UNT Theses and Dissertations - 5 Matching Results

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Photoinduced Toxicity in Early Lifestage Fiddler Crab (Uca longisignalis) Following Exposure to Deepwater Horizon Spill Oil

Description: The 2010 Deepwater Horizon (DWH) oil spill resulted in a large release of polycyclic aromatic hydrocarbons (PAH) into the Gulf of Mexico. PAH can interact with ultraviolet radiation (UV) resulting in increased toxicity, particularly to early lifestage organisms. The goal of this research was to determine the sensitivity of fiddler crab larvae (Uca longisignalis) to photo-induced toxicity following exposure to Deepwater Horizon spill oil in support of the DWH Natural Resource Damage Assessment. Five replicate dishes each containing 20 larvae, were exposed to one of three UV treatments (10%, 50%, and 100% ambient natural sunlight) and one of five dilutions of water accommodated fractions of two naturally weathered source oils. A dose dependent effect of PAH and UV on larval mortality was observed. Mortality was markedly higher in PAH treatments that included co-exposure to more intense UV light. PAH treatments under low intensity sunlight had relatively high survival. These data demonstrate the importance of considering combined effects of non-chemical (i.e. UV exposure) and chemical stressors and the potential for photo-induced effects after exposure to PAH following the Deepwater Horizon spill.
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Date: December 2015
Creator: Taylor, Leigh M.
Partner: UNT Libraries

Seeds of Disempowerment: Bt cotton and Accumulation by Dispossession in the States of Maharashtra, Telangana, and Andhra Pradesh in India

Description: In 1991, India adopted neoliberalism, a system of political economic practices that promotes private property and free trade, as its political and economic system to promote development in their country. India's neoliberal reform has created issues surrounding human development, resource accumulation, and power struggles. Eleven years later, in 2002, Bt cotton was introduced to the Indian agricultural sector. This research examines how the genetically modified organism Bt cotton is being used to commodify nature in the context of agriculture under neoliberalism. The research focuses on the dispossession of the rural farmers through the commodification of agriculture using Bt cotton. Dispossession of the rural farmers happen through the implications that arise from the commodification of nature. Through Marxist theory of primitive accumulation, this research analyzes accumulation by dispossession and how it neglects the working class and its struggle in rural India. Through this examination, the research will argue alternatives to the dispossession of the working class and the commodification of nature through Bt cotton. Dispossession, in this research, is examined both through working class, but also through the dispossession of biodiversity. Through the loss of biodiversity, the rural farmers are becoming dispossessed from a more sustainable environment. Along with these goals, the research will also incorporate themes of food security through changing landscape of agriculture due to the incorporation of Bt cotton. This research argues the contradictions that are presented through the commodification of agriculture under neoliberalism and provide a contribution to social justice literature, and our understanding of the relationship between technology and the commodification of nature.
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Date: May 2018
Creator: Hoyt, Andrew
Partner: UNT Libraries

Automated Tree Crown Discrimination Using Three-Dimensional Shape Signatures Derived from LiDAR Point Clouds

Description: Discrimination of different tree crowns based on their 3D shapes is essential for a wide range of forestry applications, and, due to its complexity, is a significant challenge. This study presents a modified 3D shape descriptor for the perception of different tree crown shapes in discrete-return LiDAR point clouds. The proposed methodology comprises of five main components, including definition of a local coordinate system, learning salient points, generation of simulated LiDAR point clouds with geometrical shapes, shape signature generation (from simulated LiDAR points as reference shape signature and actual LiDAR point clouds as evaluated shape signature), and finally, similarity assessment of shape signatures in order to extract the shape of a real tree. The first component represents a proposed strategy to define a local coordinate system relating to each tree to normalize 3D point clouds. In the second component, a learning approach is used to categorize all 3D point clouds into two ranks to identify interesting or salient points on each tree. The third component discusses generation of simulated LiDAR point clouds for two geometrical shapes, including a hemisphere and a half-ellipsoid. Then, the operator extracts 3D LiDAR point clouds of actual trees, either deciduous or evergreen. In the fourth component, a longitude-latitude transformation is applied to simulated and actual LiDAR point clouds to generate 3D shape signatures of tree crowns. A critical step is transformation of LiDAR points from their exact positions to their longitude and latitude positions using the longitude-latitude transformation, which is different from the geographic longitude and latitude coordinates, and labeled by their pre-assigned ranks. Then, natural neighbor interpolation converts the point maps to raster datasets. The generated shape signatures from simulated and actual LiDAR points are called reference and evaluated shape signatures, respectively. Lastly, the fifth component determines the similarity between evaluated and reference shape ...
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Date: May 2018
Creator: Sadeghinaeenifard, Fariba
Partner: UNT Libraries

Developing a Soil Moisture-Based Irrigation Scheduling Tool (SMIST) Using Web-GIS Technology

Description: Software as a service (SaaS) is a primary working pattern and a significant application model for next generation Internet application. Web GIS services are the new generation of the Software as a service that can provide the hosted spatial data and GIS functionalities to the practical customized applications. This study focused on developing a webGIS based application, Soil Moisture-Based Irrigation Scheduling Tool (SMIST), for predicting soil moisture in the next seven days using the soil moisture diagnostic equation (SMDE) and the upcoming seven precipitation forecasts made by the National Weather Service (NWS), and ultimately producing an accurate irrigation schedule based on the predicted soil moisture. The SMIST is expected to be capable of improving the irrigation efficiency to protect groundwater resources in the Texas High Plains and reducing the cost of energy for pumping groundwater for irrigation, as an essential public concern in this area. The SMIST comprised an integration of web-based programs, a Hydrometeorological model, GIS, and geodatabase. It integrates two main web systems, the soil moisture estimating web application for irrigation scheduling based on the soil moisture diagnostic equation (SMDE), and an agricultural field delineation webGIS application to prepare input data and the model parameters. The SMIST takes advantage of the latest historical and forecasted precipitation data to predict soil moisture in the user-specified agricultural field(s). In this regard, the next seven days soil moisture versus the soil moisture threshold for normal growth would be presented in the result page of the SMIST to help users to adjust irrigation rate and sequence.
Date: May 2018
Creator: Nikfal, Mohammadreza
Partner: UNT Libraries

Improvement of the Soil Moisture Diagnostic Equation for Estimating Root-Zone Soil Moisture

Description: Soil moisture information can be used accurately in determining the timing and amount of irrigation applied to plants. Pan and Pan et al. proposed a robust and simple daily diagnostic equation for estimating daily soil moisture. The diagnostic equation evaluates the relationship between the soil moisture loss function and the summation weighted average of precipitation. The loss function uses the sinusoidal wave function which employs day of the year (DOY) to evaluate the seasonal variation in soil moisture loss for a given year. This was incorporated into the daily diagnostic equation to estimate the daily soil moisture for a location. Solar radiation is an energy source that drives the energy and water exchanges between vegetation and the atmosphere (i.e., evapotranspiration), and thus impacts the soil moisture dry-down. In this paper, two parameters (the actual solar radiation and the clear sky solar radiation) are introduced into loss function coefficient to improve the estimation of soil moisture. After the Introduction of the solar radiation data into soil moisture loss function, a slight improvement was observed in the estimated daily soil moisture. Pan observed that generally the correlation coefficient between the estimated and the observed soil moisture is above 0.75 and the root mean square error is below 5.0 (%v/v). The introduction solar radiation data (i.e. clear sky solar radiation and actual solar) improve the correlation coefficient average for all the sites evaluated by 0.03 when the root mean square error is generally below 4.5(%v/v) for the entire root zone.
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Date: May 2018
Creator: Omotere, Olumide Olubunmi
Partner: UNT Libraries