Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.

Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.

Development of advanced silicon radiation detectors for high energy physics and medical imaging

The 1st chapter of this work presents the different experiments and collaborations in which I am involved during my PhD studies of Physics. Following those descriptions, the 2nd chapter is dedicated to how the radiation affects the silicon sensors, as well as some experimental measurements carried out at CERN (Geneve, Schwitzerland) and IFIC (Valencia, Spain) laboratories. Besides the previous investigation results, this chapter includes the most recent scientific papers appeared in the latest RD50 (Research & Development #50) Status Report, published in January 2007, as well as some others published this year. The 3rd and 4th are dedicated to the simulation of the electrical behavior of solid state detectors. In chapter 3 are reported the results obtained for the illumination of edgeless detectors irradiated at different fluences, in the framework of the TOSTER Collaboration. The 4th chapter reports about simulation design, simulation and fabrication of a novel 3D detector developed at CNM for ions detection in the future ITER fusion reactor. This chapter will be extended with irradiation simulations and experimental measurements in my PhD Thesis.

Quantitative analysis of image factors in a cultural heritage tourist destination

The tourism consumer’s purchase decision process is, to a great extent, conditioned by the image the tourist has of the different destinations that make up his or her choice set. In a highly competitive international tourist market, those responsible for destinations’ promotion and development policies seek differentiation strategies so that they may position the destinations in the most suitable market segments for their product in order to improve their attractiveness to visitors and increase or consolidate the economic benefits that tourism activity generates in their territory. To this end, the main objective we set ourselves in this paper is the empirical analysis of the factors that determine the image formation of Tarragona city as a cultural heritage destination. Without a doubt, UNESCO’s declaration of Tarragona’s artistic and monumental legacies as World Heritage site in the year 2000 meant important international recognition of the quality of the cultural and patrimonial elements offered by the city to the visitors who choose it as a tourist destination. It also represents a strategic opportunity to boost the city’s promotion of tourism and its consolidation as a unique destination given its cultural and patrimonial characteristics. Our work is based on the use of structured and unstructured techniques to identify the factors that determine Tarragona’s tourist destination image and that have a decisive influence on visitors’ process of choice of destination. In addition to being able to ascertain Tarragona’s global tourist image, we consider that the heterogeneity of its visitors requires a more detailed study that enables us to segment visitor typology. We consider that the information provided by these results may prove of great interest to those responsible for local tourism policy, both when designing products and when promoting the destination.

Acute Damage to the Posterior Limb of the Internal Capsule on Diffusion Tensor Tractography as an Early Imaging Predictor of Motor Outcome after Stroke

Background and Purpose Early prediction of motor outcome is of interest in stroke management. We aimed to determine whether lesion location at DTT is predictive of motor outcome after acute stroke and whether this information improves the predictive accuracy of the clinical scores. Methods We evaluated 60 consecutive patients within 12 hours of MCA stroke onset. We used DTT to evaluate CST involvement in the MC and PMC, CS, CR, and PLIC and in combinations of these regions at admission, at day 3, and at day 30. Severity of limb weakness was assessed using the m-NIHSS (5a, 5b, 6a, 6b). We calculated volumes of infarct and FA values in the CST of the pons. Results Acute damage to the PLIC was the best predictor associated with poor motor outcome, axonal damage, and clinical severity at admission (P&.001). There was no significant correlation between acute infarct volume and motor outcome at day 90 (P=.176, r=0.485). The sensitivity, specificity, and positive and negative predictive values of acute CST involvement at the level of the PLIC for 4 motor outcome at day 90 were 73.7%, 100%, 100%, and 89.1%, respectively. In the acute stage, DTT predicted motor outcome at day 90 better than the clinical scores (R2=75.50, F=80.09, P&.001). Conclusions In the acute setting, DTT is promising for stroke mapping to predict motor outcome. Acute CST damage at the level of the PLIC is a significant predictor of unfavorable motor outcome.

Solitary Fibrous Tumor. Imaging findings in a series of nine cases

Es presenta un estudi retrospectiu descrivint les característiques radiològiques en una sèrie de nou casos de tumor fibrós solitari que affecta partes toves. Aquests resultats es comparen amb els resultats d’anatomia patològica i amb l’evolució clínica dels pacients

Research development of terahertz imaging systems

The electromagnetic radiation at a terahertz frequencies (from 0.1 THz to 10 THz) is situated in the frequency band comprised between the optical band and the radio band. The interest of the scientific community in this frequency band has grown up due to its large capabilities to develop innovative imaging systems. The terahertz waves are able to generate extremely short pulses that achieve good spatial resolution, good penetration capabilities and allow to identify microscopic structures using spectral analysis. The work carried out during the period of the grant has been based on the developement of system working at the aforementioned frequency band. The main system is based on a total power radiometer working at 0.1 THz to perform security imaging. Moreover, the development of this system has been useful to gain knowledge in the behavior of the component systems at this frequency band. Moreover, a vectorial network analyzer has been used to characterize materials and perform active raster imaging. A materials measurement system has been designed and used to measure material properties as permittivity, losses and water concentration. Finally, the design of a terahertz time-domain spectrometer (THz-TDS) system has been started. This system will allow to perform tomographic measurement with very high penetration resolutions while allowing the spectral characterization of the sample material. The application range of this kind of system is very wide: from the identification of cancerous tissues of a skin to the characterization of the thickness of a painted surface of a car.

Segmentació d'imatge de ressonància magnètica de pit utilitzant atlas probabilístic

La localització d'òrgans és un tòpic important en l'àmbit de la imatge mèdica per l'ajuda del tractament i diagnosi del càncer. Un exemple es pot trobar en la cal•libració de models farmacoquinètics. Aquesta pot ésser realitzada utilitzant un teixit de referència, on, per exemple en imatges de ressonància magnètica de pit, una correcta segmentació del múscul pectoral és necessària per a la detecció de signes de malignitat. Els mètodes de segmentació basat en atlas han estat altament avaluats en imatge de ressonància magnètica de cervell, obtenint resultats satisfactoris. En aquest projecte, en col•laboració amb el el Diagnostic Image Analysis Group de la Radboud University Nijmegen Medical Centre i la supervisió del Dr. N.Karssemeijer, es presenta la primera aproximació d'un mètode de segmentació basat en atlas per segmentar els diferents teixits visibles en imatges de ressonància magnètica (T1) del pit femení. L'atlas consisteix en 5 estructures (teixit greixòs, teixit dens, cor, pulmons i múscul pectoral) i ha estat utilitzat en un algorisme de segmentació Bayesià per tal de delinear les esmentades estructures. A més a més, s'ha dut a terme una comparació entre un mètode de registre global i un de local, utilitzats tant en la construcció de l'atlas com en la fase de segmentació, essent el primer el que ha presentat millors resultats en termes d'eficiència i precisió. Per a l'avaluació, s'ha dut a terme una comparació visual i numèrica entre les segmentacions obtingudes i les realitzades manualment pels experts col•laboradors. Pel que fa a la numèrica, s'ha emprat el coeficient de similitud de Dice ( mesura que dóna valors entre 0 i 1, on 0 significa no similitud i 1 similitud màxima) i s'ha obtingut una mitjana general de 0.8. Aquest resultat confirma la validesa del mètode presentat per a la segmentació d'imatges de ressonància magnètica del pit.

On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

Avenços en l'estudi de la litiasi renal: mètodes de chemical imaging i intel·ligencia artificial (ANN) per la caracterització de càlculs renals

La litiasi urinària és un trastorn que implica la formació de precipitats en qualsevol part del tracte urinari. Aquest és un desordre comú que afecta aproximadament a una desena part de la població de la Unió Europea al llarg de la seva vida. A més, durant els cinc anys posteriors a un episodi litiàsic el percentatge de recurrència dels pacients és del 45 al 75%. Aquest trastorn urinari està influït per una gran quantitat de variables, d’origen fisiològic, psicològic i ambiental. Els episodis litiàsics, es poden solucionar espontàniament, amb l’expulsió del càlcul renal, o bé a través de diverses intervencions mèdiques. Els tractaments mèdics derivats de la litiasi urinària; és a dir, la fragmentació del càlcul, intervencions quirúrgiques i tractaments posteriors generen unes grans despeses als sistemes mèdics. Pels motius exposats, la identificació del desordre que ha originat l’episodi litiàsic és de radical importància, per tal de minimitzar el risc de reincidència. Els mètodes més usuals per determinar les causes que desencadenen la formació del càlcul renal són les anàlisis d’orina i l’estudi del càlcul generat. La correcta descripció de la composició i, especialment, l’estructura del càlcul renal pot aportar informació clau sobre les possibles causes de la seva formació, tant de l’inici de nucleació del càlcul com de les successives etapes de creixement cristal·lí. Tenint en compte aquest darrer aspecte, el present estudi s’ha dirigit a la caracterització de càlculs urinaris mitjançant l’aplicació de metodologies d’imatge química (Hyperspectral Imaging), el que va contribuir a determinar les principals característiques espectrals de cada compost majoritari als càlculs renals. D’altra banda, la utilització de mostres de composició coneguda ha possibilitat la creació d’un model amb Xarxes Neuronals Artificials, que permet la classificació de noves mostres de composició desconeguda, de manera més ràpida que el procediment actual. Aquest treball constitueix una nova contribució a la comprensió de l’estructura de les pedres de ronyó, així com les condicions de la seva formació. Els resultats obtinguts destaquen les possibilitats que presenten les tècniques emprades al camp de la litiasi renal, que permeten complementar els coneixements existents enfocats a millorar la qualitat de vida dels pacients.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.