Influência do ganho de massa corporal, induzido por dieta rica em sacarose, em parâmetros biométricos, bioquímicos e biofísicos de ratos Wistar

Pós-graduação em Ciências Fisiológicas - FOA

Evapotranspiração regional utilizando imagens orbitais para a Amazônia Oriental

A evapotranspiração (ET) foi espacializada através do algoritmo SEBAL para uma região de floresta primária na Amazônia Oriental (Caxiuanã, Pará). Para tal, utilizaram-se dados observacionais da torre micrometeorológica (localizada no interior desta floresta) em combinação com dados de origem orbital (imagens Modis/Acqua). Os primeiros resultados indicaram que, apesar da superestimativa, o SEBAL reproduz qualitativamente bem o padrão da variabilidade mensal da evapotranspiração para a região, principalmente para os meses da estação seca; em relação ao quantitativo, os resultados revelaram haver necessidade de acurácia no algoritmo. Para isso, calibrou-se o SEBAL a partir do saldo de radiação (Rn), com ajustes no albedo, na emissividade atmosférica e emissividade da superfície. As estimativas de ET geradas a partir deste SEBAL modificado apresentaram melhorias significativas na reprodução da variabilidade diária da evapotranspiração para a região, principalmente nos meses da estação chuvosa. Isto é, os ajustes realizados no algoritmo mostraram que as taxas de ET estimadas tornaram-se muito mais semelhantes às relatadas na literatura para a Amazônia, concordando melhor com a evapotranspiração observada. Através do SEBAL modificado foi possível também mapear o albedo, o saldo de radiação, o NDVI e a própria ET para duas vegetações distintas, encontradas dentro dos limites de Caxiuanã. A estimativa espacial destes parâmetros biofísicos foi coerentemente reproduzida para as duas vegetações, demonstrando que se o SEBAL modificado for aplicado a dados temporal e espacial de alta resolução, esta técnica pode ser rotineiramente utilizada, tornando-se uma ferramenta fundamental no monitoramento de necessidades hídricas e atmosféricas.

Aspectos topográficos na dinâmica espaço-temporal do saldo de radiação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Informationsgehalt von ERS-1/-2 SAR-Daten zur Erfassung der Arteninventare und des Zustandes landwirtschaftlich genutzter Böden und Vegetation

Auf einer drei Anbauperioden umfassenden Ground Truth Datenbasis wird der Informationsgehalt multitemporaler ERS-1/-2 Synthetic Aperture Radar (SAR) Daten zur Erfassung der Arteninventare und des Zustandes landwirtschaftlich genutzter Böden und Vegetation in Agrarregionen Bayerns evaluiert.Dazu wird ein für Radardaten angepaßtes, multitemporales, auf landwirtschaftlichen Schlägen beruhendes Klassifizierungsverfahren ausgearbeitet, das auf bildstatistischen Parametern der ERS-Zeitreihen beruht. Als überwachte Klassifizierungsverfahren wird vergleichend der Maximum-Likelihood-Klassifikator und ein Neuronales-Backpropagation-Netz eingesetzt. Die auf Radarbildkanälen beruhenden Gesamtgenauigkeiten variieren zwischen 75 und 85%. Darüber hinaus wird gezeigt, daß die interferometrische Kohärenz und die Kombination mit Bildkanälen optischer Sensoren (Landsat-TM, SPOT-PAN und IRS-1C-PAN) zur Verbesserung der Klassifizierung beitragen. Gleichermaßen können die Klassifizierungsergebnisse durch eine vorgeschaltete Grobsegmentierung des Untersuchungsgebietes in naturräumlich homogene Raumeinheiten verbessert werden. Über die Landnutzungsklassifizierung hinaus, werden weitere bio- und bodenphysikalische Parameter aus den SAR-Daten anhand von Regressionsmodellen abgeleitet. Im Mittelpunkt stehen die Paramter oberflächennahen Bodenfeuchte vegetationsfreier/-armer Flächen sowie die Biomasse landwirtschaftlicher Kulturen. Die Ergebnisse zeigen, daß mit ERS-1/-2 SAR-Daten eine Messung der Bodenfeuchte möglich ist, wenn Informationen zur Bodenrauhigkeit vorliegen. Hinsichtlich der biophysikalischen Parameter sind signifikante Zusammenhänge zwischen der Frisch- bzw. Trockenmasse des Vegetationsbestandes verschiedener Getreide und dem Radarsignal nachweisbar. Die Biomasse-Informationen können zur Korrektur von Wachstumsmodellen genutzt werden und dazu beitragen, die Genauigkeit von Ertragsschätzungen zu steigern.

Materno-fetal nutrient transfer across primary human trophoblast layer.

MATERNO-FETAL NUTRIENT TRANSFER ACROSS PRIMARY HUMAN TROPHOBLAST MONOLAYER Objectives: Polarized trophoblasts represent the transport and metabolic barrier between the maternal and fetal circulation. Currently human placental nutrient transfer in vitro is mainly investigated unidirectionallyon cultured primary trophoblasts, or bidirectionally on the Transwell® system using BeWo cells treated with forskolin. As forskolin can induce various gene alterations (e.g. cAMP response element genes), we aimed to establish a physiological primary trophoblast model for materno-fetal nutrient exchange studies without forskolin application. Methods: Human term cytotrophoblasts were isolated by enzymatic digestion and Percoll® gradient separation. The purity of the primary cells was assessed by flow cytometry using the trophoblast-specific marker cytokeratin-7. After screening different coating matrices, we optimized the growth conditions for the primary cytotrophoblasts on Transwell/ inserts. The morphology of 5 days cultured trophoblasts was determined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Membrane makers were visualized using confocal microscopy. Additionally transport studies were performed on the polarized trophoblasts in the Transwell® system. Results: During 5 days culture, the trophoblasts (>90% purity) developed a modest trans-epithelial electrical resistance (TEER) and a sizedependent apparent permeability coefficient (Papp) to fluorescently labeled compounds (MW ~400-70’000D). SEM analyses confirmed a confluent trophoblast layer with numerous microvilli at day six, and TEM revealed a monolayer with tight junctions. Immunocytochemistry on the confluent trophoblasts showed positivity for the cell-cell adhesion molecule E-cadherin, the tight junction protein ZO-1, and the membrane proteins ABCA1 and Na+/K+-ATPase. Vectorial glucose and cholesterol transport studies confirmed functionality of the cultured trophoblast barrier. Conclusion: Evidence from cell morphology, biophysical parameters and cell marker expressions indicate the successful and reproducible establishment of a primary trophoblast monolayer model suitable for transport studies. Application of this model to pathological trophoblasts will help to better understand the mechanism underlying gestational diseases, and to define the consequences of placental pathology on materno-fetal nutrient transport.

Halocarbon and pigment profiles in the waters of the Amundsen and Ross Seas, Antarctica

Little is known regarding the distribution of volatile halogenated organic compounds (halocarbons) in Antarctic waters, and their relation to biophysical variables. During the austral summer (December to January) in 2007-08 halocarbon and pigment concentrations were measured in the Amundsen (100-130ºW) and Ross Sea (158ºW- 160ºE). In addition, halocarbons were determined in air, snow and sea ice. The distribution of halocarbons was influenced to a large extent by sea ice, and to a much lesser extent by pelagic biota. Concentrations of naturally produced halocarbons were elevated in the surface mixed layer in ice covered areas compared to open waters in polynyas and in the bottom waters of the Ross Sea. Higher concentrations of halocarbons were also found in sea ice brine compared to the surface waters. Incubations of snow revealed an additional source of halocarbons. The distribution of halocarbons also varied considerably between the Amundsen and Ross Seas, mainly due to the different oceanographic settings. For iodinated compounds, weak correlations were found with the presence of pigments indicative of Phaeocystis, mainly in the Ross Sea. Saturation anomalies for the surface water and brine (in sea ice) were determined for the two indicator halocarbons bromoform and chloriodomethane. For bromoform, the surface water anomalies varied between -83 and 11%, whereas chloroiodomethane anomalies varied between -6 and 1,200%. The saturation anomalies for brine varied between -56 to 120% for bromoform and 91 to 22,000% for chloroiodomethane, indicating that sea ice could be a possible source both to the atmosphere and the surface waters. Polar waters can have a substantial impact on global halocarbon budgets and need to be included in large-scale assessments.

Modelización del cálculo de Indicadores Ambientales, a partir de sensores ópticos de alta resolución temporal a bordo de satélite

La presente tesis doctoral tiene por objeto el estudio y análisis de técnicas y modelos de obtención de parámetros biofísicos e indicadores ambientales, de manera automatizada a partir de imágenes procedentes de satélite de alta resolución temporal. En primer lugar se revisan los diferentes programas espaciales de observación del territorio, con especial atención a los que proporcionan dicha resolución. También se han revisado las metodologías y procesos que permiten la obtención de diferentes parámetros cuantitativos y documentos cualitativos, relacionados con diversos aspectos de las cubiertas terrestres, atendiendo a su adaptabilidad a las particularidades de los datos. En segundo lugar se propone un modelo de obtención de parámetros ambientales, que integra información proveniente de sensores espaciales y de otras fuentes auxiliares utilizando, en cierta medida, las metodologías presentadas en apartados anteriores y optimizando algunas de las referidas o proponiendo otras nuevas, de manera que se permita dicha obtención de manera eficiente, a partir de los datos disponibles y de forma sistemática. Tras esta revisión de metodologías y propuesta del modelo, se ha procedido a la realización de experimentos, con la finalidad de comprobar su comportamiento en diferentes casos prácticos, depurar los flujos de datos y procesos, así como establecer las situaciones que pueden afectar a los resultados. De todo ello se deducirá la evaluación del referido modelo. Los sensores considerados en este trabajo han sido MODIS, de alta resolución temporal y Thematic Mapper (TM), de media resolución espacial, por tratarse de instrumentos de referencia en la realización de estudios ambientales. También por la duración de sus correspondientes misiones de registro de datos, lo que permite realizar estudios de evolución temporal de ciertos parámetros biofísicos, durante amplios periodos de tiempo. Así mismo. es de destacar que la continuidad de los correspondientes programas parece estar asegurada. Entre los experimentos realizados, se ha ensayado una metodología para la integración de datos procedentes de ambos sensores. También se ha analizado un método de interpolación temporal que permite obtener imágenes sintéticas con la resolución espacial de TM (30 m) y la temporal de MODIS (1 día), ampliando el rango de aplicación de este último sensor. Asimismo, se han analizado algunos de los factores que afectan a los datos registrados, tal como la geometría de la toma de los mismos y los episodios de precipitación, los cuales alteran los resultados obtenidos. Por otro lado, se ha comprobado la validez del modelo propuesto en el estudio de fenómenos ambientales dinámicos, en concreto la contaminación orgánica de aguas embalsadas. Finalmente, se ha demostrado un buen comportamiento del modelo en todos los casos ensayados, así como su flexibilidad, lo que le permite adaptarse a nuevos orígenes de datos, o nuevas metodologías de cálculo. Abstract This thesis aims to the study and analysis of techniques and models, in order to obtain biophysical parameters and environmental indicators in an automated way, using high temporal resolution satellite data. Firstly we have reviewed the main Earth Observation Programs, paying attention to those that provide high temporal resolution. Also have reviewed the methodologies and process flow diagrams in order to obtain quantitative parameters and qualitative documents, relating to various aspects of land cover, according to their adaptability to the peculiarities of the data. In the next stage, a model which allows obtaining environmental parameters, has been proposed. This structure integrates information from space sensors and ancillary data sources, using the methodologies presented in previous sections that permits the parameters calculation in an efficient and automated way. After this review of methodologies and the proposal of the model, we proceeded to carry out experiments, in order to check the behavior of the structure in real situations. From this, we derive the accuracy of the model. The sensors used in this work have been MODIS, which is a high temporal resolution sensor, and Thematic Mapper (TM), which is a medium spatial resolution instrument. This choice was motivated because they are reference sensors in environmental studies, as well as for the duration of their corresponding missions of data logging, and whose continuity seems assured. Among the experiments, we tested a methodology that allows the integration of data from cited sensors, we discussed a proposal for a temporal interpolation method for obtaining synthetic images with spatial resolution of TM (30 m) and temporal of MODIS (1 day), extending the application range of this one. Furthermore, we have analyzed some of the factors that affect the recorded data, such as the relative position of the satellite with the ground point, and the rainfall events, which alter the obtained results. On the other hand, we have proven the validity of the proposed model in the study of the organic contamination in inland water bodies. Finally, we have demonstrated a good performance of the proposed model in all cases tested, as well as its flexibility and adaptability.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.

Molecular and Functional Characterization of Histone Derived Antimicrobial Peptides from Marine Organisms

Antimicrobial peptides (AMPs) are gene encoded, small sized, generally cationic, amphiphathic peptides characterized by antimicrobial activity against bacteria, fungi, viruses and other pathogens. They are a major component of the innate immune defense system of almost all living organisms, ranging from bacteria to humans and represent the first line of defense against the invading microbial pathogens (Boman, 1995; Zasloff, 2002). Antimicrobial peptides represent a heterogeneous group displaying multiple modes of action that are determined by the sequence and concentration of peptides. Their remarkable specificity for prokaryotes with low toxicity for eukaryotic cells has favored their investigation and exploitation as new antibiotics

Three-dimensional, in-silico breast phantom for multimodality image simulations

We report on the construction of anatomically realistic three-dimensional in-silico breast phantoms with adjustable sizes, shapes and morphologic features. The concept of multiscale spatial resolution is implemented for generating breast tissue images from multiple modalities. Breast epidermal boundary and subcutaneous fat layer is generated by fitting an ellipsoid and 2nd degree polynomials to reconstructive surgical data and ultrasound imaging data. Intraglandular fat is simulated by randomly distributing and orienting adipose ellipsoids within a fibrous region immediately within the dermal layer. Cooper’s ligaments are simulated as fibrous ellipsoidal shells distributed within the subcutaneous fat layer. Individual ductal lobes are simulated following a random binary tree model which is generated based upon probabilistic branching conditions described by ramification matrices, as originally proposed by Bakic et al [3, 4]. The complete ductal structure of the breast is simulated from multiple lobes that extend from the base of the nipple and branch towards the chest wall. As lobe branching progresses, branches are reduced in height and radius and terminal branches are capped with spherical lobular clusters. Biophysical parameters are mapped onto the complete anatomical model and synthetic multimodal images (Mammography, Ultrasound, CT) are generated for phantoms of different adipose percentages (40%, 50%, 60%, and 70%) and are analytically compared with clinical examples. Results demonstrate that the in-silico breast phantom has applications in imaging performance evaluation and, specifically, great utility for solving image registration issues in multimodality imaging.

Energy balance model applied to pasture experimental areas in São Paulo State, Brazil.

The Simple Algorithm for Evapotranspiration Retrieving (SAFER) was used to estimate biophysical parameters and theenergy balance components in two different pasture experimental areas, in the São Paulo state, Brazil. The experimentalpastures consist in six rotational (RGS) and three continuous grazing systems (CGS) paddocks. Landsat-8 images from2013 and 2015 dry and rainy seasons were used, as these presented similar hydrological cycle, with 1,600 mm and 1,613mm of annual precipitation, resulting in 19 cloud-free images. Bands 1 to 7 and thermal bands 10 and 11 were used withweather data from a station located nearthe experimental area. NDVI, biomass, evapotranspiration and latent heat flux(λE) temporal values statistically differ CGS from RGS areas. Grazing systems influences the energy partition and theseresults indicate that RGS benefits biomass production, evapotranspiration and the microclimate, due higher LE values.SAFER is a feasible tool to estimate biophysical parameters and energy balance components in pasture and has potentialto discriminate continuous and rotation grazing systems in a temporal analysis.

Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

Short-term synaptic depression (STD) is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network and increasing during silent states. Here, we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, we studied how trains of synaptic potentials had lesser decay during periods of activity (UP states) than during silent periods (DOWN states), providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.

Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.

Biochemical and biophysical properties of a highly active recombinant arginase from Leishmania (Leishmania) amazonensis and subcellular localization of native enzyme

Arginase (L-arginine amidinohydrolase, E.C. 3.5.3.1) is a metalloenzyme that catalyses the hydrolysis Of L-arginine to L-ornithine and urea. In Leishmania spp., the biological role of the enzyme may be involved in modulating NO production upon macrophage infection. Previously, we cloned and characterized the arginase gene from Leishmania (Leishmania) amazonensis. In the present work, we successfully expressed the recombinant enzyme in E. coli and performed biochemical and biophysical characterization of both the native and recombinant enzymes. We obtained K-M and V-max. values of 23.9(+/- 0.96) mM and 192.3 mu mol/min mg protein (+/- 14.3), respectively, for the native enzyme. For the recombinant counterpart, K-M was 21.5(+/- 0.90) mM and V-max was 144.9(+/- 8.9) mu mol/min mg. Antibody against the recombinant protein confirmed a glycosomal cellular localization of the enzyme in promastigotes. Data from light scattering and small angle X-ray scattering showed that a trimeric state is the active form of the protein. We determined empirically that a manganese wash at room temperature is the best condition to purify active enzyme. The interaction of the recombinant protein with the immobilized nickel also allowed us to confirm the structural disposition of histidine at positions 3 and 324. The determined structural parameters provide substantial data to facilitate the search for selective inhibitors of parasitic sources of arginase, which could subsequently point to a candidate for leishmaniasis therapy. (c) 2008 Elsevier B.V. All rights reserved.

Thermal stability of extracellular hemoglobin of Glossoscolex paulistus: Determination of activation parameters by optical spectroscopic and differential scanning calorimetric studies

Glossoscolex paulistus hemoglobin (HbGp) was studied by dynamic light scattering (DLS), optical absorption spectroscopy (UV-VIS) and differential scanning calorimetry (DSC). At pH 7.0, cyanomet-HbGp is very stable, no oligomeric dissociation is observed, while denaturation occurs at 56 degrees C, 4 degrees C higher as compared to oxy-HbGp. The oligomeric dissociation of HbGp occurs simultaneously with some protein aggregation. Kinetic studies for oxy-HbGp using UV-VIS and DES allowed to obtain activation energy (E(a)) values of 278-262 kJ/mol (DES) and 333 kJ/mol (UV-VIS). Complimentary DSC studies indicate that the denaturation is irreversible, giving endotherms strongly dependent upon the heating scan rates, suggesting a kinetically controlled process. Dependence on protein concentration suggests that the two components in the endotherms are due to oligomeric dissociation effect upon denaturation. Activation energies are in the range 200-560 kJ/mol. The mid-point transition temperatures were in the range 50-65 degrees C. Cyanomet-HbGp shows higher mid-point temperatures as well as activation energies, consistent with its higher stability. DSC data are reported for the first time for an extracellular hemoglobin. (C) 2010 Elsevier B.V. All rights reserved.