Duality Symmetric Strings, Dilatons and O(d,d) Effective Actions

We calculate the background field equations for the T-duality symmetric string building on previous work by including the effect of the Dilaton up to two-loops. Inclusion of the Dilaton allows us to obtain the full beta functionals of the duality symmetric sigma model. We are able to interpret the result in terms of a dimensionally reduced O(d,d) invariant target space effective action.Comment: 15 pages, latex; v2 reference added, typos fixe

Senior Recital: Daniel Hull, Guitar

Kemp Recital Hall Saturday Evening April 4, 1992 8:00p.m

Background Field Equations for the Duality Symmetric String

This paper describes the background field equations for strings in T-duality symmetric formalisms in which the dimension of target space is doubled and the sigma model supplemented with constraints. These are calculated by demanding the vanishing of the beta-functional of the sigma model couplings in the doubled target space. We demonstrate the equivalence with the background field equations of the standard string sigma model.Comment: 26 pages, latex, v2 typos correcte

Use of Machine Learning to Model Volume Load Effects on Changes in Jump Performance

Purpose: To use an artificial neural network (ANN) to model the effect of 15 weeks of resistance training on changes in countermovement jump (CMJ) performance in male track-and-field athletes. Methods: Resistance training volume load (VL) of 21 male division I track-and-field athletes was monitored over the course of 15 weeks, which covered their indoor and outdoor competitive season. Weekly CMJ height was also measured and used to calculate the overall 15-week change in CMJ performance. A feed-forward ANN with 5 hidden layers was used to model how the VL from each of the 15 weeks was associated with the overall change in CMJ height. Results: Testing the performance of the developed ANN on 4 separate athletes showed that 15 weeks of VL data could predict individual changes in CMJ height with an average error between 0.21 and 1.47 cm, which suggested that the ANN adequately modeled the relationship between weekly VL and its effects on CMJ performance. In addition, analysis of the relative importance of each week in predicting changes in CMJ height indicated that the VLs during deload or taper weeks were the best predictors (10%–17%) of changes in CMJ performance. Conclusions: ANN can be used to effectively model the effects of weekly VL on changes in CMJ performance. In addition, ANN can be used to assess the relative importance of each week in predicting changes in CMJ height

On the Applicability of Fixed Point Theory to the Design of Coupled Core Walls

Coupled core walls offer an efficient lateral load resisting system. Due to their exceptional stiffness (many times greater than the sum of the component wall piers), coupled core wall structures are especially attractive in earthquake-resistant settings. Current design practice does not address dynamic properties of the structure, in particular the optimization of the coupling beams. The coupling beams affect both the "static" (stiffness) and dynamic performance of the structure to varying degrees depending on their damping and stiffness properties. Fixed Point Theory is applied to find optimal damping and stiffness values for beams coupling two wall pier structures. In this initial investigative work, "performance" is defined in a novel way: as the practical minimization of transmissibility of horizontal ground motion. An initial parametric study applies fixed point theory optimization to a series of 84 sets of wall piers. From this parametric study, two prototype structures are advanced and analyzed using linear time history analyses to assess their performance in a simulated earthquake. These "optimized" structures are compared to practical, uncoupled, and rigidly linked systems to determine the validity of the application of Fixed Point Theory to the choice of coupling beam properties