The solvent dependence of enzymatic selectivity

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 1996.Includes bibliographical references (leaves 86-97).by Charles R. Wescott.Ph.D

A Multi-wavelength Study of the Sunyaev-Zel'dovich Effect in the Triple-Merger Cluster MACS J0717.5+3745 with MUSTANG and Bolocam

We present 90, 140, and 268GHz sub-arcminute resolution imaging of the Sunyaev-Zel'dovich effect (SZE) in MACSJ0717.5+3745. Our 90GHz SZE data result in a sensitive, 34uJy/bm map at 13" resolution using MUSTANG. Our 140 and 268GHz SZE imaging, with resolutions of 58" and 31" and sensitivities of 1.8 and 3.3mJy/beam respectively, was obtained using Bolocam. We compare these maps to a 2-dimensional pressure map derived from Chandra X-ray observations. Our MUSTANG data confirm previous indications from Chandra of a pressure enhancement due to shock-heated, >20keV gas immediately adjacent to extended radio emission seen in low-frequency radio maps. The MUSTANG data also detect pressure substructure that is not well-constrained by the X-ray data in the remnant core of a merging subcluster. We find that the small-scale pressure enhancements in the MUSTANG data amount to ~2% of the total pressure measured in the 140GHz Bolocam observations. The X-ray template also fails on larger scales to accurately describe the Bolocam data, particularly at the location of a subcluster known to have a high line of sight optical velocity (~3200km/s). Our Bolocam data are adequately described when we add an additional component - not described by a thermal SZE spectrum - coincident with this subcluster. Using flux densities extracted from our model fits, and marginalizing over the temperature constraints for the region, we fit a thermal+kinetic SZE spectrum to our data and find the subcluster has a best-fit line of sight proper velocity of 3600+3440/-2160km/s. This agrees with the optical velocity estimates for the subcluster. The probability of velocity<0 given our measurements is 2.1%. Repeating this analysis using flux densities measured non-parametrically results in a 3.4% probability of a velocity<=0. We note that this tantalizing result for the kinetic SZE is on resolved, subcluster scales.Comment: 10 Figures, 18 pages. this version corrects issues with the previous arXiv versio

Ewing Brass Quintet: Herb Koerselman, Trumpet; Kirby Reese, Trumpet; Don Peterson, Horn; Charles Stokes, Trombone; Ed Livingston, Tuba; March 27, 1977

Hayden AuditoriumSunday EveningMarch 27, 19778:00 p.m

Ewing Brass Quintet: Herb Koerselman, Trumpet; Kirby Reese, Trumpet; Philip Hillstrom, Horn; Charles Stokes, Trombone; Ed Livingston, Tuba; April 13, 1976

Center for the Visual Arts, Art GalleryTuesday EveningApril 13, 19768:15 p.m

Ewing Brass Quintet: Herb Koerselman, Trumpet; Kirby Reese, Trumpet; John Rehm, Trombone; Charles Stokes, Trombone; Philip Hillstrom, Horn; October 26, 1975

Hayden AuditoriumSunday EveningOctober 26, 19758:15 p.m

Defining Yield Goals and Management Zones to Minimize Yield and Nitrogen and Phosphorus Fertilizer Recommendation Errors

Three general approaches (minimize soil nutrient variability, yield, and fertilizer recommendation errors) have been used to assess nutrient management zone boundaries. The objective of this study was to determine the influence of different approaches to define management zones and yield goals on minimizing yield variability and fertilizer recommendation errors. This study used soil nutrient and yield information collected from two east-central South Dakota fields between 1995 and 2000. The crop rotation was corn (Zea mays L.) followed by soybean [Glycine max (L.) Merr.]. The four management zone delineation approaches tested were to: (i) sample areas impacted by old homesteads separately from the rest of the field; (ii) separate the field into grid cells; (iii) use geographic information systems or cluster analysis of apparent electrical conductivity, elevation, aspect, and connectedness to identify zones; and (iv) use the Order 1 soil survey. South Dakota fertilizer N and P recommendations were used to calculate fertilizer requirements. This study showed that management zones based on a 4-ha grid cell and an Order 1 soil survey had lower within-zone yield variability than the other methods tested. The best approaches for minimizing recommendation errors were nutrient specific. Nitrogen and P recommendations were improved using multiple years of yield monitor data to develop landscape-specific yield goals, sampling old homesteads separately from the rest of the field, and grid cell soil sampling to fine-tune N and P recommendations

Alternative Methods of Estimating Snow-Water Parameters

A recurrence analysis technique using probability and contingency relationships of snow depth, water equivalent, and snow density is presented. Three methods of estimating snow water parameters at site A by recurrence and the presently used regression techniques are based on (1) the value from the previous month at site A, (2) the value from a reference site, and (3) the month to previous month contingency parameter of the reference course. The recurrence technique (Pearson type 3) when it was tested on three central Idaho snow courses was most useful when method 3 was used to estimate snow depth and either method 1 or 3 was used to estimate the water equivalent. Correlation of estimated values to measured values indicated equal reliability of recurrence and regression analysis when the three methods were used. The recurrence technique can successfully be used in estimating snow water parameters and their probability of occurrence. This technique like the regression technique requires a basic data set before it can be applied

1992: Abilene Christian College Bible Lectures - Full Text

CORINTH REVISITED: Studies in I Corinthians Being the Abilene Christian University Annual Bible Lectures 1992 Published by ACU PRESS 1634 Campus Court Abilene, Texas 7960