30 resultados para fractal based metallo-dielectric structures


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Monitoring thunderstorms activity is an essential part of operational weather surveillance given their potential hazards, including lightning, hail, heavy rainfall, strong winds or even tornadoes. This study has two main objectives: firstly, the description of a methodology, based on radar and total lightning data to characterise thunderstorms in real-time; secondly, the application of this methodology to 66 thunderstorms that affected Catalonia (NE Spain) in the summer of 2006. An object-oriented tracking procedure is employed, where different observation data types generate four different types of objects (radar 1-km CAPPI reflectivity composites, radar reflectivity volumetric data, cloud-to-ground lightning data and intra-cloud lightning data). In the framework proposed, these objects are the building blocks of a higher level object, the thunderstorm. The methodology is demonstrated with a dataset of thunderstorms whose main characteristics, along the complete life cycle of the convective structures (development, maturity and dissipation), are described statistically. The development and dissipation stages present similar durations in most cases examined. On the contrary, the duration of the maturity phase is much more variable and related to the thunderstorm intensity, defined here in terms of lightning flash rate. Most of the activity of IC and CG flashes is registered in the maturity stage. In the development stage little CG flashes are observed (2% to 5%), while for the dissipation phase is possible to observe a few more CG flashes (10% to 15%). Additionally, a selection of thunderstorms is used to examine general life cycle patterns, obtained from the analysis of normalized (with respect to thunderstorm total duration and maximum value of variables considered) thunderstorm parameters. Among other findings, the study indicates that the normalized duration of the three stages of thunderstorm life cycle is similar in most thunderstorms, with the longest duration corresponding to the maturity stage (approximately 80% of the total time).

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A new technology for the three-dimensional (3-D) stacking of very thin chips on a substrate is currently under development within the ultrathin chip stacking (UTCS) Esprit Project 24910. In this work, we present the first-level UTCS structure and the analysis of the thermomechanical stresses produced by the manufacturing process. Chips are thinned up to 10 or 15 m. We discuss potentially critical points at the edges of the chips, the suppression of delamination problems of the peripheral dielectric matrix and produce a comparative study of several technological choices for the design of metallic interconnect structures. The purpose of these calculations is to give inputs for the definition of design rules for this technology. We have therefore undertaken a programme that analyzes the influence of sundry design parameters and alternative development options. Numerical analyses are based on the finite element method.

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We present an analytical model to interpret nanoscale capacitance microscopy measurements on thin dielectric films. The model displays a logarithmic dependence on the tip-sample distance and on the film thickness-dielectric constant ratio and shows an excellent agreement with finite-element numerical simulations and experimental results on a broad range of values. Based on these results, we discuss the capabilities of nanoscale capacitance microscopy for the quantitative extraction of the dielectric constant and the thickness of thin dielectric films at the nanoscale.

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In this work a new admittance spectroscopy technique is proposed to determine the conduction band offset in single quantum well structures (SQW). The proposed technique is based on the study of the capacitance derivative versus the frequency logarithm. This method is found to be less sensitive to parasitic effects, such as leakage current and series resistance, than the classical conductance analysis. Using this technique, we have determined the conduction band offset in In0.52Al0.48As/InxGa1¿xAs/In0.52Al0.48As SQW structures. Two different well compositions, x=0.53, which corresponds to the lattice¿matched case and x=0.60, which corresponds to a strained case, and two well widths (5 and 25 nm) have been considered. The average results are ¿Ec=0.49±0.04 eV for x=0.53 and ¿Ec =0.51±0.04 eV for x=0.6, which are in good agreement with previous reported data.

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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

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Lasers are essential tools for cell isolation and monolithic interconnection in thin-film-silicon photovoltaic technologies. Laser ablation of transparent conductive oxides (TCOs), amorphous silicon structures and back contact removal are standard processes in industry for monolithic device interconnection. However, material ablation with minimum debris and small heat affected zone is one of the main difficulty is to achieve, to reduce costs and to improve device efficiency. In this paper we present recent results in laser ablation of photovoltaic materials using excimer and UV wavelengths of diode-pumped solid-state (DPSS) laser sources. We discuss results concerning UV ablation of different TCO and thin-film silicon (a-Si:H and nc-Si:H), focussing our study on ablation threshold measurements and process-quality assessment using advanced optical microscopy techniques. In that way we show the advantages of using UV wavelengths for minimizing the characteristic material thermal affection of laser irradiation in the ns regime at higher wavelengths. Additionally we include preliminary results of selective ablation of film on film structures irradiating from the film side (direct writing configuration) including the problem of selective ablation of ZnO films on a-Si:H layers. In that way we demonstrate the potential use of UV wavelengths of fully commercial laser sources as an alternative to standard backscribing process in device fabrication.

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We present a seabed profile estimation and following method for close proximity inspection of 3D underwater structures using autonomous underwater vehicles (AUVs). The presented method is used to determine a path allowing the AUV to pass its sensors over all points of the target structure, which is known as coverage path planning. Our profile following method goes beyond traditional seabed following at a safe altitude and exploits hovering capabilities of recent AUV developments. A range sonar is used to incrementally construct a local probabilistic map representation of the environment and estimates of the local profile are obtained via linear regression. Two behavior-based controllers use these estimates to perform horizontal and vertical profile following. We build upon these tools to address coverage path planning for 3D underwater structures using a (potentially inaccurate) prior map and following cross-section profiles of the target structure. The feasibility of the proposed method is demonstrated using the GIRONA 500 AUV both in simulation using synthetic and real-world bathymetric data and in pool trials

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This work describes a simulation tool being developed at UPC to predict the microwave nonlinear behavior of planar superconducting structures with very few restrictions on the geometry of the planar layout. The software is intended to be applicable to most structures used in planar HTS circuits, including line, patch, and quasi-lumped microstrip resonators. The tool combines Method of Moments (MoM) algorithms for general electromagnetic simulation with Harmonic Balance algorithms to take into account the nonlinearities in the HTS material. The Method of Moments code is based on discretization of the Electric Field Integral Equation in Rao, Wilton and Glisson Basis Functions. The multilayer dyadic Green's function is used with Sommerfeld integral formulation. The Harmonic Balance algorithm has been adapted to this application where the nonlinearity is distributed and where compatibility with the MoM algorithm is required. Tests of the algorithm in TM010 disk resonators agree with closed-form equations for both the fundamental and third-order intermodulation currents. Simulations of hairpin resonators show good qualitative agreement with previously published results, but it is found that a finer meshing would be necessary to get correct quantitative results. Possible improvements are suggested.

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The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

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Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

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This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.

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Implantation of deep brain stimulation (DBS) electrodes via stereotactic neurosurgery has become a standard procedure for the treatment of Parkinson's disease. More recently, the range of neuropsychiatric conditions and the possible target structures suitable for DBS have greatly increased. The former include obsessive compulsive disease, depression, obesity, tremor, dystonia, Tourette's syndrome and cluster-headache. In this article we argue that several of the target structures for DBS (nucleus accumbens, posterior inferior hypothalamus, nucleus subthalamicus, nuclei in the thalamus, globus pallidus internus, nucleus pedunculopontinus) are located at strategic positions within brain circuits related to motivational behaviors, learning, and motor regulation. Recording from DBS electrodes either during the operation or post-operatively from externalized leads while the patient is performing cognitive tasks tapping the functions of the respective circuits provides a new window on the brain mechanisms underlying these functions. This is exemplified by a study of a patient suffering from obsessive-compulsive disease from whom we recorded in a flanker task designed to assess action monitoring processes while he received a DBS electrode in the right nucleus accumbens. Clear error-related modulations were obtained from the target structure, demonstrating a role of the nucleus accumbens in action monitoring. Based on recent conceptualizations of several different functional loops and on neuroimaging results we suggest further lines of research using this new window on brain functions.

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The encapsulation of metal clusters in endohedral metallofullerenes (EMFs) takes place in cages that in most cases are far from being the most stable isomer in the corresponding hollow fullerenes. There exist several possible explanations for the choice of the hosting cages in EMFs, although the final reasons are actually not totally well understood. Moreover, the reactivity and regioselectivity of (endohedral metallo)fullerenes have in the past decade been shown to be generally dependent on a number of factors, such as the size of the fullerene cage, the type of cluster that is being encapsulated, and the number of electrons that are transferred formally from the cluster to the fullerene cage. Different rationalizations of the observed trends had been proposed, based on bond lengths, pyramidalization angles, shape and energies of (un)occupied orbitals, deformation energies of the cages, or separation distances between the pentagon rings. Recently, in our group we proposed that the quest for the maximum aromaticity (maximum aromaticity criterion) determines the most suitable hosting carbon cage for a given metallic cluster (i.e. EMF stabilization), including those cases where the IPR rule is not fulfilled. Moreover, we suggested that local aromaticity plays a determining role in the reactivity of EMFs, which can be used as a criterion for understanding and predicting the regioselectivity of different reactions such as Diels-Alder cycloadditions or Bingel-Hirsch reactions. This review highlights different aspects of the aromaticity of fullerenes and EMFs, starting from how this can be measured and ending by how it can be used to rationalize and predict their molecular structure and reactivity

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Across Latin America 420 indigenous languages are spoken. Spanish is considered a second language in indigenous communities and is progressively introduced in education. However, most of the tools to support teaching processes of a second language have been developed for the most common languages such as English, French, German, Italian, etc. As a result, only a small amount of learning objects and authoring tools have been developed for indigenous people considering the specific needs of their population. This paper introduces Multilingual–Tiny as a web authoring tool to support the virtual experience of indigenous students and teachers when they are creating learning objects in indigenous languages or in Spanish language, in particular, when they have to deal with the grammatical structures of Spanish. Multilingual–Tiny has a module based on the Case-based Reasoning technique to provide recommendations in real time when teachers and students write texts in Spanish. An experiment was performed in order to compare some local similarity functions to retrieve cases from the case library taking into account the grammatical structures. As a result we found the similarity function with the best performance

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We present new analytical tools able to predict the averaged behavior of fronts spreading through self-similar spatial systems starting from reaction-diffusion equations. The averaged speed for these fronts is predicted and compared with the predictions from a more general equation (proposed in a previous work of ours) and simulations. We focus here on two fractals, the Sierpinski gasket (SG) and the Koch curve (KC), for two reasons, i.e. i) they are widely known structures and ii) they are deterministic fractals, so the analytical study of them turns out to be more intuitive. These structures, despite their simplicity, let us observe several characteristics of fractal fronts. Finally, we discuss the usefulness and limitations of our approa