Future Supernovae observations as a probe of dark energy

We study the potential impact of improved future supernovae data on our understanding of the dark energy problem. We carefully examine the relative utility of different fitting functions that can be used to parameterize the dark energy models, and provide concrete reasons why a particular choice (based on a parameterization of the equation of state) is better in almost all cases. We discuss the details of a representative sample of dark energy models and show how future supernova observations could distinguish among these. As a specific example, we consider the proposed ``SNAP'' satellite which is planned to observe around 2000 supernovae. We show how a SNAP-class data set taken alone would be a powerful discriminator among a family of models that would be approximated by a constant equation of state for the most recent epoch of cosmic expansion. We show how this family includes most of the dark energy models proposed so far. We then show how an independent measurement of $\Omega_{\rm m}$ can allow SNAP to probe the evolution of the equation of state as well, allowing further discrimination among a larger class of proposed dark energy models. We study the impact of the satellite design parameters on this method to distinguish the models and compare SNAP to alternative measurements. We establish that if we exploit the full precision of SNAP it provides a very powerful probe.Comment: 29 pages, 22 figures; replaced to match version accepted for publication in PRD, section V shortend and merged into section VI; brief discussion on non-flat cosmologies adde

Towards a Theory of GIS Program Management

After a brief flurry of monographs on business and organizational aspects of GIS in the 1990s, little attention has been paid to a systematic approach in support of GIS Program management. Most existing efforts in both public and private enterprises are based on anecdotal evidence. This chapter outlines a range of research questions and the beginning efforts to study modern GIS management practices and help develop a body of knowledge that can be used for the accreditation of GIS Programs and the certification of GIS Program managers

The decrease in growth hormone (GH) response after repeated stimulation with GH-Releasing hormone is partly caused by an elevation of somatostatin tonus.

Repeated injection of GHRH leads to a decrease in the GH response in normal subjects. Arginine (Arg) stimulates GH secretion by suppression of hypothalamic somatostatin. To confirm these findings, eight normal men were examined in a series of five settings: test 1 (GHRH/GHRH-TRH), 100 micrograms GHRH injected iv, followed by 100 micrograms GHRH, iv, after 120 min and 200 micrograms TRH, iv, after 150 min; test 2 (GHRH/Arg-TRH), like test 1, but instead of the second GHRH injection, a 30 g Arg infusion over 30 min; test 3 (GHRH/GHRH-Arg-TRH), like test 1, but additionally a 30 g Arg infusion after 120 min; test 4 (GHRH-Arg-TRH), iv GHRH and Arg infusion initially, followed by iv TRH after 30 min; and test 5 (TRH), 200 micrograms TRH, iv, at 0 min. For statistical evaluation, the area under the GH curve (AUC) from 0-120 min was compared with the AUC from 120-240 min. The GH response to the second administration of GHRH was significantly lower (P < 0.02) than the first increase [AUC, 0.5 +/- 0.01 min.mg/L (mean +/- SE) vs. 1.2 +/- 0.3]. No significant differences were found between the GH responses to either GHRH or Arg alone (AUC, 0.9 +/- 0.2 min.mg/L vs. 0.9 +/- 0.2). A larger GH increase (P < 0.02) was seen after GHRH-Arg compared to GHRH alone (AUC, 1.9 +/- 0.4 min.mg/L vs. 1.2 +/- 0.3). The GH response (P < 0.02) to GHRH-Arg stimulation was lower after previous GHRH injection than after GHRH-Arg stimulation alone (AUC, 1.9 +/- 0.4 min.mg/L vs. 3.5 +/- 0.9). There was a statistically significant difference between the TRH-stimulated TSH response in test 4 compared to that in test 5. We could show that decreasing GH responses to repeated GHRH can be avoided by a combined stimulation with GHRH/Arg. These findings suggest that the decreased GH response to a second GHRH bolus may be partly due to an elevated hypothalamic somatostatin secretion, which can be suppressed by Arg. The lower GH response to GHRH-Arg stimulation after a previous GHRH bolus suggests, furthermore, that the readily available GH pool in the human pituitary may be limited

Open Source Foundations for Spatial Decision Support Systems

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools have been developed by open source communities. In stark contrast to the abundance of OpenGeo software, there is a dearth of open source SDSS. The core of the article is a discussion of different approaches that lend themselves as platforms to develop an open source framework to build a variety of SDSS