Report of the Academic Building Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Academic Building Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Dormitory and Dining Services Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Dormitory and Dining Services Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Diplostigmaty in plants: a novel mechanism that provides reproductive assurance.

Differentiation of female sexual organs in flowering plants is rare and contrasts with the wide range of male reproductive strategies. An unusual example involves diplostigmaty, the possession of spatially and temporally distinct stigmas in Sebaea (Gentianaceae). Here, the single pistil within a flower has an apical stigma, as occurs in most flowering plants, but also a secondary stigma that occurs midway down the style, which is physically discrete and receptive several days after the apical stigma. We examined the function of diplostigmaty in Sebaea aurea, an insect-pollinated species of the Western Cape of South Africa. Floral manipulations and measurements of fertility and mating patterns provided evidence that basal stigmas function to enable autonomous delayed self-pollination, without limiting opportunities for outcrossing and thus avoiding the costs of seed discounting. We suggest that delayed selfing serves as a mechanism of reproductive assurance in populations with low plant density. The possession of dimorphic stigma function provides a novel example of a flexible mixed-mating strategy in plants that is responsive to changing demographic conditions.

Report of the Recreational Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Recreational Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Student Health Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Utility System Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Utility System Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Parking System Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Parking System Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Ice Arena Facility Revenue Note Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Ice Arena Facility Revenue Note Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Indoor Multipurpose Use and Training Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Regulated Materials Facility Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Memorial Union Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Memorial Union Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Athletic Facilities Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Report of the Athletic Facilities Revenue Bond Funds of Iowa State University of Science and Technology as of and for the year ended June 30, 2008

Iowa Department of Revenue Performance Plan, FY 2009

Agency Performance Plan, Iowa Department of Revenue

Iowa Workforce Development Revenue Performance Plan, FY 2009

Agency Performance Plan, Iowa Workforce Development

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.