Browsing Theses and Dissertations (MU) by Title

Now showing items 3645-3664 of 11332

    Title
    Evaluation of incisional gastropexy modified by addition of two full-thickness stomach to body wall sutures for prevention of gastric dilatation-volvulus [1]
    Evaluation of innovative materials subjected to near-contact detonations [1]
    Evaluation of J-turn design performance in Missouri [1]
    Evaluation of long-term CIDR-based estrus synchronization protocols in primiparous two-year-old beef cows [1]
    Evaluation of machine learning algorithms for prediction of 5-year survivability for seven types of cancers [1]
    Evaluation of micro-dystrophin based and dystrophin-independent AAV gene therapies for Duchenne Muscular Dystrophy [1]
    An evaluation of Missouri Master Naturalist Program: changes in volunteer knowledge and the relationship between motivations and changes in volunteer knowledge [1]
    Evaluation of mobility impacts of temporary ramp metering in work zones [1]
    Evaluation of modified montmorillonites in poultry diets [1]
    Evaluation of modulus of polycaprolactone fused deposition modeling 3D printed tissue scaffolds [1]
    Evaluation of Monte Carlo method in PageRank [1]
    Evaluation of novel diagnostic and therapeutic modalities for treatment of canine pulmonary hypertension [1]
    Evaluation of novel hovering strategies to improve gravity-tractor deflection merits [1]
    Evaluation of patch-burn grazing on species richness and density of grassland birds [1]
    Evaluation of performance funding systems : results from the event study design [1]
    Evaluation of post punching capacity of flat plates under progressive collapse [1]
    An evaluation of pre- and post-timber harvest water quality in low-order streams in the Missouri Ozarks [1]
    Evaluation of pre-formulated micronutrients products and their interactions with glyphosate on corn growth and yield [1]
    Evaluation of prestress losses in an innovative prestressed precast pavement system [1]
    Evaluation of process-structure-property relationships of carbon nanotube forests using simulation and deep learning [1]