Assessing Health Needs of the Burlington Probation and Parole Population

The Burlington Probation and Parole population confronts numerous social, economic, and healthcare challenges upon their return to the community. While health and healthcare issues of inmates have been studied extensively, the health status and medical issues of the reentry offenders, particularly in rural areas have not been previously assessed. Data about health risks, major medical issues, and lifestyle choices among offenders on parole in the rural setting may prove helpful in the identification of preventative measures and development of strategies to promote positive health behaviors among the target population. The aim of this study is to evaluate the health risks among offenders on parole in the Burlington area and guide recommendations towards improving their health outcomes through community and educational initiatives. We also sought to gain a better understanding of the barriers within the rural setting that prevent positive health behaviors among the parolees upon their reintegration into the communityhttps://scholarworks.uvm.edu/comphp_gallery/1068/thumbnail.jp

Bacteria Source Tracking Shapes a Holistic Watershed Management Plan

In 2005, several tidal water bodies near Savannah, Ga., were found to violate state fecal coliform and dissolved oxygen regulations. When the city and nearby stakeholders drew up a holistic watershed management plan, bacterial source tracking and fluorometry enabled them to target pollution reduction efforts

Bacteria Source Tracking Shapes a Holistic Watershed Management Plan

In 2005, several tidal water bodies near Savannah, Ga., were found to violate state fecal coliform and dissolved oxygen regulations. When the city and nearby stakeholders drew up a holistic watershed management plan, bacterial source tracking and fluorometry enabled them to target pollution reduction efforts

Virtualizing Ancient Rome: 3D acquisition and modeling of a large plaster-of-Paris model of Imperial Rome

Computer modeling through digital range images has been used for many applications, including 3D modeling of objects belonging to our cultural heritage. The scales involved range from small objects (e.g. pottery), to middle-sized works of art (statues, architectural decorations), up to very large structures (architectural and archaeological monuments). For any of these applications, suitable sensors and methodologies have been explored by different authors. The object to be modeled within this project is the “Plastico di Roma antica,” a large plaster-of-Paris model of imperial Rome (16x17 meters) created in the last century. Its overall size therefore demands an acquisition approach typical of large structures, but it also is characterized extremely tiny details typical of small objects (houses are a few centimeters high; their doors, windows, etc. are smaller than 1 centimeter). This paper gives an account of the procedures followed for solving this “contradiction” and describes how a huge 3D model was acquired and generated by using a special metrology Laser Radar. The procedures for reorienting in a single reference system the huge point clouds obtained after each acquisition phase, thanks to the measurement of fixed redundant references, are described. The data set was split in smaller sub-areas 2 x 2 meters each for purposes of mesh editing. This subdivision was necessary owing to the huge number of points in each individual scan (50-60 millions). The final merge of the edited parts made it possible to create a single mesh. All these processes were made with software specifically designed for this project since no commercial package could be found that was suitable for managing such a large number of points. Preliminary models are presented. Finally, the significance of the project is discussed in terms of the overall project known as “Rome Reborn,” of which the present acquisition is an important component

Dose-dependent white matter damage after brain radiotherapy

BACKGROUND AND PURPOSE: Brain radiotherapy is limited in part by damage to white matter, contributing to neurocognitive decline. We utilized diffusion tensor imaging (DTI) with multiple b-values (diffusion weightings) to model the dose-dependency and time course of radiation effects on white matter. MATERIALS AND METHODS: Fifteen patients with high-grade gliomas treated with radiotherapy and chemotherapy underwent MRI with DTI prior to radiotherapy, and after months 1, 4-6, and 9-11. Diffusion tensors were calculated using three weightings (high, standard, and low b-values) and maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ(‖)), and radial diffusivity (λ(⊥)) were generated. The region of interest was all white matter. RESULTS: MD, λ(‖), and λ(⊥)increased significantly with time and dose, with corresponding decrease in FA. Greater changes were seen at lower b-values, except for FA. Time-dose interactions were highly significant at 4-6 months and beyond (p < .001), and the difference in dose response between high and low b-values reached statistical significance at 9-11 months for MD, λ(‖), and λ(⊥) (p < .001, p < .001, p = .005 respectively) as well as at 4-6 months for λ(‖) (p = .04). CONCLUSIONS: We detected dose-dependent changes across all doses, even <10 Gy. Greater changes were observed at low b-values, suggesting prominent extracellular changes possibly due to vascular permeability and neuroinflammation