988 resultados para transfer path modeling


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Heat transfer is considered as one of the most critical issues for design and implement of large-scale microwave heating systems, in which improvement of the microwave absorption of materials and suppression of uneven temperature distribution are the two main objectives. The present work focuses on the analysis of heat transfer in microwave heating for achieving highly efficient microwave assisted steelmaking through the investigations on the following aspects: (1) characterization of microwave dissipation using the derived equations, (2) quantification of magnetic loss, (3) determination of microwave absorption properties of materials, (4) modeling of microwave propagation, (5) simulation of heat transfer, and (6) improvement of microwave absorption and heating uniformity. Microwave heating is attributed to the heat generation in materials, which depends on the microwave dissipation. To theoretically characterize microwave heating, simplified equations for determining the transverse electromagnetic mode (TEM) power penetration depth, microwave field attenuation length, and half-power depth of microwaves in materials having both magnetic and dielectric responses were derived. It was followed by developing a simplified equation for quantifying magnetic loss in materials under microwave irradiation to demonstrate the importance of magnetic loss in microwave heating. The permittivity and permeability measurements of various materials, namely, hematite, magnetite concentrate, wüstite, and coal were performed. Microwave loss calculations for these materials were carried out. It is suggested that magnetic loss can play a major role in the heating of magnetic dielectrics. Microwave propagation in various media was predicted using the finite-difference time-domain method. For lossy magnetic dielectrics, the dissipation of microwaves in the medium is ascribed to the decay of both electric and magnetic fields. The heat transfer process in microwave heating of magnetite, which is a typical magnetic dielectric, was simulated by using an explicit finite-difference approach. It is demonstrated that the heat generation due to microwave irradiation dominates the initial temperature rise in the heating and the heat radiation heavily affects the temperature distribution, giving rise to a hot spot in the predicted temperature profile. Microwave heating at 915 MHz exhibits better heating homogeneity than that at 2450 MHz due to larger microwave penetration depth. To minimize/avoid temperature nonuniformity during microwave heating the optimization of object dimension should be considered. The calculated reflection loss over the temperature range of heating is found to be useful for obtaining a rapid optimization of absorber dimension, which increases microwave absorption and achieves relatively uniform heating. To further improve the heating effectiveness, a function for evaluating absorber impedance matching in microwave heating was proposed. It is found that the maximum absorption is associated with perfect impedance matching, which can be achieved by either selecting a reasonable sample dimension or modifying the microwave parameters of the sample.

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In recent years, the bio-conjugated nanostructured materials have emerged as a new class of materials for the bio-sensing and medical diagnostics applications. In spite of their multi-directional applications, interfacing nanomaterials with bio-molecules has been a challenge due to somewhat limited knowledge about the underlying physics and chemistry behind these interactions and also for the complexity of biomolecules. The main objective of this dissertation is to provide such a detailed knowledge on bioconjugated nanomaterials toward their applications in designing the next generation of sensing devices. Specifically, we investigate the changes in the electronic properties of a boron nitride nanotube (BNNT) due to the adsorption of different bio-molecules, ranging from neutral (DNA/RNA nucleobases) to polar (amino acid molecules). BNNT is a typical member of III-V compounds semiconductors with morphology similar to that of carbon nanotubes (CNTs) but with its own distinct properties. More specifically, the natural affinity of BNNTs toward living cells with no apparent toxicity instigates the applications of BNNTs in drug delivery and cell therapy. Our results predict that the adsorption of DNA/RNA nucleobases on BNNTs amounts to different degrees of modulation in the band gap of BNNTs, which can be exploited for distinguishing these nucleobases from each other. Interestingly, for the polar amino acid molecules, the nature of interaction appeared to vary ranging from Coulombic, van der Waals and covalent depending on the polarity of the individual molecules, each with a different binding strength and amount of charge transfer involved in the interaction. The strong binding of amino acid molecules on the BNNTs explains the observed protein wrapping onto BNNTs without any linkers, unlike carbon nanotubes (CNTs). Additionally, the widely varying binding energies corresponding to different amino acid molecules toward BNNTs indicate to the suitability of BNNTs for the biosensing applications, as compared to the metallic CNTs. The calculated I-V characteristics in these bioconjugated nanotubes predict notable changes in the conductivity of BNNTs due to the physisorption of DNA/RNA nucleobases. This is not the case with metallic CNTs whose transport properties remained unaltered in their conjugated systems with the nucleobases. Collectively, the bioconjugated BNNTs are found to be an excellent system for the next generation sensing devices.

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Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

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This work presents a 1-D process scale model used to investigate the chemical dynamics and temporal variability of nitrogen oxides (NOx) and ozone (O3) within and above snowpack at Summit, Greenland for March-May 2009 and estimates surface exchange of NOx between the snowpack and surface layer in April-May 2009. The model assumes the surface of snowflakes have a Liquid Like Layer (LLL) where aqueous chemistry occurs and interacts with the interstitial air of the snowpack. Model parameters and initialization are physically and chemically representative of snowpack at Summit, Greenland and model results are compared to measurements of NOx and O3 collected by our group at Summit, Greenland from 2008-2010. The model paired with measurements confirmed the main hypothesis in literature that photolysis of nitrate on the surface of snowflakes is responsible for nitrogen dioxide (NO2) production in the top ~50 cm of the snowpack at solar noon for March – May time periods in 2009. Nighttime peaks of NO2 in the snowpack for April and May were reproduced with aqueous formation of peroxynitric acid (HNO4) in the top ~50 cm of the snowpack with subsequent mass transfer to the gas phase, decomposition to form NO2 at nighttime, and transportation of the NO2 to depths of 2 meters. Modeled production of HNO4 was hindered in March 2009 due to the low production of its precursor, hydroperoxy radical, resulting in underestimation of nighttime NO2 in the snowpack for March 2009. The aqueous reaction of O3 with formic acid was the major sync of O3 in the snowpack for March-May, 2009. Nitrogen monoxide (NO) production in the top ~50 cm of the snowpack is related to the photolysis of NO2, which underrepresents NO in May of 2009. Modeled surface exchange of NOx in April and May are on the order of 1011 molecules m-2 s-1. Removal of measured downward fluxes of NO and NO2 in measured fluxes resulted in agreement between measured NOx fluxes and modeled surface exchange in April and an order of magnitude deviation in May. Modeled transport of NOx above the snowpack in May shows an order of magnitude increase of NOx fluxes in the first 50 cm of the snowpack and is attributed to the production of NO2 during the day from the thermal decomposition and photolysis of peroxynitric acid with minor contributions of NO from HONO photolysis in the early morning.

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High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

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The study is based on experimental work conducted in alpine snow. We made microwave radiometric and near-infrared reflectance measurements of snow slabs under different experimental conditions. We used an empirical relation to link near-infrared reflectance of snow to the specific surface area (SSA), and converted the SSA into the correlation length. From the measurements of snow radiances at 21 and 35 GHz , we derived the microwave scattering coefficient by inverting two coupled radiative transfer models (the sandwich and six-flux model). The correlation lengths found are in the same range as those determined in the literature using cold laboratory work. The technique shows great potential in the determination of the snow correlation length under field conditions.

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Gene therapy, aimed at the correction of key pathologies being out of reach for conventional drugs, bears the potential to alter the treatment of cardiovascular diseases radically and thereby of heart failure. Heart failure gene therapy refers to a therapeutic system of targeted drug delivery to the heart that uses formulations of DNA and RNA, whose products determine the therapeutic classification through their biological actions. Among resident cardiac cells, cardiomyocytes have been the therapeutic target of numerous attempts to regenerate systolic and diastolic performance, to reverse remodeling and restore electric stability and metabolism. Although the concept to intervene directly within the genetic and molecular foundation of cardiac cells is simple and elegant, the path to clinical reality has been arduous because of the challenge on delivery technologies and vectors, expression regulation, and complex mechanisms of action of therapeutic gene products. Nonetheless, since the first demonstration of in vivo gene transfer into myocardium, there have been a series of advancements that have driven the evolution of heart failure gene therapy from an experimental tool to the threshold of becoming a viable clinical option. The objective of this review is to discuss the current state of the art in the field and point out inevitable innovations on which the future evolution of heart failure gene therapy into an effective and safe clinical treatment relies.

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The spectacular images of Comet 103P/Hartley 2 recorded by the Medium Resolution Instrument (MRI) and High Resolution Instrument (HRI) on board of the Extrasolar Planet Observation and Deep Impact Extended Investigation (EPOXI) spacecraft, as the Deep Impact extended mission, revealed that its bi-lobed very active nucleus outgasses volatiles heterogeneously. Indeed, CO2 is the primary driver of activity by dragging out chunks of pure ice out of the nucleus from the sub-solar lobe that appear to be the main source of water in Hartley 2's coma by sublimating slowly as they go away from the nucleus. However, water vapor is released by direct sublimation of the nucleus at the waist without any significant amount of either CO2 or icy grains. The coma structure for a comet with such areas of diverse chemistry differs from the usual models where gases are produced in a homogeneous way from the surface. We use the fully kinetic Direct Simulation Monte Carlo model of Tenishev et al. (Tenishev, V.M., Combi, M.R., Davidsson, B. [2008]. Astrophys. J. 685, 659-677; Tenishev, V.M., Combi, M.R., Rubin, M. [2011]. Astrophys. J. 732, 104-120) applied to Comet 103P/Hartley 2 including sublimating icy grains to reproduce the observations made by EPOXI and ground-based measurements. A realistic bi-lobed nucleus with a succession of active areas with different chemistry was included in the model enabling us to study in details the coma of Hartley 2. The different gas production rates from each area were found by fitting the spectra computed using a line-by-line non-LTE radiative transfer model to the HRI observations. The presence of icy grains with long lifetimes, which are pushed anti-sunward by radiation pressure, explains the observed OH asymmetry with enhancement on the night side of the coma.

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The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

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Colorectal cancer is the forth most common diagnosed cancer in the United States. Every year about a hundred forty-seven thousand people will be diagnosed with colorectal cancer and fifty-six thousand people lose their lives due to this disease. Most of the hereditary nonpolyposis colorectal cancer (HNPCC) and 12% of the sporadic colorectal cancer show microsatellite instability. Colorectal cancer is a multistep progressive disease. It starts from a mutation in a normal colorectal cell and grows into a clone of cells that further accumulates mutations and finally develops into a malignant tumor. In terms of molecular evolution, the process of colorectal tumor progression represents the acquisition of sequential mutations. ^ Clinical studies use biomarkers such as microsatellite or single nucleotide polymorphisms (SNPs) to study mutation frequencies in colorectal cancer. Microsatellite data obtained from single genome equivalent PCR or small pool PCR can be used to infer tumor progression. Since tumor progression is similar to population evolution, we used an approach known as coalescent, which is well established in population genetics, to analyze this type of data. Coalescent theory has been known to infer the sample's evolutionary path through the analysis of microsatellite data. ^ The simulation results indicate that the constant population size pattern and the rapid tumor growth pattern have different genetic polymorphic patterns. The simulation results were compared with experimental data collected from HNPCC patients. The preliminary result shows the mutation rate in 6 HNPCC patients range from 0.001 to 0.01. The patients' polymorphic patterns are similar to the constant population size pattern which implies the tumor progression is through multilineage persistence instead of clonal sequential evolution. The results should be further verified using a larger dataset. ^

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Even the best school health education programs will be unsuccessful if they are not disseminated effectively in a manner that encourages classroom adoption and implementation. This study involved two components: (1) the development of a videotape intervention to be used in the dissemination phase of a 4-year, NCI-funded diffusion study and (2) the evaluation of that videotape intervention strategy in comparison with a print (information transfer) strategy. Conceptualization has been guided by Social Learning Theory, Diffusion Theory, and communication theory. Additionally, the PRECEDE Framework has been used. Seventh and 8th grade classroom teachers from Spring Branch Independent School District in west Houston participated in the evaluation of the videotape and print interventions using a 57-item preadoption survey instrument developed by the UT Center for Health Promotion Research and Development. Two-way ANOVA was used to study individual score differences for five outcome variables: Total Scale Score (comprised of 57 predisposing, enabling, and reinforcing items), Adoption Characteristics Subscale, Attitude Toward Innovation Subscale, Receptivity Toward Innovation, and Reinforcement Subscale. The aim of the study is to compare the effect upon score differences of video and print interventions alone and in combination. Seventy-three 7th and 8th grade classroom teachers completed the study providing baseline and post-intervention measures on factors related to the adoption and implementation of tobacco-use prevention programs. Two-way ANOVA, in relation to the study questions, found significant scoring differences for those exposed to the videotape intervention alone for both the Attitude Toward Innovation Subscale and the Receptivity to Adopt Subscale. No significant results were found to suggest that print alone influences favorable scoring differences between baseline and post-intervention testing. One interaction effect was found suggesting video and print combined are more effective for influencing favorable scoring differences for the Reinforcement for the Adoption Subscale.^ This research is unique in that it represents a newly emerging field in health promotion communications research with implications for Social Learning Theory, Diffusion Theory, and communication science that are applicable to the development of improved school health interventions. ^

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Developing countries are experiencing unprecedented levels of economic growth. As a result, they will be responsible for most of the future growth in energy demand and greenhouse gas (GHG) emissions. Curbing GHG emissions in developing countries has become one of the cornerstones of a future international agreement under the United Nations Framework Convention for Climate Change (UNFCCC). However, setting caps for developing countries’ GHG emissions has encountered strong resistance in the current round of negotiations. Continued economic growth that allows poverty eradication is still the main priority for most developing countries, and caps are perceived as a constraint to future growth prospects. The development, transfer and use of low-carbon technologies have more positive connotations, and are seen as the potential path towards low-carbon development. So far, the success of the UNFCCC process in improving the levels of technology transfer (TT) to developing countries has been limited. This thesis analyses the causes for such limited success and seeks to improve on the understanding about what constitutes TT in the field of climate change, establish the factors that enable them in developing countries and determine which policies could be implemented to reinforce these factors. Despite the wide recognition of the importance of technology and knowledge transfer to developing countries in the climate change mitigation policy agenda, this issue has not received sufficient attention in academic research. Current definitions of climate change TT barely take into account the perspective of actors involved in actual climate change TT activities, while respective measurements do not bear in mind the diversity of channels through which these happen and the outputs and effects that they convey. Furthermore, the enabling factors for TT in non-BRIC (Brazil, Russia, India, China) developing countries have been seldom investigated, and policy recommendations to improve the level and quality of TTs to developing countries have not been adapted to the specific needs of highly heterogeneous countries, commonly denominated as “developing countries”. This thesis contributes to enriching the climate change TT debate from the perspective of a smaller emerging economy (Chile) and by undertaking a quantitative analysis of enabling factors for TT in a large sample of developing countries. Two methodological approaches are used to study climate change TT: comparative case study analysis and quantitative analysis. Comparative case studies analyse TT processes in ten cases based in Chile, all of which share the same economic, technological and policy frameworks, thus enabling us to draw conclusions on the enabling factors and obstacles operating in TT processes. The quantitative analysis uses three methodologies – principal component analysis, multiple regression analysis and cluster analysis – to assess the performance of developing countries in a number of enabling factors and the relationship between these factors and indicators of TT, as well as to create groups of developing countries with similar performances. The findings of this thesis are structured to provide responses to four main research questions: What constitutes technology transfer and how does it happen? Is it possible to measure technology transfer, and what are the main challenges in doing so? Which factors enable climate change technology transfer to developing countries? And how do different developing countries perform in these enabling factors, and how can differentiated policy priorities be defined accordingly? vi Resumen Los paises en desarrollo estan experimentando niveles de crecimiento economico sin precedentes. Como consecuencia, se espera que sean responsables de la mayor parte del futuro crecimiento global en demanda energetica y emisiones de Gases de Efecto de Invernadero (GEI). Reducir las emisiones de GEI en los paises en desarrollo es por tanto uno de los pilares de un futuro acuerdo internacional en el marco de la Convencion Marco de las Naciones Unidas para el Cambio Climatico (UNFCCC). La posibilidad de compromisos vinculantes de reduccion de emisiones de GEI ha sido rechazada por los paises en desarrollo, que perciben estos limites como frenos a su desarrollo economico y a su prioridad principal de erradicacion de la pobreza. El desarrollo, transferencia y uso de tecnologias bajas en carbono tiene connotaciones mas positivas y se percibe como la via hacia un crecimiento bajo en carbono. Hasta el momento, la UNFCCC ha tenido un exito limitado en la promocion de transferencias de tecnologia (TT) a paises en desarrollo. Esta tesis analiza las causas de este resultado y busca mejorar la comprension sobre que constituye transferencia de tecnologia en el area de cambio climatico, cuales son los factores que la facilitan en paises en desarrollo y que politicas podrian implementarse para reforzar dichos factores. A pesar del extendido reconocimiento sobre la importancia de la transferencia de tecnologia a paises en desarrollo en la agenda politica de cambio climatico, esta cuestion no ha sido suficientemente atendida por la investigacion existente. Las definiciones actuales de transferencia de tecnologia relacionada con la mitigacion del cambio climatico no tienen en cuenta la diversidad de canales por las que se manifiestan o los efectos que consiguen. Los factores facilitadores de TT en paises en desarrollo no BRIC (Brasil, Rusia, India y China) apenas han sido investigados, y las recomendaciones politicas para aumentar el nivel y la calidad de la TT no se han adaptado a las necesidades especificas de paises muy heterogeneos aglutinados bajo el denominado grupo de "paises en desarrollo". Esta tesis contribuye a enriquecer el debate sobre la TT de cambio climatico con la perspectiva de una economia emergente de pequeno tamano (Chile) y el analisis cuantitativo de factores que facilitan la TT en una amplia muestra de paises en desarrollo. Se utilizan dos metodologias para el estudio de la TT a paises en desarrollo: analisis comparativo de casos de estudio y analisis cuantitativo basado en metodos multivariantes. Los casos de estudio analizan procesos de TT en diez casos basados en Chile, para derivar conclusiones sobre los factores que facilitan u obstaculizan el proceso de transferencia. El analisis cuantitativo multivariante utiliza tres metodologias: regresion multiple, analisis de componentes principales y analisis cluster. Con dichas metodologias se busca analizar el posicionamiento de diversos paises en cuanto a factores que facilitan la TT; las relaciones entre dichos factores e indicadores de transferencia tecnologica; y crear grupos de paises con caracteristicas similares que podrian beneficiarse de politicas similares para la promocion de la transferencia de tecnologia. Los resultados de la tesis se estructuran en torno a cuatro preguntas de investigacion: .Que es la transferencia de tecnologia y como ocurre?; .Es posible medir la transferencia de tecnologias de bajo carbono?; .Que factores facilitan la transferencia de tecnologias de bajo carbono a paises en desarrollo? y .Como se puede agrupar a los paises en desarrollo en funcion de sus necesidades politicas para la promocion de la transferencia de tecnologias de bajo carbono?

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Modeling and prediction of the overall elastic–plastic response and local damage mechanisms in heterogeneous materials, in particular particle reinforced composites, is a very complex problem. Microstructural complexities such as the inhomogeneous spatial distribution of particles, irregular morphology of the particles, and anisotropy in particle orientation after secondary processing, such as extrusion, significantly affect deformation behavior. We have studied the effect of particle/matrix interface debonding in SiC particle reinforced Al alloy matrix composites with (a) actual microstructure consisting of angular SiC particles and (b) idealized ellipsoidal SiC particles. Tensile deformation in SiC particle reinforced Al matrix composites was modeled using actual microstructures reconstructed from serial sectioning approach. Interfacial debonding was modeled using user-defined cohesive zone elements. Modeling with the actual microstructure (versus idealized ellipsoids) has a significant influence on: (a) localized stresses and strains in particle and matrix, and (b) far-field strain at which localized debonding takes place. The angular particles exhibited higher degree of load transfer and are more sensitive to interfacial debonding. Larger decreases in stress are observed in the angular particles, because of the flat surfaces, normal to the loading axis, which bear load. Furthermore, simplification of particle morphology may lead to erroneous results.

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This article presents the design, kinematic model and communication architecture for the multi-agent robotic system called SMART. The philosophy behind this kind of system requires the communication architecture to contemplate the concurrence of the whole system. The proposed architecture combines different communication technologies (TCP/IP and Bluetooth) under one protocol designed for the cooperation among agents and other elements of the system such as IP-Cameras, image processing library, path planner, user Interface, control block and data block. The high level control is modeled by Work-Flow Petri nets and implemented in C++ and C♯♯. Experimental results show the performance of the designed architecture.

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The characteristics of the power-line communication (PLC) channel are difficult to model due to the heterogeneity of the networks and the lack of common wiring practices. To obtain the full variability of the PLC channel, random channel generators are of great importance for the design and testing of communication algorithms. In this respect, we propose a random channel generator that is based on the top-down approach. Basically, we describe the multipath propagation and the coupling effects with an analytical model. We introduce the variability into a restricted set of parameters and, finally, we fit the model to a set of measured channels. The proposed model enables a closed-form description of both the mean path-loss profile and the statistical correlation function of the channel frequency response. As an example of application, we apply the procedure to a set of in-home measured channels in the band 2-100 MHz whose statistics are available in the literature. The measured channels are divided into nine classes according to their channel capacity. We provide the parameters for the random generation of channels for all nine classes, and we show that the results are consistent with the experimental ones. Finally, we merge the classes to capture the entire heterogeneity of in-home PLC channels. In detail, we introduce the class occurrence probability, and we present a random channel generator that targets the ensemble of all nine classes. The statistics of the composite set of channels are also studied, and they are compared to the results of experimental measurement campaigns in the literature.