938 resultados para Spatio-temporal changes


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Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown.

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Chronic sustained hypoxia (CH) induces structural and functional adaptations in respiratory muscles of animal models, however the underlying molecular mechanisms are unclear. This study explores the putative role of CH-induced redox remodeling in a translational mouse model, with a focus on the sternohyoid—a representative upper airway dilator muscle involved in the control of pharyngeal airway caliber. We hypothesized that exposure to CH induces redox disturbance in mouse sternohyoid muscle in a time-dependent manner affecting metabolic capacity and contractile performance. C57Bl6/J mice were exposed to normoxia or normobaric CH (FiO2 = 0.1) for 1, 3, or 6 weeks. A second cohort of animals was exposed to CH for 6 weeks with and without antioxidant supplementation (tempol or N-acetyl cysteine in the drinking water). Following CH exposure, we performed 2D redox proteomics with mass spectrometry, metabolic enzyme activity assays, and cell-signaling assays. Additionally, we assessed isotonic contractile and endurance properties ex vivo. Temporal changes in protein oxidation and glycolytic enzyme activities were observed. Redox modulation of sternohyoid muscle proteins key to contraction, metabolism and cellular homeostasis was identified. There was no change in redox-sensitive proteasome activity or HIF-1α content, but CH decreased phospho-JNK content independent of antioxidant supplementation. CH was detrimental to sternohyoid force- and power-generating capacity and this was prevented by chronic antioxidant supplementation. We conclude that CH causes upper airway dilator muscle dysfunction due to redox modulation of proteins key to function and homeostasis. Such changes could serve to further disrupt respiratory homeostasis in diseases characterized by CH such as chronic obstructive pulmonary disease. Antioxidants may have potential use as an adjunctive therapy in hypoxic respiratory disease.

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Over the past decades star formation has been a very attractive field because knowledge of star formation leads to a better understanding of the formation of planets and thus of our solar system but also of the evolution of galaxies. Conditions leading to the formation of high-mass stars are still under investigation but an evolutionary scenario has been proposed: As a cold pre-stellar core collapses under gravitational force, the medium warms up until it reaches a temperature of 100 K and enters the hot molecular core (HMC) phase. The forming central proto-star accretes materials, increasing its mass and luminosity and eventually it becomes sufficiently evolved to emit UV photons which irradiate the surrounding environment forming a hyper compact (HC) and then a ultracompact (UC) HII region. At this stage, a very dense and very thin internal photon-dominated region (PDR) forms between the HII region and the molecular core. Information on the chemistry allows to trace the physical processes occurring in these different phases of star formation. Formation and destruction routes of molecules are influenced by the environment as reaction rates depend on the temperature and radiation field. Therefore, chemistry also allows the determination of the evolutionary stage of astrophysical objects through the use of chemical models including the time evolution of the temperature and radiation field. Because HMCs host a very rich chemistry with high abundances of complex organic molecules (COMs), several astrochemical models have been developed to study the gas phase chemistry as well as grain chemistry in these regions. In addition to HMCs models, models of PDRs have also been developed to study in particular photo-chemistry. So far, few studies have investigated internal PDRs and only in the presence of outflows cavities. Thus, these unique regions around HC/UCHII regions remain to be examined thoroughly. My PhD thesis focuses on the spatio-temporal chemical evolution in HC/UC HII regions with internal PDRs as well as in HMCs. The purpose of this study is first to understand the impact and effects of the radiation field, usually very strong in these regions, on the chemistry. Secondly, the goal is to study the emission of various tracers of HC/UCHII regions and compare it with HMCs models, where the UV radiation field does not impact the region as it is immediately attenuated by the medium. Ultimately we want to determine the age of a given region using chemistry in combination with radiative transfer.

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Introducción: El Cáncer es prevenible en algunos casos, si se evita la exposición a sustancias cancerígenas en el medio ambiente. En Colombia, Cundinamarca es uno de los departamentos con mayores incrementos en la tasa de mortalidad y en el municipio de Sibaté, habitantes han manifestado preocupación por el incremento de la enfermedad. En el campo de la salud ambiental mundial, la georreferenciación aplicada al estudio de fenómenos en salud, ha tenido éxito con resultados válidos. El estudio propuso usar herramientas de información geográfica, para generar análisis de tiempo y espacio que hicieran visible el comportamiento del cáncer en Sibaté y sustentaran hipótesis de influencias ambientales sobre concentraciones de casos. Objetivo: Obtener incidencia y prevalencia de casos de cáncer en habitantes de Sibaté y georreferenciar los casos en un periodo de 5 años, con base en indagación de registros. Metodología: Estudio exploratorio descriptivo de corte transversal,sobre todos los diagnósticos de cáncer entre los años 2010 a 2014, encontrados en los archivos de la Secretaria de Salud municipal. Se incluyeron unicamente quienes tuvieron residencia permanente en el municipio y fueron diagnosticados con cáncer entre los años de 2010 a 2104. Sobre cada caso se obtuvo género, edad, estrato socioeconómico, nivel académico, ocupación y estado civil. Para el análisis de tiempo se usó la fecha de diagnóstico y para el análisis de espacio, la dirección de residencia, tipo de cáncer y coordenada geográfica. Se generaron coordenadas geográficas con un equipo GPS Garmin y se crearon mapas con los puntos de la ubicación de las viviendas de los pacientes. Se proceso la información, con Epi Info 7 Resultados: Se encontraron 107 casos de cáncer registrados en la Secretaria de Salud de Sibaté, 66 mujeres, 41 hombres. Sin división de género, el 30.93% de la población presento cáncer del sistema reproductor, el 18,56% digestivo y el 17,53% tegumentario. Se presentaron 2 grandes casos de agrupaciones espaciales en el territorio estudiado, una en el Barrio Pablo Neruda con 12 (21,05%) casos y en el casco Urbano de Sibaté con 38 (66,67%) casos. Conclusión: Se corroboro que el análisis geográfico con variables espacio temporales y de exposición, puede ser la herramienta para generar hipótesis sobre asociaciones de casos de cáncer con factores ambientales.

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Layered ferromanganese crusts collected by dredge from a water depth range of 2770 to 2200 m on Mendeleev Ridge, Arctic Ocean,were analyzed formineralogical and chemical compositions and dated using the excess 230Th technique. Comparison with crusts from other oceans reveals that Fe-Mn deposits of Mendeleev Ridge have the highest Fe/Mn ratios, are depleted inMn, Co, and Ni, and enriched in Si and Al aswell as some minor elements, Li, Th, Sc, As and V. However, the upper layer of the crusts shows Mn, Co, and Ni contents comparable to crusts from the Atlantic and Indian Oceans. Growth rates vary from3.03 to 3.97mm/Myr measured on the uppermost 2mm. Mn and Fe oxyhydroxides (vernadite, ferroxyhyte, birnessite, todorokite and goethite) and nonmetalliferous detrital minerals characterize the Arctic crusts. Temporal changes in crust composition reflect changes in the depositional environment. Crust formation was dominated by three main processes: precipitation of Fe-Mn oxyhydroxides from ambient ocean water, sorption of metals by those Fe and Mn phases, and fluctuating but large inputs of terrigenous debris.

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Crop monitoring and more generally land use change detection are of primary importance in order to analyze spatio-temporal dynamics and its impacts on environment. This aspect is especially true in such a region as the State of Mato Grosso (south of the Brazilian Amazon Basin) which hosts an intensive pioneer front. Deforestation in this region as often been explained by soybean expansion in the last three decades. Remote sensing techniques may now represent an efficient and objective manner to quantify how crops expansion really represents a factor of deforestation through crop mapping studies. Due to the special characteristics of the soybean productions' farms in Mato Grosso (area varying between 1000 hectares and 40000 hectares and individual fields often bigger than 100 hectares), the Moderate Resolution Imaging Spectroradiometer (MODIS) data with a near daily temporal resolution and 250 m spatial resolution can be considered as adequate resources to crop mapping. Especially, multitemporal vegetation indices (VI) studies have been currently used to realize this task [1] [2]. In this study, 16-days compositions of EVI (MODQ13 product) data are used. However, although these data are already processed, multitemporal VI profiles still remain noisy due to cloudiness (which is extremely frequent in a tropical region such as south Amazon Basin), sensor problems, errors in atmospheric corrections or BRDF effect. Thus, many works tried to develop algorithms that could smooth the multitemporal VI profiles in order to improve further classification. The goal of this study is to compare and test different smoothing algorithms in order to select the one which satisfies better to the demand which is classifying crop classes. Those classes correspond to 6 different agricultural managements observed in Mato Grosso through an intensive field work which resulted in mapping more than 1000 individual fields. The agricultural managements above mentioned are based on combination of soy, cotton, corn, millet and sorghum crops sowed in single or double crop systems. Due to the difficulty in separating certain classes because of too similar agricultural calendars, the classification will be reduced to 3 classes : Cotton (single crop), Soy and cotton (double crop), soy (single or double crop with corn, millet or sorghum). The classification will use training data obtained in the 2005-2006 harvest and then be tested on the 2006-2007 harvest. In a first step, four smoothing techniques are presented and criticized. Those techniques are Best Index Slope Extraction (BISE) [3], Mean Value Iteration (MVI) [4], Weighted Least Squares (WLS) [5] and Savitzky-Golay Filter (SG) [6] [7]. These techniques are then implemented and visually compared on a few individual pixels so that it allows doing a first selection between the five studied techniques. The WLS and SG techniques are selected according to criteria proposed by [8]. Those criteria are: ability in eliminating frequent noises, conserving the upper values of the VI profiles and keeping the temporality of the profiles. Those selected algorithms are then programmed and applied to the MODIS/TERRA EVI data (16-days composition periods). Tests of separability are realized based on the Jeffries-Matusita distance in order to see if the algorithms managed in improving the potential of differentiation between the classes. Those tests are realized on the overall profile (comprising 23 MODIS images) as well as on each MODIS sub-period of the profile [1]. This last test is a double interest process because it allows comparing the smoothing techniques and also enables to select a set of images which carries more information on the separability between the classes. Those selected dates can then be used to realize a supervised classification. Here three different classifiers are tested to evaluate if the smoothing techniques as a particular effect on the classification depending on the classifiers used. Those classifiers are Maximum Likelihood classifier, Spectral Angle Mapper (SAM) classifier and CHAID Improved Decision tree. It appears through the separability tests on the overall process that the smoothed profiles don't improve efficiently the potential of discrimination between classes when compared with the original data. However, the same tests realized on the MODIS sub-periods show better results obtained with the smoothed algorithms. The results of the classification confirm this first analyze. The Kappa coefficients are always better with the smoothing techniques and the results obtained with the WLS and SG smoothed profiles are nearly equal. However, the results are different depending on the classifier used. The impact of the smoothing algorithms is much better while using the decision tree model. Indeed, it allows a gain of 0.1 in the Kappa coefficient. While using the Maximum Likelihood end SAM models, the gain remains positive but is much lower (Kappa improved of 0.02 only). Thus, this work's aim is to prove the utility in smoothing the VI profiles in order to improve the final results. However, the choice of the smoothing algorithm has to be made considering the original data used and the classifier models used. In that case the Savitzky-Golay filter gave the better results.

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Background: Glioblastoma multiforme (GBM) is one of the deadliest and most aggressive form of primary brain tumor. Unfortunately, current GBM treatment therapies are not effective in treating GBM patients. They usually experience very poor prognosis with a median survival of approximately 12 months. Only 3-5% survive up to 3 years or more. A large-scale gene profile study revealed that several genes involved in essential cellular processes are altered in GBM, thus, explaining why existing therapies are not effective. The survival of GBM patients depends on understanding the molecular and key signaling events associated with these altered physiological processes in GBM. Phosphoinositides (PI) form just a tiny fraction of the total lipid content in humans, however they are implicated in almost all essential biological processes, such as acting as second messengers in spatio-temporal regulation of cell signaling, cytoskeletal reorganization, cell adhesion, migration, apoptosis, vesicular trafficking, differentiation, cell cycle and post-translational modifications. Interestingly, these essential processes are altered in GBM. More importantly, incoming reports have associated PI metabolism, which is mediated by several PI phosphatases such as SKIP, lipases such as PLCβ1, and other kinases, to regulate GBM associated cellular processes. Even as PLCβ1 and SKIP are involved in regulating aberrant cellular processes in several other cancers, very few studies, of which majority are in-silico-based, have focused on the impact of PLCβ1 and SKIP in GBM. Hence, it is important to employ clinical, in vitro, and in vivo GBM models to define the actual impact of PLCβ1 and SKIP in GBM. AIM: Since studies of PLCβ1 and SKIP in GBM are limited, this study aimed at determining the pathological impact of PI metabolic enzymes, PLCB1 and SKIP, in GBM patient samples, GBM cell line models, and xenograft models for SKIP. Results: For the first time, this study confirmed through qPCR that PLCβ1 gene expression is lower in human GBM patient samples. Moreover, PLCβ1 gene expression inversely correlates with pathological grades of glioma; it decreases as glioma grades increases or worsens. Silencing PLCβ1 in U87MG GBM cells produces a dual impact in GBM by participating in both pro-tumoral and anti-tumoral roles. PLCβ1 knockdown cells were observed to have more migratory abilities, increased cell to extracellular matrix (ECM) adhesion, transition from epithelial phenotype to mesenchymal phenotype through the upregulation of EMT transcription factors Twist1 and Slug, and mesenchymal marker, vimentin. On the other hand, p-Akt and p-mTOR protein expression were downregulated in PLCβ1 knockdown cells. Thus, the oncogenic pathway PI3K/Akt/mTOR pathway is inhibited during PLCβ1 knockdown. Consistently, cell viability in PLCβ1 knockdown cells were significantly decreased compared to controls. As for SKIP, this study demonstrated that about 48% of SKIP colocalizes with nuclear PtdIns(4,5)P2 to nuclear speckles and that SKIP knockdown alters nuclear PtdIns(4,5)P2 in a cell-type dependent manner. In addition, SKIP silencing increased tumor volume and weight in xenografts than controls by reducing apoptosis and increasing viability. All in all, these data confirm that PLCβ1 and SKIP are involved in GBM pathology and a complete understanding of their roles in GBM may be beneficial.

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Entre la fin du Néolithique et l’âge du Bronze, la présence d’habitats groupés de type village est un phénomène diffus, tant en Italie qu’en France méridionale. Néanmoins, la prise en compte de la variabilité des formes de la stratification des sites interroge. En quoi l’enregistrement sédimentaire des sols d’habitat permet-il d’appréhender la question de l’organisation villageoise et de sa variabilité entre la fin du Néolithique et l’âge du Bronze ? Quelle image cet enregistrement sédimentaire donne-t-il de l’organisation sociale et économique du village ? Afin d’aborder ces questions, nous avons choisi de mener une étude géoarchéologique sur des sites de formes différentes, issus de contextes chrono-culturels et environnementaux variés. La démarche, fondée sur l’emploi de la micromorphologie des sols en tant qu’outil analytique, vise à caractériser l’organisation spatio-temporelle des sols d’occupation à l’échelle du site, selon une approche spatiale des processus de formation de la stratification archéologique. L’élaboration d’un modèle, qui repose sur une classification des micro-faciès sédimentaires selon le système d’activité, et son application à des sites-laboratoires permettent de qualifier les techniques de construction en terre, l’usage du sol et les dynamiques d’occupation propres à chaque site, dans le but de déterminer les comportements socio-économiques et les spécificités du mode de vie villageois enregistrées par les sols. Cette approche permet d’évaluer les constantes et les variables qui qualifient les différents types d’occupation. Le sol, conçu comme matérialité de l’espace villageois, devient ainsi un témoignage direct de la variabilité culturelle et des différentes formes d’organisation des communautés de la fin du Néolithique et de l’âge du Bronze.

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There are only a few insights concerning the influence that agronomic and management variability may have on superficial scald (SS) in pears. Abate Fétel pears were picked during three seasons (2018, 2019 and 2020) from thirty commercial orchards in the Emilia Romagna region, Italy. Using a multivariate statistical approach, high heterogeneity between farms for SS development after cold storage with regular atmosphere was demonstrated. Indeed, some factors seem to affect SS in all growing seasons: high yields, soil texture, improper irrigation and Nitrogen management, use of plant growth regulators, late harvest, precipitations, Calcium and cow manure, presence of nets, orchard age, training system and rootstock. Afterwards, we explored the spatio/temporal variability of fruit attributes in two pear orchards. Environmental and physiological spatial variables were recorded by a portable RTK GPS. High spatial variability of the SS index was observed. Through a geostatistical approach, some characteristics, including soil electrical conductivity and fruit size, have been shown to be negatively correlated with SS. Moreover, regression tree analyses were applied suggesting the presence of threshold values of antioxidant capacity, total phenolic content, and acidity against SS. High pulp firmness and IAD values before storage, denoting a more immature fruit, appeared to be correlated with low SS. Finally, a convolution neural networks (CNN) was tested to detect SS and the starch pattern index (SPI) in pears for portable device applications. Preliminary statistics showed that the model for SS had low accuracy but good precision, and the CNN for SPI denoted good performances compared to the Ctifl and Laimburg scales. The major conclusion is that Abate Fétel pears can potentially be stored in different cold rooms, according to their origin and quality features, ensuring the best fruit quality for the final consumers. These results might lead to a substantial improvement in the Italian pear industry.

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Astrocytes are the most numerous glial cell type in the mammalian brain and permeate the entire CNS interacting with neurons, vasculature, and other glial cells. Astrocytes display intracellular calcium signals that encode information about local synaptic function, distributed network activity, and high-level cognitive functions. Several studies have investigated the calcium dynamics of astrocytes in sensory areas and have shown that these cells can encode sensory stimuli. Nevertheless, only recently the neuro-scientific community has focused its attention on the role and functions of astrocytes in associative areas such as the hippocampus. In our first study, we used the information theory formalism to show that astrocytes in the CA1 area of the hippocampus recorded with 2-photon fluorescence microscopy during spatial navigation encode spatial information that is complementary and synergistic to information encoded by nearby "place cell" neurons. In our second study, we investigated various computational aspects of applying the information theory formalism to astrocytic calcium data. For this reason, we generated realistic simulations of calcium signals in astrocytes to determine optimal hyperparameters and procedures of information measures and applied them to real astrocytic calcium imaging data. Calcium signals of astrocytes are characterized by complex spatiotemporal dynamics occurring in subcellular parcels of the astrocytic domain which makes studying these cells in 2-photon calcium imaging recordings difficult. However, current analytical tools which identify the astrocytic subcellular regions are time consuming and extensively rely on user-defined parameters. Here, we present Rapid Astrocytic calcium Spatio-Temporal Analysis (RASTA), a novel machine learning algorithm for spatiotemporal semantic segmentation of 2-photon calcium imaging recordings of astrocytes which operates without human intervention. We found that RASTA provided fast and accurate identification of astrocytic cell somata, processes, and cellular domains, extracting calcium signals from identified regions of interest across individual cells and populations of hundreds of astrocytes recorded in awake mice.

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Investigating stock identity of marine species in a multidisciplinary holistic approach can reveal patterns of complex spatial population structure and signatures of potential local adaptation. The population structure of common sole (Solea solea) in the Mediterranean Sea was delineated using genomic and otolith data, including single nucleotide polymorphisms (SNPs) markers and otolith data. SNPs were correlated with environmental and spatial variables to evaluate the impact of these features on the actual genetic population structure. Integrated holistic approach was applied to combine the tracers with different spatio-temporal scales. SNPs data was also used to illustrate the population structure of European hake (Merluccius merluccius) within the Alboran Sea, extending into the neighboring Mediterranean Sea and Atlantic Ocean. The aim was to identify patterns of neutral and potential adaptive genetic variation by applying seascape genomic framework. Results from both genetic and otolith data suggested significant divergence among putative populations of common sole, confirming a clear separation between Western, Adriatic Sea and Eastern Mediterranean Sea. Evidence of fine-scale population structure in the Western Mediterranean Sea was observed at outlier loci level and in the Adriatic. Our study not only indicates that separation among Mediterranean sole population is led primarily by neutral processes, but it also suggests the presence of local adaptation influenced by environmental and spatial factors. The holistic approach by considering the spatio-temporal scales of variation confirmed that the same pattern of separation between these geographical sites is currently occurring and has occurred for many generations. Results showed the occurrence of population structure in Merluccius merluccius by detecting westward–eastward differentiation among populations and distinct subgroups at a fine geographical scale using outlier SNPs. These results enhance the knowledge of the population structure of commercially relevant species to support the application of spatial stock assessment models, including a redefinition of fishery management units.

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In this thesis we focus on the analysis and interpretation of time dependent deformations recorded through different geodetic methods. Firstly, we apply a variational Bayesian Independent Component Analysis (vbICA) technique to GPS daily displacement solutions, to separate the postseismic deformation that followed the mainshocks of the 2016-2017 Central Italy seismic sequence from the other, hydrological, deformation sources. By interpreting the signal associated with the postseismic relaxation, we model an afterslip distribution on the faults involved by the mainshocks consistent with the co-seismic models available in literature. We find evidences of aseismic slip on the Paganica fault, responsible for the Mw 6.1 2009 L’Aquila earthquake, highlighting the importance of aseismic slip and static stress transfer to properly model the recurrence of earthquakes on nearby fault segments. We infer a possible viscoelastic relaxation of the lower crust as a contributing mechanism to the postseismic displacements. We highlight the importance of a proper separation of the hydrological signals for an accurate assessment of the tectonic processes, especially in cases of mm-scale deformations. Contextually, we provide a physical explanation to the ICs associated with the observed hydrological processes. In the second part of the thesis, we focus on strain data from Gladwin Tensor Strainmeters, working on the instruments deployed in Taiwan. We develop a novel approach, completely data driven, to calibrate these strainmeters. We carry out a joint analysis of geodetic (strainmeters, GPS and GRACE products) and hydrological (rain gauges and piezometers) data sets, to characterize the hydrological signals in Southern Taiwan. Lastly, we apply the calibration approach here proposed to the strainmeters recently installed in Central Italy. We provide, as an example, the detection of a storm that hit the Umbria-Marche regions (Italy), demonstrating the potential of strainmeters in following the dynamics of deformation processes with limited spatio-temporal signature

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Ziel dieser Dissertation ist es, die grundlegenden philosophisch-theoretischen Implikationen von Schellings letzter systematischer Darlegung seiner Naturphilosophie nach dem Berliner Textfragment von 1843/44, der “Darstellung des Naturprocesses”, zu untersuchen. Angesichts der sich zwischen den 1830 und den 1860 Jahren in Berlin abzeichnenden neuen intellektuellen Tendenzen und der Entwicklungen in den Naturwissenschaften legt Schelling hier die Grundlagen für eine allgemeine Ontologie des Wirklichen in kritischer Auseinandersetzung mit Kants transzendentalem Idealismus. Innerhalb des systematischen Horizonts der "apriorischen Vernunftwissenschaft" oder "negativen Philosophie" stellt er im ersten Teil seines Werkes die Prinzipien fest, die die „Idee des Existierenden“ ausmachen, und beschreibt die rationale Operation, die durchgeführt werden muss, um zum Gedanken einer „Welt außer der Idee“ zu gelangen. Die philosophisch-systematischen Annahmen, die mit dem Übergang von der bloßen Idee des Existierenden zum Gedanken der außeridealen Welt verbunden sind, werden im ersten Kapitel dieser Dissertation untersucht. Im zweiten Teil seines Werkes definiert Schelling durch eine detaillierte Analyse von Kants Transzendentalen Ästhetik den Raum als diejenige Form, in der uns die Existenzen als voneinander getrennt vorstellen lassen. Obwohl der Zeitbegriff von Schelling nur am Rande behandelt wird, trägt er zusammen mit dem Raum dazu bei, die erste ontologische Grundstruktur der außeridealen Welt zu definieren. Die Analyse von Schellings Konzeption der raumzeitlichen Grundstruktur der außeridealen Welt stellt das Thema des zweiten Kapitels dieser Dissertation dar. Schließlich bestimmt Schelling im dritten Teil seines Werkes die Finalität als diejenige Kausalitätsform, die es ermöglicht, die außerideale Welt als einen werdenden Kontext zu verstehen, dessen Entwicklungsstufen die siderische Welt, die unorganische Welt und die organische Welt sind. Die Schelling‘sche Definition der Teleologie der Natur als zweite ontologische Grundstruktur der außeridealen Welt ist das Thema des dritten Kapitels dieser Dissertation.

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Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.