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(Ohio State University)

Ohio State University is a public research university located in Columbus, Ohio. It was founded in 1870 as a land-grant university and is currently the second largest university campus in the United States. Ohio State is currently ranked by U.S. News & World Report as the best public university in Ohio, among the top 150 universities in the world, among the top 60 universities in the United States, and among the top 20 public universities in the United States. Ohio State has been officially designated as the flagship institution of Ohio's public universities by the newly centralized University System of Ohio. It also includes regional campuses in Lima, Mansfield, Marion, Newark, and Wooster.

More information: http://en.wikipedia.org/wiki/Ohio_State_University

Carbon Sequestration: Super Critical CO2’s effect on subsurface brines in the Illinois Basin Daniel Blake, Kyle Shalek, Dr. Frank Schwartz, Stephanie Konfal, Dr. Jeff Daniels The Ohio State University, School of Earth Sciences, 125 S. Oval Mall, Columbus OH 43210 Abstract What is Super Critical CO2? Mt.Simon and St. Peter Sandstone Xu Et Al Normalized Sandstone ArcGIS Data Water Chemistry of St. Peter Sandstone Conclusions Acknowledgments References Analysis of : TGS Water Chemistry Data Set. Tough React Data Set (Xu). AEP Carbon Sequestration Data Set. Scientific Papers from GSW. SES/SEI Carbon Sequestration Workshop Mt. Simon Sandstone St. Peter Sandstone Tough React (Xu) Porosity 8%-18% 10%-40% 10%-30% Type Feldspathic Qtz Sand Qtz Arenite Normalized Qtz Lithic Arkose Thickness 50ft. – 2000* ft. 0 ft.-100 ft. 10m* Physiochemical properties: High density Solubility's approaching the liquid phase Diffusivity approaching the gas phase Minimum constraints: 74 bars 303 K 2,500ft Geothermal Data: 303 K/km 105 bar/km Major Constituents: Quartz, Kaolinite, Calcite, Illite, Oligioclase, K-Feldspar, Hematite, Chlorite, Na-Smectite General Data: Normalized Sandstone contains 56% Quartz, 28% Feldspar and 16% Lithic fragments Testing revealed up to 30% of the medium formed secondary minerals Porosity lowering carbonates Permeability lowering clay minerals Concentration vs. Depth Relationship: Even distributio...

Introduction Discussion A Retrospective Survey of Temporary Anchorage Device Utilization in a University Practice Tyrun J. Ray, F. Michael Beck, Sarandeep S. Huja The Ohio State University, College of Dentistry, Columbus, OH The goal of this study is to examine factors that affect the success of Temporary Anchorage Devices in orthodontic treatment. Few studies have been conducted concerning the affects of patient and clinician variables on the stability of TADs and, therefore, the ability of TADs to produce the intended treatment outcome. This study examines factors that relate to success and failure of TADs in a university-based graduate and faculty clinic. Results Materials & Methods References: 1. Wang YC and Liou EJW. Comparison of the loading behavior of self-drilling and predrilled mini-screws throughout orthodontic loading. Am J Orthod Dentofacial Orthop 2008; 133:38-43. Acknowledgements: SSH acknowledges Dr. Tatakis for his assistance and support. The clinical success rates, as reported in literature, range from approximately 85-93%1. Soft tissue overgrowth was significantly related (P < 0.001) to TAD failure. While not statistically significant, factors such as jaw location and TAD use for intrusion/extrusion can also be considered as factors relating to failure. The results of this study should be interpreted relative to the small sample size, retrospective and nonrandomized design. With only 32 of 128 T...

Genetic determinants of subgingival bacterial colonization Papapostolou*, D. N. Tatakis and P. S. Kumar The Ohio State University College of Dentistry, Columbus, Ohio The purpose of this study was to compare the subgingival microbial profiles of periodontally healthy twins using a molecular method for bacterial profiling. Results The gingival sulcus is complex bacterial ecosystem. Majority of subgingival bacteria are uncultivated. Role of host genetics in bacterial colonization is poorly understood. Twin studies are a powerful model to study the role of host genetics. Open-ended molecular methods allow comparisons of complex microbial systems. Introduction Purpose Methods Conclusions Laboratory methods: Collect subgingival plaque samples with paper points DNA Isolation PCR Restriction Digest of PCR product T-RFLP analysis Abstract Introduction: The gingival sulcus consists of a complex bacterial ecosystem, the majority of which is uncultivated. Although the sequence of oral bacterial colonization has been investigated, factors affecting this process, especially host genetics, are poorly understood. Twin studies provide a powerful model to study the contribution of genetics to host traits. Open-ended molecular methods are accurate and comprehensive approaches to compare complex microbial communities. The purpose of this study was to compare the subgingival microbial profiles of periodontally healthy twins using a...

EXPERIMENT SETUP Observations from 11 upper-air stations around Antarctica, shown in Fig. 1, are compared with output from 60-km resolution Polar WRF output from 12-27 February 2007. Forecasts are initialized twice daily at 00 and 12 UTC. Simulations are run by the Polar Meteorology Group using WRF version 2.2. The model has 28 (sigma) levels in the vertical, unevenly spaced with more levels in the lower troposphere to allow for better representation of complex interactions in the planetary boundary layer. The Kain-Fritsch cumulus scheme, Mellor-Yamada-Janjic PBL scheme, Thompson et al. microphysics scheme, Dudhia shortwave scheme, Rapid Radiative Transfer Model (RRTM) longwave scheme, and Noah LSM are used. Polar modifications include use of latent heat of sublimation over ice surfaces, assuming ice saturation over ice surfaces, adjustment of the radiation scheme, modified ice and snow thermal properties, as well as a better representation of heat transfer through ice sheets through the addition of levels in the soil model. REFERENCES AND ACKNOWLEDGEMENTS Bromwich, D. H., J. J. Cassano, T. Klein, G. Heinemann, K. M. Hines, K. Steffen, and J. E. Box, 2001: Mesoscale modeling of katabatic winds over Greenland with the Polar MM5. Mon. Wea. Rev., 129, 2290-2309. ——, A. J. Monaghan, K. W. Manning, and J. G. Powers, 2005: Real-time forecasting for the Antarctic: An evaluation of the Antarctic Mesoscale Prediction System (AMPS). Mon. Wea. Rev., 133, 579-603. Gre...

Evaluation of Williams Field Terminal Aerodrome Forecasts (TAFs) During the 2006-07 Field Season Daniel F. Steinhoff1,2 and David H. Bromwich1,2 1Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio USA 2Atmospheric Sciences Program, Department of Geography, The Ohio State University, Columbus, Ohio USA SUMMARY The TAF-AMPS comparison project, which compares forecasts for selected variables in TAFs and AMPS to observations at Williams Field, provides insight into the behavior of the AMPS cloud ceiling product. The general consensus during the field visit was that AMPS was overestimating moisture, especially at low-levels, in the McMurdo area. However, during the study period it is found that AMPS has forecasts with cloud ceilings about a quarter of the time that TAFs and observations have ceilings, with a similar ratio compared to TAFs when ceilings are 3000 ft or lower. Further study would be needed to better understand issues associated with AMPS cloud ceiling, and a more sophisticated and detailed study would be needed to provide a more robust validation of the selected forecast fields. Regardless, this study shows that McMurdo forecasters bring additional and necessary skill into aviation forecasts. The additional forecast skill is most apparent with the cloud ceiling forecasts, as forecast accuracy increases by almost 20% when forecasters are involved. INTRODUCTION AND EXPERIMENT SETUP Terminal Ae...
Schedule - Jezek

Schedule - Jezek

October start of informal discussions and telecons for Greenland flight planning AGU Town Hall Meeting January PARCA/IceBridge Science team meeting at GSFC Summer 2011 IceBridge Flight Planning and Science Team meeting (JPL?)

Objective Key Milestones TRLin =3 Approach Develop and test radars and algorithms for imaging the base of the polar ice sheets Investigate interferometric and tomographic clutter rejection and basal imaging methods 3-d topography of the glacial bed Images of subglacial conditions Develop multiphase center P-band and VHF radars Capable of sounding 5 km of ice Single and repeat pass interferometric operation Assess the requirements for extension to continental scale campaigns PI: Prof. Kenneth C. Jezek, The Ohio State University Global Ice Sheet Interferometric Radar (GISIR) Use available topography data to simulate interferograms for testing the InSAR and tomographic concepts. Modify the SAR simulator to include operating characteristics of several aircraft and several radar designs Develop UHF and VHF radars and antenna systems Test methodology by collecting data over the Greenland and Antarctic ice sheets Algorithm validation and sensitivity assessment. Co-Is: E. Rodriguez, JPL; P. Gogineni, U. Kansas; J. Curlander, Vexcel Corp.; John Sonntag, EG&G; C. Allen, U. Kansas; P. Kanagaratnam, U. Kansas 1/ 06 Phase History Simulations and Algorithm Testing 9/06 Radar and Antenna Development 11/06 First flight test in Greenland 7/06 InSAR and tomography algorithm refinement 11/07 Second flight test in Antarctica 7/08 Algorithm and methodology assessment 8/08 Requirements doc. for continental scale imaging http://esto.nasa.gov Repeat pass tomogr...

Height error “scaling” factor Temporal Decorrelation and Topographic Layover Impact on Ka-band Swath Altimetry for Surface Water Hydrology Delwyn Moller, Remote Sensing Solutions Ernesto Rodriguez, Jet Propulsion Laboratory, California Institute of Technology Overview: Traditional radar altimetry has demonstrated the ability to retrieve surface water heights with decimeter accuracies along the nadir path. However, a profiling sensor is insufficient to provide global monitoring of fresh water bodies. In response, to address both hydrologic and oceanographic needs, the NRC Decadal Survey has recommended the Surface Water Ocean Topography (SWOT) mission. During this mission a swath-based imaging altimeter (shown at right in Figure 1) will provide the key hydrologic variables needed for comprehensive river discharge and storage observations, specifically temporal height change, slope and spatial extent [1]. In addition, key imaging capabilities provide classification masks and data for topographic corrections. As part of a “virtual mission,” we have developed a high-fidelity instrument simulator capable of predicting the radar response and error characteristics over dynamically modeled study regions [2]. In this poster we specifically address two error sources: The effects of water decorrelation on the SAR image formation. Predictions of layover contamination in the high relief topography. Coherence Time Characterization and Effects: To provide proof-of-concept validat...
Eric Larour, Mechanical Division, Thermal and Cryogenics Engineering Section Jet Propulsion Laboratory Analysis. eric.larour@jpl.nasa.gov

Eric Larour, Mechanical Division, Thermal and Cryogenics Engineering Section Jet Propulsion Laboratory Analysis. eric.larour@jpl.nasa.gov

Goals as member of the science team: carry out sensitivity analysis studies on all major basins of Greenland and Antarctica. Input parameters: basal drag, thickness and ice rheology. Output parameters: mass outflux. Carry out sampling analysis on all major basins of Antarctica and Greenland -> mass outflux mean and standard deviation Applications: Large scale modeling of Antarctica and Greenland: basal drag inversions using new DEMS, thickness maps. Short-term transient projections of mass balance at the continental level. OIB Meeting. September 2010
Daily Assignment A17

Daily Assignment A17

Repeat steps 1, 2, and 3 from A16 using a script file instead of entering commands directly into the command window. The diary file from A16 may prove helpful in completing A17
Daily Assignment A19

Daily Assignment A19

To compute the standard deviation you may want to use: MATLAB's intrinsic vector capabilities (think "dot" operators – .*, ./, .^) MATLAB's "C-like" looping capabilities a combination of the two approaches Once your MATLAB script is running, compare your answer to what MATLAB's built in standard deviation function (std) predicts
Daily Assignment A09

Daily Assignment A09

A09 combines the while loop, the for loop, and the switch/case structure plus other program elements that we have used previously. From the algorithm develop your own pseudo code for this program. Break the program into parts and then write, compile, and test the individual parts. Do NOT try to write the entire program without compiling Make variables mnemonic using three or more characters
Select Demographic, Economic, and Social Trends impacting the future of Crawford County Presentation to Crawford County Planning October 27, 2004 Presentation by Jeff S. Sharp

Select Demographic, Economic, and Social Trends impacting the future of Crawford County Presentation to Crawford County Planning October 27, 2004 Presentation by Jeff S. Sharp

Exurban Change Program Analyzing Rural-Urban Change
Using GIS to Model Patterns of Urban-Rural Land Use Change Elena Irwin, Assistant Professor Dept. of Agricultural, Environmental, and Development Economics Ohio State University

Using GIS to Model Patterns of Urban-Rural Land Use Change Elena Irwin, Assistant Professor Dept. of Agricultural, Environmental, and Development Economics Ohio State University
Low Density Development in Ohio: Trends and Impacts Jason Reece & Elena Irwin Department of Agricultural, Environmental and Development Economics The Ohio State University

Low Density Development in Ohio: Trends and Impacts Jason Reece & Elena Irwin Department of Agricultural, Environmental and Development Economics The Ohio State University

Prepared for The American Society of Farm Managers and Rural Appraisers, Ohio Chapter May 30th 2002
Change in Exurbia: Demography, Policy and Research Needs Jill Clark, The Ohio State University Allen Prindle, Otterbein College Larry Libby, The Ohio State University

Change in Exurbia: Demography, Policy and Research Needs Jill Clark, The Ohio State University Allen Prindle, Otterbein College Larry Libby, The Ohio State University
A Two-Dimensional Probability Model for Peptide Identification Using Tandem Mass Spectrometry and Protein Databases. * Computational Proteomics and Mass Spectrometry Columbus, OH Rovshan Sadygov ThermoElectron Corporation San Jose, CA.

A Two-Dimensional Probability Model for Peptide Identification Using Tandem Mass Spectrometry and Protein Databases. * Computational Proteomics and Mass Spectrometry Columbus, OH Rovshan Sadygov ThermoElectron Corporation San Jose, CA.
Clinical Translation of Cancer Biomarkers: Statistical and Epidemiologic Considerations Bruce J. Trock, Ph.D. Johns Hopkins School of Medicine Departments of Urology, Epidemiology, Oncology

Clinical Translation of Cancer Biomarkers: Statistical and Epidemiologic Considerations Bruce J. Trock, Ph.D. Johns Hopkins School of Medicine Departments of Urology, Epidemiology, Oncology
How conserved are fine scale recombination rates? Susan Ptak

How conserved are fine scale recombination rates? Susan Ptak
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