42 resultados para AERIAL DISPERSAL
em Digital Commons at Florida International University
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Aerial View of the FLorida International University University Park Campus.
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Aerial View of the FLorida International University University Park Campus.
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In this study three aspects of sexual reproduction in Everglades plants were examined to more clearly understand seed dispersal and the allocation of resources to sexual reproduction—spatial dispersal process, temporal dispersal of seeds (seedbank), and germination patterns in the dominant species, sawgrass (Cladium jamaicense). Community assembly rules for fruit dispersal were deduced by analysis of functional traits associated with this process. Seedbank ecology was investigated by monitoring emergence of germinants from sawgrass soil samples held under varying water depths to determine the fate of dispersed seeds. Fine-scale study of sawgrass fruits yielded information on contributions to variation in sexually produced propagules in this species, which primarily reproduces vegetatively. It was hypothesized that Everglades plants possess a set of functional traits that enhance diaspore dispersal. To test this, 14 traits were evaluated among 51 species by factor analysis. The factorial plot of this analysis generated groups of related traits, with four suites of traits forming dispersal syndromes. Hydrochory traits were categorized by buoyancy and appendages enhancing buoyancy. Anemochory traits were categorized by diaspore size and appendages enhancing air movement. Epizoochory traits were categorized by diaspore size, buoyancy, and appendages allowing for attachment. Endozoochory traits were categorized by diaspore size, buoyancy, and appendages aiding diaspore presentation. These patterns/trends of functional trait organization also represent dispersal community assembly rules. Seeds dispersed by hydrochory were hypothesized to be caught most often in the edge of the north side of sawgrass patches. Patterns of germination and dispersal mode of all hydrochorous macrophytes with propagules in the seedbank were elucidated by germination analysis from 90 soil samples collected from 10 sawgrass patches. Mean site seed density was 486 seeds/m2 from 13 species. Most seeds collected at the north side of patches and significantly in the outer one meter of the patch edge (p = 0.013). Sawgrass seed germination was hypothesized to vary by site, among individual plants, and within different locations of a plant’s infructescence. An analysis of sawgrass fruits with nested ANOVAs found that collection site and interaction of site x individual plant significantly affect germination ability, seed viability, and fruit size (p ≤ 0.050). Fruit location within a plant’s infructescence did not significantly affect germination. As for allocation of resources to sexual reproduction, only 17.9% of sawgrass seeds germinated and only 4.8% of ungerminated seeds with fleshy endosperm were presumed viable, but dormant. Collectively, only 22% of all sawgrass seeds produced were viable.
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Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
Resumo:
This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
Resumo:
This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
Resumo:
This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.