967 resultados para Flux variability analysis


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In this work the differentiability of the principal eigenvalue lambda = lambda(1)(Gamma) to the localized Steklov problem -Delta u + qu = 0 in Omega, partial derivative u/partial derivative nu = lambda chi(Gamma)(x)u on partial derivative Omega, where Gamma subset of partial derivative Omega is a smooth subdomain of partial derivative Omega and chi(Gamma) is its characteristic function relative to partial derivative Omega, is shown. As a key point, the flux subdomain Gamma is regarded here as the variable with respect to which such differentiation is performed. An explicit formula for the derivative of lambda(1) (Gamma) with respect to Gamma is obtained. The lack of regularity up to the boundary of the first derivative of the principal eigenfunctions is a further intrinsic feature of the problem. Therefore, the whole analysis must be done in the weak sense of H(1)(Omega). The study is of interest in mathematical models in morphogenesis. (C) 2011 Elsevier Inc. All rights reserved.

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Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.

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The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.

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The use of numerical simulation in the design and evaluation of products performance is ever increasing. To a greater extent, such estimates are needed in a early design stage, when physical prototypes are not available. When dealing with vibro-acoustic models, known to be computationally expensive, a question remains, which is related to the accuracy of such models in view of the well-know variability inherent to the mass manufacturing production techniques. In addition, both academia and industry have recently realized the importance of actually listening to a products sound, either by measurements or by virtual sound synthesis, in order to assess its performance. In this work, the scatter of significant parameter variations on a simplified vehicle vibro-acoustic model is calculated on loudness metrics using Monte Carlo analysis. The mapping from the system parameters to sound quality metric is performed by a fully-coupled vibro-acoustic finite element model. Different loudness metrics are used, including overall sound pressure level expressed in dB and Specific Loudness in Sones. Sound quality equivalent sources are used to excite this model and the sound pressure level at the driver's head position is acquired to be evaluated according to sound quality metrics. No significant variation has been perceived when evaluating the system using regular sound pressure level expressed in in dB and dB(A). This happens because of the third-octave filters that averages the results under some frequency bands. On the other hand, Zwicker Loudness presents important variations, arguably, due to the masking effects.

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Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.

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The two main tools to determine the dynamical and physical parameters of exoplanet systems are the radial velocity (RV) measurements and, when available, transit timings. The two techniques are complementary: The RV's allow us to know some of the orbital elements while the transit timings allow us to obtain the orbital inclination and planetary radius, impossible of obtain from the RV, and to resolve the indetermination in the determination of the planet mass from the RV's. The space observation of transiting planets is however not limited to transit times. They extend to long periods of time and are precise enough to provide information on variations along the orbit. Besides the effects of stellar rotation, deserve mention the Doppler shift in the radiation flux, as consequence of stellar movement around the center of mass, or Beaming Effect (BE); the Ellipsoidal Variability (EV) due to the tidal deformation of the star due to the gravitation of its close companion; and the Reflection (ER) of the stellar radiation incident on the planet and re-emitted to the observer. In the case of large hot Jupiters, these effects are enhanced by the strong gravitational interaction and the analysis of the light variation allows us independent estimates of the mass and radius of planet. The planetary system CoRoT 3 is favorable for such analysis. In this case, the secondary is a brown dwarf whose mass is of the order of 22Mj. We show results obtained from the analysis of 35 RV measurements, 236999 photometric observations and 11 additional RV observations made during a transit to determine the star rotation via the Rossiter-McLaughlin effect. The results obtained from this determination are presented in this communication. The results are compared to those resulting from other determinations.

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We report on four years of observations of 3C 273 at 7mm obtained with the Itapetinga radio telescope, in Brazil, between 2009 and 2013. We detected a flare in 2010 March, when the flux density increased by 50 per cent and reached 35 Jy. After the flare, the flux density started to decrease and reached values lower than 10 Jy. We suggest that the 7-mm flare is the radio counterpart of the γ -ray flare observed by the Fermi Large Area Telescope in 2009 September, in which the flux density at high energies reached a factor of 50 of its average value. A delay of 170 d between the radio and γ -ray flares was revealed using the discrete correlation function (DCF) that can be interpreted in the context of a shock model, in which each flare corresponds to the formation of a compact superluminal component that expands and becomes optically thin at radio frequencies at latter epochs. The differences in flare intensity between frequencies and at different times are explained as a consequence of an increase in the Doppler factor δ, as predicted by the 16-yr precession model proposed by Abraham & Romero. This increase has a large effect on boosting at high frequencies while it does not affect the observed optically thick radio emission too much. We discuss other observable effects of the variation in δ, such as the increase in the formation rate of superluminal components, the variations in the time delay between flares and the periodic behaviour of the radio light curve that we have found to be compatible with changes in the Doppler factor.

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Membrane proteins are a large and important class of proteins. They are responsible for several of the key functions in a living cell, e.g. transport of nutrients and ions, cell-cell signaling, and cell-cell adhesion. Despite their importance it has not been possible to study their structure and organization in much detail because of the difficulty to obtain 3D structures. In this thesis theoretical studies of membrane protein sequences and structures have been carried out by analyzing existing experimental data. The data comes from several sources including sequence databases, genome sequencing projects, and 3D structures. Prediction of the membrane spanning regions by hydrophobicity analysis is a key technique used in several of the studies. A novel method for this is also presented and compared to other methods. The primary questions addressed in the thesis are: What properties are common to all membrane proteins? What is the overall architecture of a membrane protein? What properties govern the integration into the membrane? How many membrane proteins are there and how are they distributed in different organisms? Several of the findings have now been backed up by experiments. An analysis of the large family of G-protein coupled receptors pinpoints differences in length and amino acid composition of loops between proteins with and without a signal peptide and also differences between extra- and intracellular loops. Known 3D structures of membrane proteins have been studied in terms of hydrophobicity, distribution of secondary structure and amino acid types, position specific residue variability, and differences between loops and membrane spanning regions. An analysis of several fully and partially sequenced genomes from eukaryotes, prokaryotes, and archaea has been carried out. Several differences in the membrane protein content between organisms were found, the most important being the total number of membrane proteins and the distribution of membrane proteins with a given number of transmembrane segments. Of the properties that were found to be similar in all organisms, the most obvious is the bias in the distribution of positive charges between the extra- and intracellular loops. Finally, an analysis of homologues to membrane proteins with known topology uncovered two related, multi-spanning proteins with opposite predicted orientations. The predicted topologies were verified experimentally, providing a first example of "divergent topology evolution".

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Memoria presentada para optar al Diploma de Estudios Avanzados en Ciencias del Mar

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Trabajo realizado por: Packard, T. T., Osma, N., Fernández Urruzola, I., Gómez, M

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La variabilità genetica è un importante strumento per lo studio e la conservazione della biodiversità in specie rare e minacciate di estinzione. Durante il mio dottorato mi sono quindi occupata di mettere a punto diverse metodologie molecolari al fine di valutare la diversità genetica in due specie rare della flora italiana che presentano problematiche diverse e specifiche. I marcatori arbitrari RAPD e i marcatori semi-arbitrari ISSR sono stati utilizzati per valutare la diversità genetica in Quercus crenata Lam. e per confermare l’ipotesi della sua origine ibridogena dalle due specie presunte parentali Quercus cerris L. e Quercus suber L., essendo Q. crenata presente in Italia settentrionale dove Q. suber è attualmente assente. I marcatori SSR o microsatelliti sono invece stati messi a punto su una specie a rischio di estinzione, endemica dell’Appennino Tosco-Emiliano, Primula apennina Widmer, applicando una metodologia specifica, basata sulla costruzione di una libreria genomica arricchita per l’isolamento di primer specifici. I marcatori RAPD e ISSR, utilizzati su un totale di 85 campioni, hanno mostrato alti livelli di diversità molecolare entro le specie studiate, eccetto per Q. suber le cui popolazioni rappresentano il margine orientale di distribuzione della specie, per questo più sottoposte ad impoverimento genetico. Oltre alla cluster analysis (UPGMA) e alla Analisi delle Componenti Principali effettuate per entrambi i marcatori, che confermano l’ipotesi dell’origine ibrida degli individui di Q. crenata diffusi in Italia Settentrionale, sono stati calcolati l’indice di ibridità basato sul maximum likelihood, che dimostra una introgressione asimmetrica di Q. crenata verso il parentale caratterizzato da superiorità demografica (Q. cerris) e il test di Mantel. Quest’ultimo ha permesso di confrontare i due marcatori RAPD e ISSR utilizzati ottenendo una bassa correlazione, a conferma del fatto che, amplificando tratti differenti del DNA nucleare, i dati non sono sovrapponibili, sebbene forniscano risultati analoghi. Per l’isolamento di loci microsatelliti ipervariabili ho utilizzato il protocolllo FIASCO (Fast isolation by AFLP of sequences containing repeats- Zane et al. 2002) che permette di costruire una libreria genomica arricchita partendo dal DNA estratto da P. apennina. Tale procedura ha previsto la digestione del DNA genomico per la produzione di una miscela di frammenti di DNA. Tramite ibridazione con opportune sonde sono stati isolati i frammenti contenenti i microsatelliti. Sequenziando i cloni ricombinanti, ho ottenuto sequenze contenenti repeats sulle cui regioni fiancheggianti sono stati costruiti 15 coppie di primer che potranno, in seguito, essere utilizzate per definire la quota di riproduzione clonale in P. apennina e per valutare la diversità genetica delle popolazioni che coprono l’areale di distribuzione della specie. Data la loro natura altamente variabile e la loro abbondanza nel DNA, gli SSR saranno, come i marcatori RAPD e gli ISSR, ugualmente validi per lo studio della variabilità genetica e per l’analisi di problematiche specifiche legate alle specie rare.

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In Performance-Based Earthquake Engineering (PBEE), evaluating the seismic performance (or seismic risk) of a structure at a designed site has gained major attention, especially in the past decade. One of the objectives in PBEE is to quantify the seismic reliability of a structure (due to the future random earthquakes) at a site. For that purpose, Probabilistic Seismic Demand Analysis (PSDA) is utilized as a tool to estimate the Mean Annual Frequency (MAF) of exceeding a specified value of a structural Engineering Demand Parameter (EDP). This dissertation focuses mainly on applying an average of a certain number of spectral acceleration ordinates in a certain interval of periods, Sa,avg (T1,…,Tn), as scalar ground motion Intensity Measure (IM) when assessing the seismic performance of inelastic structures. Since the interval of periods where computing Sa,avg is related to the more or less influence of higher vibration modes on the inelastic response, it is appropriate to speak about improved IMs. The results using these improved IMs are compared with a conventional elastic-based scalar IMs (e.g., pseudo spectral acceleration, Sa ( T(¹)), or peak ground acceleration, PGA) and the advanced inelastic-based scalar IM (i.e., inelastic spectral displacement, Sdi). The advantages of applying improved IMs are: (i ) "computability" of the seismic hazard according to traditional Probabilistic Seismic Hazard Analysis (PSHA), because ground motion prediction models are already available for Sa (Ti), and hence it is possibile to employ existing models to assess hazard in terms of Sa,avg, and (ii ) "efficiency" or smaller variability of structural response, which was minimized to assess the optimal range to compute Sa,avg. More work is needed to assess also "sufficiency" and "scaling robustness" desirable properties, which are disregarded in this dissertation. However, for ordinary records (i.e., with no pulse like effects), using the improved IMs is found to be more accurate than using the elastic- and inelastic-based IMs. For structural demands that are dominated by the first mode of vibration, using Sa,avg can be negligible relative to the conventionally-used Sa (T(¹)) and the advanced Sdi. For structural demands with sign.cant higher-mode contribution, an improved scalar IM that incorporates higher modes needs to be utilized. In order to fully understand the influence of the IM on the seismis risk, a simplified closed-form expression for the probability of exceeding a limit state capacity was chosen as a reliability measure under seismic excitations and implemented for Reinforced Concrete (RC) frame structures. This closed-form expression is partuclarly useful for seismic assessment and design of structures, taking into account the uncertainty in the generic variables, structural "demand" and "capacity" as well as the uncertainty in seismic excitations. The assumed framework employs nonlinear Incremental Dynamic Analysis (IDA) procedures in order to estimate variability in the response of the structure (demand) to seismic excitations, conditioned to IM. The estimation of the seismic risk using the simplified closed-form expression is affected by IM, because the final seismic risk is not constant, but with the same order of magnitude. Possible reasons concern the non-linear model assumed, or the insufficiency of the selected IM. Since it is impossibile to state what is the "real" probability of exceeding a limit state looking the total risk, the only way is represented by the optimization of the desirable properties of an IM.

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In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

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During recent years a consistent number of central nervous system (CNS) drugs have been approved and introduced on the market for the treatment of many psychiatric and neurological disorders, including psychosis, depression, Parkinson disease and epilepsy. Despite the great advancements obtained in the treatment of CNS diseases/disorders, partial response to therapy or treatment failure are frequent, at least in part due to poor compliance, but also genetic variability in the metabolism of psychotropic agents or polypharmacy, which may lead to sub-therapeutic or toxic plasma levels of the drugs, and finally inefficacy of the treatment or adverse/toxic effects. With the aim of improving the treatment, reducing toxic/side effects and patient hospitalisation, Therapeutic Drug Monitoring (TDM) is certainly useful, allowing for a personalisation of the therapy. Reliable analytical methods are required to determine the plasma levels of psychotropic drugs, which are often present at low concentrations (tens or hundreds of nanograms per millilitre). The present PhD Thesis has focused on the development of analytical methods for the determination of CNS drugs in biological fluids, including antidepressants (sertraline and duloxetine), antipsychotics (aripiprazole), antiepileptics (vigabatrin and topiramate) and antiparkinsons (pramipexole). Innovative methods based on liquid chromatography or capillary electrophoresis coupled to diode-array or laser-induced fluorescence detectors have been developed, together with the suitable sample pre-treatment for interference removal and fluorescent labelling in case of LIF detection. All methods have been validated according to official guidelines and applied to the analysis of real samples obtained from patients, resulting suitable for the TDM of psychotropic drugs.