>Magister Scientiae - MSc / The Kars has a well-defined channel along the 62 km stretch from its sources in the Bredasdorp Mountains. After entering the Agulhas plain which has a very low gradient, this river changes into a triangular shaped wetland. This wetland is 7 km in length with no defined channel running through it. The wetland then discharges into another 7 km long channel that joins the Heuningnes River with its mouth at the Indian Ocean. The presence of the wetland causes frequent flooding which affects cultivated lands and a major highway linking towns on the coastal Cape Agulhas area with the rest of the country. Before this study, there was no monitoring of flows along the Kars River including water levels within the wetland. Consequently, the conditions leading to flooding of the wetlands were unknown. This study is aimed at understanding how the combination of local rainfall, Kars River inflow into the wetland, soil characteristics, and the morphology of the wetland influence flooding/inundation. The study monitored river inflows into and outflows from the wetland. A soil survey was conducted within the wetland using the augering method and an infiltrometer to determine soil type and infiltration rates. This was done to assess the hydrological characteristics of the wetland. Using the collected climate data and river flow data, a conceptual model was developed for predicting downstream outflows and possible flood events on a daily timescale. The results indicated that the Kars wetland comprises soil with high silt and clay content, and low infiltration capacity. The wetland causes flood attenuation and diffuse surface flows. Low infiltration rates result in ponding of local rainfall which can contribute to flooding.

Pulmonary artery hypertension (PAH), which is diagnosed by an abnormal increase of blood pressure in the pulmonary artery, can be a severe disease, leading to heart failure. In recent years, medical imaging, such as echocardiography, magnetic resonance imaging (MRI), and computed tomography (CT), has been widely used due to its non-invasive property. Right pulmonary artery (RPA) wall distensibility derived from CT angiography was reported to serve as a reliabile marker for the diagnosis of PAH. This study presented a robust method for automatic segmentation of artery based on CT angiography. The algorithm can be divided into two steps: generation of initial contour and refinement of edge. In the first step, a series of original images at different cardiac phases were thresholded to retrieve appropriate intensity window of vessels, followed by the determination of initial contours by a series of morphological image processing on the binary images with two simple manual initializations. Initial contours without touching can be taken as the final results of segmentation, when others need further refinement of edge. In the second step, the center of vessel was automatically located by an ellipse fitting method and then the ray casting algorithm was applied to search for possible edge. Disconnected segments of edge will be linked to complete the vessel segmentation. Furthermore, cross-sectional areas of arteries at different cardiac phases can be measured and used to obtain distensibility. In this study, artery wall distensibility of patients and healthy subjects was evaluated on four vessels, including aorta, main pulmonary artery, right and left pulmonary artery. In addition, segmentation results of five subjects were compared with those obtained by manual selection to evaluate the reliability of the proposed method.

Using hydraulic modeling and Geographic Information System (GIS) software, the 100-year flood was delineated for the municipality of Avon Park located in Highlands County, Florida. A detailed and rigorous approach was undertaken to first collect and develop an extensive spatial database to store the data collected that is pertinent to the model. This analysis combined ArcGIS version 8.3 and the Interconnected Channel and Pond Routing (ICPR) model version 3.02 to develop hydraulic models that assigned regulatory flood elevation within the watershed. The model results were post processed and brought into GIS to delineate the 100-year flood.The steps outlined in this thesis with respect to the use of GIS as a tool in model pre and post-processing are applicable to many models. Hence, the methodology outlined in this thesis adds to the existing pool of knowledge about the use of GIS in hydraulic modeling. By documenting all the steps related to data acquisition, data processing and manipulation, the model interface and GIS, and the post processing of the model results, this thesis can serve as resources for future studies that utilize both GIS and hydraulic modeling.

This three-stage study led to the development of a delineation model of occupational therapy practice for children with Attention Deficit Hyperactivity Disorder (ADHD). Stage one explored the current practice of occupational therapy in the United Kingdom (UK) by conducting a national survey of 282 paediatric occupational therapists. Results indicated that there were only a small number of occupational therapists (8.5%) working in a designated service for children with ADBD. This result suggested that occupational therapy for children with ADHD is a small field of practice. Stage two involved the consensus development on the role of occupational therapy for children with ADHD. Seventy-two paediatric occupational therapists participated in the study. The therapists' top six priorities of assessment and five priorities of intervention were identified. An occupational therapy delineation model of practice was developed by integrating data generated from this research, information from the literature review, and the author's clinical experience. In order to apply the model to clinical practice, a family-centred occupational therapy care package was developed. The third stage evaluated the process and outcome of the devised care package by conducting a multi-centred efficacy study. Twenty occupational therapists from the four countries in the UK attended a 3-day course to learn to implement the care package. Following their training, they submitted data on a sample of 20 children with ADHD. The majority of these children (85%) showed improvement in their behavioural patterns after the implementation of the care package. Over half of the cases (65%) had statistically significant changes of scores in the ADHD Rating Scales. Parents also reported experiencing good family-centred care delivered by the research therapists. The whole study makes a significant contribution to occupational therapy knowledge by creating a new delineation model of practice for which the research undertaken offers some validation.

Doctor of Philosophy / Department of Hospitality Management and Dietetics / Kevin L. Sauer / Carol W. Shanklin / Management responsibilities in the dietetics profession are typically aligned with foodservice operations. Clinical Nutrition Managers (CNMs) are registered dietitians with administrative responsibilities for clinical nutrition services within a healthcare facility. However, no studies have clearly delineated the current responsibilities of CNMs or their level of educational preparedness for this important role. Conceptually, a gap exists between the necessary skills and knowledge required for CNMs. Focus groups, cognitive interviews, and pilot testing were used to develop an audit instrument to measure CNM practice. This audit included 84 tasks in eight job categories. The instrument was distributed online to a national sample of CNMs to assess their involvement, education preparedness, and gaps in education needed for the role. The relationships between responsibilities, educational preparedness, and self-efficacy to perform the job were investigated. Of the 84 tasks, 73 were deemed core activities [80% of CNMs (n=214) were involved in some capacity]. Significant differences were found in frequency of involvement based on size of facility (number of patient beds) and employer type. Generally, CNMs perceived importance of receiving education higher for a majority of the tasks (80 of 84). Mean scores for the level of educational needs met varied more between tasks. Clinical nutrition managers rated educational needs being met lowest for tasks within the managing financial resources category. Gap analyses revealed that the highest educational priorities were for ensuring compliance with regulations and managing human and financial resources. Categorical self-efficacy was predicted by both the educational gap and educational preparedness for some categories. Significant predictors for overall self-efficacy were the self-efficacy of the general (β = 0.203, p=0.007) and managing financial resources (β = 0.178, p=0.014) categories. Significant differences were found in overall self-efficacy based on education level [F(3, 209) = 3.881, p=0.010] and length of employment as a CNM [F(4, 208) = 7.517, p<0.001]. This research can serve as a current benchmark for CNM practice. Results allow educators, managers, and the professional association to better inform students and practitioners about the leadership role. These findings may also assist others in creating leadership development programs, certificates, or graduate degree options specific for CNMs.

Positron emission tomography (PET) is a molecular imaging technique that provides a direct and accurate evaluation of tissue function in vivo. PET of the glucose analogue 18F-fluoro-deoxy-glucose, is increasingly in use to aid in gross target volume delineation in radiotherapy treatment planning (RTP) where it shows reduced inter-observer variability. The aim of this thesis was to develop and investigate a new technique for delineating PET-GTV with sufficient accuracy for RTP. A new technique, volume and contrast adjusted thresholding (VCAT), has been developed to automatically determine the optimum threshold value that measures the true volume on PET images. The accuracy was investigated in spherical and irregular lesions in phantoms using both iterative and filtered back-projection reconstructions and different image noise levels. The accuracy of delineation for the irregular lesions was assessed by comparison with CT using the Dice Similarity Coefficient and Euclidean Distance Transformation. A preliminarily investigation of implementing the newly developed technique in patients was carried out. VCAT proved to determine volumes and delineate tumour boundaries on PET/CT well within the acceptable errors for radiotherapy treatment planning irrespective of lesion contrast, image noise level and reconstruction technique.

The Department of Defense (DoD) maintains approximately 25 million acres of land that is used for military training in the continental United States. Currently, federal and state laws and regulations require that the DoD land be managed so that any activity, including training, will have a minimal effect on the natural environment.

Agriculture plays a crucial role in ensuring global food security, but its intensification has resulted in groundwater depletion, particularly in arid regions like Saudi Arabia. Although the significance of agriculture in Saudi Arabia is well-recognized, there is limited understanding of the agroinformatics aspects required to manage them at a regional or national level. High-resolution satellite data has the potential to provide valuable insights, including the number, location, size, and crop type of agriculture fields, as well as patterns of behavior. Machine learning techniques have emerged as the state-of-the-art methods to extract agricultural informatics from satellite data due to their efficiency and accuracy. However, in regions like Saudi Arabia where even basic agroinformatics data is not routinely available, the lack of ground truth data required to drive machine learning approaches is a critical consideration in model selection. One potential solution is to create a dataset by collecting field data or interpreting satellite imagery using human interpreters, but this can be time-consuming and labor-intensive. Another option is to explore unsupervised techniques that require limited or no ground truth data, but this can result in accuracy sacrifices. Ultimately, we aim to strike a balance between usability, data availability, accuracy, and computational efficiency when developing solutions to address these issues. In this study, a hybrid machine learning framework was developed to accurately delineate agricultural fields in a regional scale of Saudi Arabia, with high accuracy and stable transferability when applied to different temporal and spatial regions across the country. The framework was used to conduct the first retrospective analysis of agriculture activity over three decades on a national scale, including changes in the number, acreage, field size distribution, and the dynamics of expansion and contraction of center-pivot fields. Additionally, a novel unsupervised framework was developed to identify within-field dynamics and map critical crop phenology stages and crop types, providing valuable information for in-field agricultural practices. The agroinformatics retrieved in this study can provide valuable insights for policymakers, farmers, and other stakeholders involved in agriculture and environmental management and exhibited significant implications for the management and sustainability of agricultural systems in Saudi Arabia and other regions facing similar challenges.

No description available.

Modern methods of processing genomic data yield good results, however they are often redeemed by time consummation. This is mainly the reason why this thesis deals with numerical methods of bacterial genome processing which could be a suitable alternative for current methods, both in terms of quality and computational demands. This thesis presents the current methods used for processing of genomes in silico and proposes suitable numerical presentations for the whole genome analysis. Some of these methods are programmed and used for processing further in this diploma thesis. In it, various mathematical and statistical methods are being tested, ones that could lead to successful species delineation of bacteria by numerical presentations of their genomes.