power and energy consumption of the FFT core were reduced by a 30% factor.

Modulation der Strahlen- und Chemosensitivität menschlicher Tumorzellen durch Interferon

Pankreaskarzinome und maligne Melanome weisen eine hohe Resistenz gegenüber Zytostatika und Bestrahlung in der Therapie auf. Die Behandlung eines metastasierenden Pankreaskarzinoms besteht aus einer Kombination aus 5-FU, CDDP und IR. Für die Behandlung des malignen Melanoms ist das methylierende Agenz DTIC das Mittel erster Wahl. Das ebenfalls methylierende Agenz TMZ, welches jedoch in Deutschland noch nicht für die Behandlung von malignen Melanomen zugelassen ist, erlangt immer größere Bedeutung. Die Ansprechrate der Tumore kann durch Kombination mit IFNs erhöht werden. In der vorliegenden Arbeit wurde an Pankreaskarzinom- bzw. Melanomzelllinien untersucht, ob IFNs einen radio- bzw. chemosensibilisierender Effekt ausüben und, wenn ja, welcher Mechanismus hierfür verantwortlich ist. Es wurden zehn Pankreaskarzinom-Zelllinien (Panc-1, Su8686, Capan-1, Capan-2, Bxpc-3, PA-TU 8988T, Aspc-1, HS 766T, Mia-PaCa-2 und PA-TU 8902) untersucht. Diese zeigten eine hohe Variabilität in ihrer intrinsischen Radiosensitivität sowie in ihrer Sensitivität gegenüber IFN-alpha und IFN-beta. IFN-beta erwies sich als toxischer im Vergleich zu IFN-alpha. Die radiosensibilisierende Wirkung der IFNs an Pankreaskarzinom-Zelllinien war moderat, wobei IFN-beta im Vergleich zu IFN-alpha effektiver war. Der radiosensibilisierende Effekt ging mit einer deutlichen Erhöhung der alpha-Komponente, der Überlebenskurven einher und kam durch eine IFN-beta vermittelte Verstärkung der IR-induzierten Apoptoserate zustande. Dies wurde sowohl durch SubG1 als auch durch Annexin V / PI Messungen gezeigt. Einen Einfluss von IFN-beta auf den Zellzyklus und die DSB-Reparatur konnte durch funktionelle Untersuchungen sowie durch PCR bzw. Western-Blot-Analysen als Grund für den sensibilisierdenen Effekt ausgeschlossen werden. Ein sensibilisierender Effekt von IFN-beta auf die durch TMZ-induzierte Zytotoxizität war für die Pankreaskarzinom-Zelllinien weder in MGMT-profizientem noch –depletiertem Zustand zu beobachten. Zur Untersuchung der sensibilisierenden Eigenschaften von IFNs gegenüber TMZ in malignen Melanomzelllinien wurden p53-Wildtyp (D05 und A375) und mutierte Zelllinien (D14 und RPMI 7951) untersucht. Gegenüber alleiniger TMZ-Behandlung reagierten die untersuchten p53-Wildtyp Melanomzelllinien nicht sensitiver auf eine Behandlung mit TMZ als p53-mutierte Zelllinien. Der Nachweis des Spaltprodukts der Caspase-9 lieferte einen Hinweis darauf, dass in den Melanomzelllinien unabhängig vom p53-Status nach alleiniger TMZ-Behandlung der mitochondriale Apoptoseweg aktiviert wird. Durch eine Vorbehandlung der Zellen mit IFN-alpha oder IFN-beta konnte die TMZ-induzierte Apoptoserate in malignen Melanomzellen deutlich gesteigert werden. In p53-Wildtyp Melanomzellen war der chemosensibilisierende Effekt der IFNs besonders ausgeprägt. IFN-beta erwies sich hierbei als effektiver, weshalb es für die folgenden Versuche verwendet wurde. Durch stabile Transfektion der Zelllinie D05 mit MGMT konnte das durch TMZ-induzierte Addukt O6MeG als für den sensibilisieredenen Effekt ausschlaggebende DNA-Schädigung charakterisiert werden. Western-Blot-Analysen und gamma-H2AX-Immunfluoreszenz Untersuchungen konnten einen Einfluss von IFN-beta auf die Prozessierung der Läsion O6MeG sowie einen Einfluss von IFN-beta auf die Induktion und Reparatur von TMZ verursachten DSBs ausschließen. Durch Experimente mit einem Fas-aktivierenden Antikörper und durch eine stabile Transfektion der Zelllinien D05 und A375 mit DN-FADD konnte gezeigt werden, dass p53-Wildtyp Melanomzellen nicht oder nur eingeschränkt in der Lage sind, nach TMZ-Behandlung über den Fas-Rezeptor Signalweg Apoptose zu induzieren. Ausschlaggebend hierfür ist die geringe Pro-Caspase-8 Expression dieser Zelllinien. Eine IFN-beta Vorbehandlung bewirkte eine Reaktivierung des Fas-Rezeptor Signalweges, was mit einer verstärkten Expression der Pro-Caspase-8 einherging. Durch Experimente mit Caspase-8 siRNA konnte diese IFN-beta induzierte Verstärkung der Pro-Caspase-8 Expression als entscheidender Faktor für den sensibilisierenden Effekt ausgemacht werden. Zum ersten Mal konnte damit in dieser Arbeit gezeigt werden, dass p53-Wildtyp Melanomzellen durch eine IFN-beta vermittelte Hochregulation der Pro-Caspase-8 ihre Fähigkeit wiedererlangen, nach TMZ-Behandlung über den Fas-Rezeptor Signalweg Apoptose auszulösen. Diese Arbeiten weisen einen Weg, auf welchem die hohe Resistenz von malignen Melanomzellen, welche zu 80 % das nicht mutierte p53 Gen beherbergen, über eine IFN-beta induzierte Reaktivierung der Fas-Rezeptor vermittelten Apoptosekaskade überwunden werden kann.

Einfluss der Modulation von P-Glykoprotein (P-gp) auf die Verfügbarkeit und Wirksamkeit der pharmakologischen Behandlung psychiatrischer Erkrankungen im Tiermodell

P-Glykoprotein (P-gp) ist ein ATP-verbrauchender Transporter, der in Organschranken exprimiert wird, um Fremdstoffe auszuschleusen, darunter auch Psychopharmaka. Im Rahmen dieser Arbeit wurde im Tiermodell der Maus untersucht, welche pharmakokinetischen und pharmakodynamischen Konsequenzen sich bei Verabreichung von Risperidon als P-gp Modellsubstrat ergeben, wenn die Expression von P-gp induziert wird. Als potenzielle Induktoren wurden Dexamethason, Rifampicin, Quercetin, 5-Pregnen-3ß-ol-20-on-16α-Carbonitril (PCN) und Acitretin geprüft. Es konnte gezeigt werden, dass alle Substanzen die Verteilung von Risperidon und seinem aktiven Metaboliten 9-Hydroxyrisperidon beeinflussten. Während sich für Quercetin und Acitretin leichte P-gp inhibitorische Eigenschaften ergaben, die an Hand von erhöhten Konzentrationen von Risperidon und 9-Hydroxyrisperidon gezeigt werden konnten, führten die bekannten P-gp Induktoren Rifampicin, Dexamethason und PCN zu verringerten Konzentrationen im Vergleich zur Kontrollgruppe. Durch Western Blot Untersuchungen wurde bestätigt, dass die Induktoren die P-gp Expression im Hirngewebe tendenziell steigerten. Dies sprach dafür, dass bei Verabreichung einer Komedikation, die P-gp induziert, mit einer veränderten Verteilung von P-gp Substraten zu rechnen ist. Darüber hinaus konnte nachgewiesen werden, dass durch eine Hemmung bzw. Induktion von P-gp nicht nur die Pharmakokinetik, sondern auch die Pharmakodynamik von Risperidon und 9-Hydroxyrisperidon verändert wird. Dies wurde durch verhaltenspharmakologische Untersuchungen gezeigt. Durch Risperidon induzierte motorische Effekte auf dem RotaRod waren nach Induktion von P-gp abgeschwächt. Dies zeigte sich auch für Haloperidol, welches kein Substrat ist. Da P-gp abhängige Effekte in diesem Fall keine bedeutende Rolle spielen, ist davon auszugehen, dass neben der Induktion von P-gp an der Blut-Hirn Schranke auch andere Mechanismen wie z.B. eine Induktion von Enzymen der CYP-Familie an den beobachteten Effekten beteiligt sind. Bei Untersuchungen von kognitiven Leistungen in der Barnes Maze konnte gezeigt werden, dass Haloperidol im Gegensatz zu Risperidon das Lernverhalten negativ beeinflussen kann. Eine P-gp Induktion schien jedoch keinen deutlichen Einfluss auf das Lernverhalten unter Antipsychotika-Gabe zu haben und sprach vielmehr für substanzabhängige Effekte der einzelnen Antipsychotika bzw. P-gp Modulatoren. Zusatzuntersuchungen zur Hirngängigkeit von Acitretin, einem synthetischen Retinoid, welches derzeit als potenzielles Antidementivum geprüft wird, konnten belegen, dass es die Blut-Hirn Schranke überwindet. Bereits 1h nach Injektion war Acitretin in hoher Konzentration im Gehirn nachweisbar. Durch die Analyse zur Verteilung von Acitretin in Hirngewebe und Serum von P-gp Wildtyp und P-gp doppel knockout Mäusen konnte belegt werden, dass Acitretin nicht P-gp abhängig transportiert wird. Die Daten insgesamt betrachtet, lassen den Schluss zu, dass durch Verabreichung von Medikamenten, die P-gp Modulatoren sind, bei Antipsychotika mit pharmakokinetischen Interaktionen zu rechnen ist, welche die Wirksamkeit der Medikamente einschränken können.

The language of others mirrored in thy face: The role of political affiliation in automatic facial effects of language

People tend to automatically mimic facial expressions of others. If clear evidence exists on the effect of non-verbal behavior (emotion faces) on automatic facial mimicry, little is known about the role of verbal behavior (emotion language) in triggering such effects. Whereas it is well-established that political affiliation modulates facial mimicry, no evidence exists on whether this modulation passes also through verbal means. This research addressed the role of verbal behavior in triggering automatic facial effects depending on whether verbal stimuli are attributed to leaders of different political parties. Study 1 investigated the role of interpersonal verbs, referring to positive and negative emotion expressions and encoding them at different levels of abstraction, in triggering corresponding facial muscle activation in a reader. Study 2 examined the role of verbs expressing positive and negative emotional behaviors of political leaders in modulating automatic facial effects depending on the matched or mismatched political affiliation of participants and politicians of left-and right-wing. Study 3 examined whether verbs expressing happiness displays of ingroup politicians induce a more sincere smile (Duchenne) pattern among readers of same political affiliation relative to happiness expressions of outgroup politicians. Results showed that verbs encoding facial actions at different levels of abstraction elicited differential facial muscle activity (Study 1). Furthermore, political affiliation significantly modulated facial activation triggered by emotion verbs as participants showed more congruent and enhanced facial activity towards ingroup politicians’ smiles and frowns compared to those of outgroup politicians (Study 2). Participants facially responded with a more sincere smile pattern towards verbs expressing smiles of ingroup compared to outgroup politicians (Study 3). Altogether, results showed that the role of political affiliation in modulating automatic facial effects passes also through verbal channels and is revealed at a fine-grained level by inducing quantitative and qualitative differences in automatic facial reactions of readers.

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment

Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.

Oblique ionograms automatic scaling and eikonal based ray tracing

A method for automatic scaling of oblique ionograms has been introduced. This method also provides a rejection procedure for ionograms that are considered to lack sufficient information, depicting a very good success rate. Observing the Kp index of each autoscaled ionogram, can be noticed that the behavior of the autoscaling program does not depend on geomagnetic conditions. The comparison between the values of the MUF provided by the presented software and those obtained by an experienced operator indicate that the procedure developed for detecting the nose of oblique ionogram traces is sufficiently efficient and becomes much more efficient as the quality of the ionograms improves. These results demonstrate the program allows the real-time evaluation of MUF values associated with a particular radio link through an oblique radio sounding. The automatic recognition of a part of the trace allows determine for certain frequencies, the time taken by the radio wave to travel the path between the transmitter and receiver. The reconstruction of the ionogram traces, suggests the possibility of estimating the electron density between the transmitter and the receiver, from an oblique ionogram. The showed results have been obtained with a ray-tracing procedure based on the integration of the eikonal equation and using an analytical ionospheric model with free parameters. This indicates the possibility of applying an adaptive model and a ray-tracing algorithm to estimate the electron density in the ionosphere between the transmitter and the receiver An additional study has been conducted on a high quality ionospheric soundings data set and another algorithm has been designed for the conversion of an oblique ionogram into a vertical one, using Martyn's theorem. This allows a further analysis of oblique soundings, throw the use of the INGV Autoscala program for the automatic scaling of vertical ionograms.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

Entity extraction e text classification come strumenti per la sentiment analysis di testi giornalistici

In this thesis we are going to talk about technologies which allow us to approach sentiment analysis on newspapers articles. The final goal of this work is to help social scholars to do content analysis on big corpora of texts in a faster way thanks to the support of automatic text classification.