Intense green-yellow electroluminescence from Tb+-implanted silicon-rich silicon nitride/oxide light emitting devices

High optical power density of 0.5 mW/cm2, external quantum efficiency of 0.1%, and population inversion of 7% are reported from Tb+-implanted silicon-rich silicon nitride/oxide light emitting devices. Electrical and electroluminescence mechanisms in these devices were investigated. The excitation cross section for the 543 nm Tb3+ emission was estimated under electrical pumping, resulting in a value of 8.2 × 10−14 cm2, which is one order of magnitude larger than one reported for Tb3+:SiO2 light emitting devices. These results demonstrate the potentiality of Tb+-implanted silicon nitride material for the development of integrated light sources compatible with Si technology.

Detecció, identificació de Mycobacterium tuberculosis i caracterització molecular de la resistència als principals antituberculosos en mostra clínica directa mitjançant piroseqüenciació: aplicabilitat en l’estudi de la clonalitat de les soques.

L’augment de soques de Mycobacerium tuberculosis multiresistents i l’aparició de soques extremadament resistents, ha posat de manifest la necessitat de disposar de nous mètodes de detecció precoç de M.tuberculosis i les seves resistències als principals fàrmacs antituberculosos, així com l’estudi eficaç dels brots, per a poder dur a terme un control eficient de la malaltia. L’objectiu de l’estudi va ser determinar la capacitat de la piroseqüenciació per a detectar i identificar micobacteris a partir d’aïllats clínics i mostra directa, determinar el seu patró de resistència a Rifampicina, Isoniacida, Etambutol, Fluoroquinolones, Canamicina i Capreomicina i explorar la seva potencialitat per a ser emprada en el tipatge molecular de les soques. Mitjançant la optimització de la tecnologia de la piroseqüenciació pels gens analitzats, i el disseny de primers específics, hem verificat la utilitat de la piroseqüenciació per al maneig de la tuberculosi. S’ha pogut estudiar la presència de mutacions relacionades amb resistències a fàrmacs de primera línia en el 96.5% de les posicions analitzades en soca clínica i en el 70.4% en mostra directa. Van concordar amb el resultats obtinguts per altres mètodes fenotípics i/o fenotípics el 97.1% i el 98.2% del resultats obtinguts en soca clínica i mostra directa respectivament. La piroseqüenciació ens ha permet analitzar la presència de mutacions relacionades amb resistències a antituberculosos de segona línia, servint com a mètode de confirmació en l’anàlisi d’altres mètodes genotípics. La tècnica ens ha permès també identificar els principals micobacteris no tuberculosos implicats en la infecció humana, sòls o en coinfecció. Resultats preliminars mostren que l’anàlisi amb piroseqüenciació pot ser d’utilitat per l’estudi clonal de les soques de M.tuberculosis. Les nostres observacions mostren la piroseqüenciació com una eina valuosa en l’àmbit clínic, ja que permet una reducció de la demora del diagnòstic, estudi filogenètic i detecció de resistències M.tuberculosis, i per tant una millora de l’aplicació del tractament adequat, ajudant al control de la malaltia.

Estacionalidad de la tuberculosis en el área del Hospital Universitario Dr Peset de Valencia

La tuberculosi (TB) és una malaltia infecciosa. Diversos estudis han analitzat l'existència d'un patró estacional en la seva presentació amb resultats discordants. Ens vam proposar conèixer el patró estacional de diagnòstic de la malaltia en l'àrea del nostre hospital. Realitzem un estudi observacional prospectiu de tots els pacients, diagnosticats de TB durant el període 2002-2009 en el nostre Departament. Per a l'anàlisi estadística de les dades recollides s'ha utilitzat l'aplicació informàtica SPSS 15.0. amb un nivell de significació: p &0,05. En el nostre medi i clima, el diagnòstic de la tuberculosi pulmonar predomina durant els mesos càlids. Aquest predomini no s'ha relacionat amb les característiques socio-demogràfiques ni clíniques dels pacients.

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

Relació entre el percentatge i número absolut de cèl·lules Natural Killer i de l’expressió dels seus receptors NKG2D i NKp46 i les diferents formes de presentació de la Tuberculosi. Resultats preliminars.

La tuberculosi pot localitzar-se al pulmó: TB-P o altres òrgans: TB-EP, segons el compromís del sistema immunitari de l’hoste, on hi intervenen les cèl.lules Natural Killer-NK. L’estudi analitza el percentatge i número absolut d’NK i l’expressió dels receptors d’activació, NKG2D - NKp46, en 15 malalts/TB-P, 15 malalts/TB-EP i 15 sans, trobant-se augmentades en percentatge en el grup TB-P, disminuïdes en número absolut en els TB-EP i TB-P, i valors més alts d’ NKG2D, sobretot, malalts de TB-EP. Les coincidències amb d’altres estudis i les troballes preliminars obren possibilitats a investigacions en el camp de la TB-EP i la reacció immune.

Nanomotors: new strategies of (bio)sensing based on motion

Nanomotors are nanoscale devices capable of converting energy into movement and forces. Among them, self-propelled nanomotors offer considerable promise for developing new and novel bioanalytical and biosensing strategies based on the direct isolation of target biomolecules or changes in their movement in the presence of target analytes. The mainachievements of this project consists on the development of receptor-functionalized nanomotors that offer direct and rapid target detection, isolation and transport from raw biological samples without preparatory and washing steps. For example, microtube engines functionalized with aptamer, antibody, lectin and enzymes receptors were used for the direct isolation of analytes of biomedical interest, including proteins and whole cells, among others. A target protein was also isolated from a complex sample by using an antigen-functionalized microengine navigating into the reservoirs of a lab-on-a-chip device. The new nanomotorbased target biomarkers detection strategy not only offers highly sensitive, rapid, simple and low cost alternative for the isolation and transport of target molecules, but also represents a new dimension of analytical information based on motion. The recognition events can be easily visualized by optical microscope (without any sophisticated analytical instrument) to reveal the target presence and concentration. The use of artificial nanomachines has shown not only to be useful for (bio)recognition and (bio)transport but also for detection of environmental contamination and remediation. In this context, micromotors modified with superhydrophobic layer demonstrated that effectively interacted, captured, transported and removed oil droplets from oil contaminated samples. Finally, a unique micromotor-based strategy for water-quality testing, that mimics live-fish water-quality testing, based on changes in the propulsion behavior of artificial biocatalytic microswimmers in the presence of aquatic pollutants was also developed. The attractive features of the new micromachine-based target isolation and signal transduction protocols developed in this project offer numerous potential applications in biomedical diagnostics, environmental monitoring, and forensic analysis.

Incorporating features of distribution and progression for automatic Makam classification

Automatic classification of makams from symbolic data is a rarely studied topic. In this paper, first a review of an n-gram based approach is presented using various representations of the symbolic data. While a high degree of precision can be obtained, confusion happens mainly for makams using (almost) the same scale and pitch hierarchy but differ in overall melodic progression, seyir. To further improve the system, first n-gram based classification is tested for various sections of the piece to take into account a feature of the seyir that melodic progression starts in a certain region of the scale. In a second test, a hierarchical classification structure is designed which uses n-grams and seyir features in different levels to further improve the system.

BIMS: Biomedical Information Management System

This final year project presents the design principles and prototype implementation of BIMS (Biomedical Information Management System), a flexible software system which provides an infrastructure to manage all information required by biomedical research projects.The BIMS project was initiated with the motivation to solve several limitations in medical data acquisition of some research projects, in which Universitat Pompeu Fabra takes part. These limitations,based on the lack of control mechanisms to constraint information submitted by clinicians, impact on the data quality, decreasing it.BIMS can easily be adapted to manage information of a wide variety of clinical studies, not being limited to a given clinical specialty. The software can manage both, textual information, like clinical data (measurements, demographics, diagnostics, etc ...), as well as several kinds of medical images (magnetic resonance imaging, computed tomography, etc ...). Moreover, BIMS provides a web - based graphical user interface and is designed to be deployed in a distributed andmultiuser environment. It is built on top of open source software products and frameworks.Specifically, BIMS has been used to represent all clinical data being currently used within the CardioLab platform (an ongoing project managed by Universitat Pompeu Fabra), demonstratingthat it is a solid software system, which could fulfill requirements of a real production environment.

Back to square one: Identification issues in DSGE models

We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

Weighted metric multidimensional scaling

This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures.

The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the soil moisture and ocean salinity (SMOS) end-to-end performance simulator (SEPS). The brightness temperature generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This high-resolution generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. Results are compared to brightness temperatures that are computed under the assumption of an ellipsoidal Earth.

SrRuO3/SrTiO3/SrRuO3 heterostructures for magnetic tunnel junctions

We report on the growth and characterization of SrRuO3 single layers and SrRuO3/SrTiO3/SrRuO3 heterostructures grown on SrTiO3(100) substrates. The thickness dependence of the coercivity was determined for these single layers. Heterostructures with barrier thickness tb=1, 2.5, and 4 nm were fabricated, with electrodes having thickness ranging from 10 to 100 nm. The hysteresis loops of heterostructures with tb=2.5¿nm, 4 nm reveal uncoupled magnetic switching of the electrodes. Therefore, these heterostructures can be used for the fabrication of magnetic tunneling junctions.