Contribution to dimensionality reduction of digital predistorter behavioral models for RF power amplifier linearization

The power efficiency and linearity of radio frequency (RF) power amplifiers (PAs) are critical in wireless communication systems. The main scope of PA designers is to build the RF PAs capable to maintain high efficiency and linearity figures simultaneously. However, these figures are inherently conflicted to each other and system-level solutions based on linearization techniques are required. Digital predistortion (DPD) linearization has become the most widely used solution to mitigate the efficiency versus linearity trade-off. The dimensionality of the DPD model depends on the complexity of the system. It increases significantly in high efficient amplification architectures when considering current wideband and spectrally efficient technologies. Overparametrization may lead to an ill-conditioned least squares (LS) estimation of the DPD coefficients, which is usually solved by employing regularization techniques. However, in order to both reduce the computational complexity and avoid ill-conditioning problems derived from overparametrization, several efforts have been dedicated to investigate dimensionality reduction techniques to reduce the order of the DPD model. This dissertation contributes to the dimensionality reduction of DPD linearizers for RF PAs with emphasis on the identification and adaptation subsystem. In particular, several dynamic model order reduction approaches based on feature extraction techniques are proposed. Thus, the minimum number of relevant DPD coefficients are dynamically selected and estimated in the DPD adaptation subsystem. The number of DPD coefficients is reduced, ensuring a well-conditioned LS estimation while demanding minimum hardware resources. The presented dynamic linearization approaches are evaluated and compared through experimental validation with an envelope tracking PA and a class-J PA The experimental results show similar linearization performance than the conventional LS solution but at lower computational cost.La eficiencia energetica y la linealidad de los amplificadores de potencia (PA) de radiofrecuencia (RF) son fundamentales en los sistemas de comunicacion inalambrica. El principal objetivo a alcanzar en el diserio de amplificadores de radiofrecuencia es lograr simultaneamente elevadas cifras de eficiencia y de linealidad. Sin embargo, estas cifras estan inherentemente en conflicto entre si, y se requieren soluciones a nivel de sistema basadas en tecnicas de linealizacion. La linealizacion mediante predistorsion digital (DPD) se ha convertido en la solucion mas utilizada para mitigar el compromise entre eficiencia y linealidad. La dimension del modelo del predistorsionador DPD depende de la complejidad del sistema, y aumenta significativamente en las arquitecturas de amplificacion de alta eficiencia cuando se consideran los actuales anchos de banda y las tecnologfas espectralmente eficientes. El exceso de parametrizacion puede conducir a una estimacion de los coeficientes DPD, mediante minimos cuadrados (LS), mal condicionada, lo cual generalmente se resuelve empleando tecnicas de regularizacion. Sin embargo, con el fin de reducir la complejidad computacional y evitar dichos problemas de mal acondicionamiento derivados de la sobreparametrizacion, se han dedicado varies esfuerzos para investigar tecnicas de reduccion de dimensionalidad que permitan reducir el orden del modelo del DPD. Esta tesis doctoral contribuye a aportar soluciones para la reduccion de la dimension de los linealizadores DPD para RF PA, centrandose en el subsistema de identificacion y adaptacion. En concrete, se proponen varies enfoques de reduccion de orden del modelo dinamico, basados en tecnicas de extraccion de caracteristicas. El numero minimo de coeficientes DPD relevantes se seleccionan y estiman dinamicamente en el subsistema de adaptacion del DPD, y de este modo la cantidad de coeficientes DPD se reduce, lo cual ademas garantiza una estimacion de LS bien condicionada al tiempo que exige menos recursos de hardware. Las propuestas de linealizacion dinamica presentados en esta tesis se evaluan y comparan mediante validacion experimental con un PA de seguimiento de envolvente y un PA tipo clase J. Los resultados experimentales muestran unos resultados de linealizacion de los PA similares a los obtenidos cuando se em plea la solucion LS convencional, pero con un coste computacional mas reducido.Postprint (published version

Generation of plasmon-polaritons in epsilon-near-zero polaritonic metamaterial

In this paper, we study the generation of plasmon-polaritons in the epsilon-near-zero nanorod polaritonic metamaterial by using nonlocal effective medium approximation (EMT). The results indicate that the nonlocal EMT is the simplest and most accurate approach to describe the characteristics of plasmon-polaritons at the epsilon-near-zero regime (e ≈ 0) in the polaritonic metamaterial. In contrast, the Maxwell-Garnett effective medium approximation is considered to be the most general method to study the generated plasmon-polaritons in metamaterials. An additional plasmon-polariton is found in the polaritonic metamaterial through the nonlocal EMT, which could not be found with the Maxwell-Garnett EMT. A flat longitudinal wave-number of the excited plasmon-polariton occurs in the angle of incident light ranging from –20 to 20°, leading to the collinear group-velocity vectors, and its energy will be carried in one direction. The findings can be used in some applications in optical communication

Norepinephrine and dopamine increase motility, biofilm formation and virulence of Vibrio harveyi

Vibrio harveyi is one of the major pathogens of aquatic organisms, affecting both vertebrates and invertebrates, and causes important losses in the aquaculture industry. In order to develop novel methods to control disease caused by this pathogen, we need to obtain a better understanding of pathogenicity mechanisms. Sensing of catecholamines increases both growth and production of virulence-related factors in pathogens of terrestrial animals and humans. However, at this moment, knowledge on the impact of catecholamines on the virulence of pathogens of aquatic organisms is lacking. In the present study, we report that in V harveyi, norepinephrine (NE) and dopamine (Dopa) increased growth in serum-supplemented medium, siderophore production, swimming motility, and expression of genes involved in flagellar motility, biofilm formation, and exopolysaccharide production. Consistent with this, pretreatment of V harveyi with catecholamines prior to inoculation into the rearing water resulted in significantly decreased survival of gnotobiotic brine shrimp larvae, when compared to larvae challenged with untreated V harveyi. Further, NE-induced effects could be neutralized by alpha-adrenergic antagonists or by the bacterial catecholamine receptor antagonist LED209, but not by beta-adrenergic or dopaminergic antagonists. Dopa-induced effects could be neutralized by dopaminergic antagonists or LED209, but not by adrenergic antagonists. Together, our results indicate that catecholamine sensing increases the success of transmission of V harveyi and that interfering with catecholamine sensing might be an interesting strategy to control vibriosis in aquaculture. We hypothesize that upon tissue and/or hemocyte damage during infection, pathogens come into contact with elevated catecholamine levels, and that this stimulates the expression of virulence factors that are required to colonize a new host

Temporal patterns of synchrony in a pyramidal-interneuron gamma (PING) network

Synchronization in neural system plays an important role in many brain functions. Synchronization in the gamma frequency band (30Hz-100Hz) is involved in a variety of cognitive phenomena; abnormalities of the gamma synchronization are found in schizophrenia and autism spectrum disorder. Frequently, the strength of synchronization is not very high and is intermittent even on short time scales (a few cycles of oscillations). That is, the network exhibits intervals of synchronization followed by intervals of desynchronization. Neural circuits dynamics may show different distributions of desynchronization durations even if the synchronization strength is fixed. In this study, we use a conductance-based neural network exhibiting pyramidal-interneuron (PING) gamma rhythm to study the temporal patterning of synchronized neural oscillations. We found that changes in the synaptic strength (as well as changes in the membrane kinetics) can alter the temporal patterning of synchrony. Moreover, we found that the changes in the temporal pattern of synchrony may be independent of the changes in the average synchrony strength. Even though the temporal patterning may vary, there is a tendency for dynamics with short (although potentially numerous) desynchronizations, similar to what was observed in experimental studies of neural activity synchronization in the brain. Recent studies suggested that the short desynchronizations dynamics may facilitate the formation and the break-up of transient neural assemblies. Thus, the results of this study suggest that changes of synaptic strength may alter the temporal patterning of the gamma synchronization as to make the neural networks more efficient in the formation of neural assemblies and the facilitation of cognitive phenomena

The Impact of Foreign Direct Investment on Economic Growth: Evidence from Vietnam

The relationship between Foreign Direct Investment (FDI) and economic growth has long been a topic of great interest in the field of international development. Although this interest has provided rich insights into the impact of FDI on growth in developing countries, there are very few empirical analyses of the linkage in Vietnam compared to other developing countries. Therefore, this study investigates the impact of FDI inflows on economic growth in Vietnam over the period from 1990 to 2013 using time series analysis techniques that address the problem of nonstationarity. Specifically, the Unit root test and Cointegration approach are applied to ensure that the regressions are not spurious. The empirical results reveal that FDI inflows, domestic investment, trade openness and secondary education have positive impacts on economic growth whereas inflation rate is found to have negative effect on economic growth. In addition, the impact of government consumption on economic growth is negative and statistically insignificant. Ultimately, this paper suggests that Vietnamese government should improve regulations governing business activities by easing the process of business start-up, controlling price, enhancing public spending on education and training, and augmenting cooperation between training centers and Foreign-invested enterprises. Keywords: Foreign Direct Investment, economic growth, time series, unit root test, cointegration, Vietnam

Encapsulation of Peanut Allergens with Bimetallic Metal-Phenolic Networks (MPNs) for Therapeutic Applications

The efficacy and safety of oral immunotherapy for food allergy is still an ongoing challenge. Plant-derived polyphenols have been shown to exhibit immunomodulatory action through their anti-inflammatory and antioxidant properties. This thesis explored a synthesis of dual-functional pH-responsive metal-phenolic networks (MPNs) encapsulated peanut allergens using plant phenolics as an immunomodulating “adjuvant”. The compatibility of ferric/ferrous (Fe3+/Fe2+) and zinc ion (Zn2+) with plant-derived phenolics, tannic acid (TA) and catechin hydrate (CTC), was investigated for the formation of stable MPN film and encapsulation of peanut crude protein. Using bovine serum albumin (BSA) as a template biomolecule, it was demonstrated that the concentration/molar ratio between different metal ions and between metal ions and phenolics, order of reagent addition, synthesis methods and pH change during the synthesis influenced the final colour, size, and overall surface charge of the particles. The optimum condition for each tested MPN system with the protein template tested varied significantly. In the two bimetallic systems, Fe3+ showed the strongest interaction with the other coordinating ions, and with phenolics, followed by Fe2+ and then Zn2+. The morphological and elemental analysis of the BSA-Fe2+/Zn2+-CTC MPN confirmed the spherical particles presented in clusters and that a significantly higher Fe2+ than Zn2+ presented in the bimetallic MPN system. The selected bimetallic Fe2+/Zn2+-CTC MPN was implemented in the encapsulation of peanut crude protein with mixed molecular weight (MW) proteins and the major allergen, Ara h 1. More negatively charged nanoparticles were observed for the crude protein capsules compared to Ara h 1 capsules. The pH-responsive controlled release of the crude peanut-MPN capsules under the simulated gastric condition revealed that protein-MPN capsules with final pH of 6.3 were more stable than those with pH 3.9. The former had small amounts of residues remaining intact, whilst the latter dissociated completely after 2 hr digestion. The MPN capsules disassembled immediately after being exposed to the acidic condition and the dissociation rate was faster at pH 2 than pH 3. The released peanut protein was still immunoreactive. The pH-responsive peanut-MPN capsules using the bimetallic system with immunomodulating plant polyphenols could be a prospective allergen delivery system for oral immunotherapy