PathBeat. Number 13 (Winter 2012) University of Iowa Department of Pathology.

University of Iowa Department of Pathology newsletter.

PathBeat. Number 14 (Winter 2013) University of Iowa Department of Pathology.

University of Iowa Department of Pathology newsletter.

PathBeat. Number 13 (Winter 2012) University of Iowa Department of Pathology.

University of Iowa Department of Pathology newsletter.

Audit report of the Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Dormitory Revenue Refunding Bonds for the year ended June 30, 2012

Audit report of the Schedule of Debt Service and Coverage for Iowa State University of Science and Technology for the Dormitory Revenue Refunding Bonds for the year ended June 30, 2012

Audit report of Iowa State University of Science and Technology, Ames, Iowa, and its discretely presented component unit as of and for the years ended June 30, 2013 and 2012

Audit report of Iowa State University of Science and Technology, Ames, Iowa, and its discretely presented component unit as of and for the years ended June 30, 2013 and 2012

Audit report of the State University of Iowa, Iowa City, Iowa, (University of Iowa) and its discretely presented component units as of and for the years ended June 30, 2013 and 2012

Audit report of the State University of Iowa, Iowa City, Iowa, (University of Iowa) and its discretely presented component units as of and for the years ended June 30, 2013 and 2012

IMRT credentialing for prospective trials using institutional virtual phantoms: results of a joint European Organization for the Research and Treatment of Cancer and Radiological Physics Center project.

BACKGROUND AND PURPOSE: Intensity-modulated radiotherapy (IMRT) credentialing for a EORTC study was performed using an anthropomorphic head phantom from the Radiological Physics Center (RPC; RPCPH). Institutions were retrospectively requested to irradiate their institutional phantom (INSTPH) using the same treatment plan in the framework of a Virtual Phantom Project (VPP) for IMRT credentialing. MATERIALS AND METHODS: CT data set of the institutional phantom and measured 2D dose matrices were requested from centers and sent to a dedicated secure EORTC uploader. Data from the RPCPH and INSTPH were thereafter centrally analyzed and inter-compared by the QA team using commercially available software (RIT; ver.5.2; Colorado Springs, USA). RESULTS: Eighteen institutions participated to the VPP. The measurements of 6 (33%) institutions could not be analyzed centrally. All other centers passed both the VPP and the RPC ±7%/4 mm credentialing criteria. At the 5%/5 mm gamma criteria (90% of pixels passing), 11(92%) as compared to 12 (100%) centers pass the credentialing process with RPCPH and INSTPH (p = 0.29), respectively. The corresponding pass rate for the 3%/3 mm gamma criteria (90% of pixels passing) was 2 (17%) and 9 (75%; p = 0.01), respectively. CONCLUSIONS: IMRT dosimetry gamma evaluations in a single plane for a H&N prospective trial using the INSTPH measurements showed agreement at the gamma index criteria of ±5%/5 mm (90% of pixels passing) for a small number of VPP measurements. Using more stringent, criteria, the RPCPH and INSTPH comparison showed disagreement. More data is warranted and urgently required within the framework of prospective studies.

Report on a review of the operations of certain departments of the University of Iowa Hospitals and Clinics for the period July 1, 2010 through December 31, 2012

Report on a review of the operations of certain departments of the University of Iowa Hospitals and Clinics for the period July 1, 2010 through December 31, 2012

Report on a special investigation of the University of Iowa Hospitals and Clinics, Health Care Information Systems Department, for the period January 1, 2005 through July 5, 2013

Report on a special investigation of the University of Iowa Hospitals and Clinics, Health Care Information Systems Department, for the period January 1, 2005 through July 5, 2013

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.