How Much Is Enough? an Analysis of the 5' Nontranslated Region of the Deformed Wing Virus in Honeybees

Honeybees are an essential component of today¿s agricultural system because of their role as pollinators. However, viruses, including a member of the Picornavirales order known commonly as Deformed Wing Virus (DWV), are compromising the health of honeybee colonies. Many picornaviruses, such as poliovirus, have been studied in depth because of their relation to human disease, but also because of their use of an Internal Ribosome Entry Site (IRES) to initiate translation. The primary goal of this thesis was to determine if the 5¿ Non-Translated Region (NTR) of Deformed Wing Virus (DWV) functions as an IRES. A secondary goal was to determine if there are specific parts of that 5¿ NTR that are important to IRES function. Six plasmids were constructed by inserting three different sections of the 5¿ NTR of DWV, in both sense and antisense directions, between two reporter genes. These plasmids, along with several control plasmids, were transfected into Sf9 cells, and post-transfection luciferase assays were conducted. Results were inconclusive. This could have been due to an inability of the plasmids to be expressed in Sf9 cells, an error in the construction of the plasmids, or a mechanical error in the assay procedure. At this time it appears most likely that the 5¿ NTR of DWV may be cell-type or species specific, and the next step would be to transfect the plasmids into a recently developed cultured honeybee cell line.

Static and Dynamic Error Correction of a Computer-Aided Mechanical Navigation Linkage for Arthroscopic Hip Surgery

While beneficially decreasing the necessary incision size, arthroscopic hip surgery increases the surgical complexity due to loss of joint visibility. To ease such difficulty, a computer-aided mechanical navigation system was developed to present the location of the surgical tool relative to the patient¿s hip joint. A preliminary study reduced the position error of the tracking linkage with limited static testing trials. In this study, a correction method, including a rotational correction factor and a length correction function, was developed through more in-depth static testing. The developed correction method was then applied to additional static and dynamic testing trials to evaluate its effectiveness. For static testing, the position error decreased from an average of 0.384 inches to 0.153 inches, with an error reduction of 60.5%. Three parameters utilized to quantify error reduction of dynamic testing did not show consistent results. The vertex coordinates achieved 29.4% of error reduction, yet with large variation in the upper vertex. The triangular area error was reduced by 5.37%, however inconsistent among all five dynamic trials. Error of vertex angles increased, indicating a shape torsion using the developed correction method. While the established correction method effectively and consistently reduced position error in static testing, it did not present consistent results in dynamic trials. More dynamic paramters should be explored to quantify error reduction of dynamic testing, and more in-depth dynamic testing methodology should be conducted to further improve the accuracy of the computer-aided nagivation system.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.