Generative Adversarial Networks (GANs) have recently demonstrated the capability to synthesize compelling real-world images, such as room interiors, album covers, manga, faces, birds, and flowers. While existing models can synthesize images based on global constraints such as a class label or caption, they do not provide control over pose or object location. We propose a new model, the Generative Adversarial What-Where Network (GAWWN), that synthesizes images given instructions describing what content to draw in which location. We show high-quality 128 × 128 image synthesis on the Caltech-UCSD Birds dataset, conditioned on both informal text descriptions and also object location. Our system exposes control over both the bounding box around the bird and its constituent parts. By modeling the conditional distributions over part locations, our system also enables conditioning on arbitrary subsets of parts (e.g. only the beak and tail), yielding an efficient interface for picking part locations. We also show preliminary results on the more challenging domain of text-and location-controllable synthesis of images of human actions on the MPII Human Pose dataset.

While considerable research exists on models designed to capture specific risk and return attributes of fixed income securities, general equilibrium and arbitrage asset valuation theories (e.g., CAPM, APT, Option Pricing) have been applied primarily to common stocks. Pricing models been used to empirically test risk and return relationships for fixed income securities.The purpose of this study is to review the major directions of research in bond risk and return and to analyze the use of OLS regression in determination of CAPM based market model risk estimates. Both Alexander [ l ] and Weinstein [ 2 ] have recently used OLS regression to obtain market model estimates of security betas for fixed income securities. Alexander highlights some of the violations of assumptions (e.g., autocorrelation of residuals) of the market model regression. This paper confirms his finding and uses Cochrane-Orcutt procedures to remove the effects of residual autocorrelation.Only recently have C U M , APT, and Option Statistical DesignFirst, distribution properties of the bond returns use in the analysis are reviewed. Second, market model parameters derived from the OLS and Cochrane-Orcutt regressions are used to forecast bond returns in a following prediction period. Lastly, the parameters of the market model are used as inputs to the Sharpe portfolio model to derive efficient bond portfolios. The correspondence between the return and variance of corner efficient portfolios and the actual return and risk in hold-out period i s also used as a basis for determining the usefulness of OLS determined bond betas. Summary and ConclusionsIt i s important to note that OLS estimates of beta may be systematically biased since a bond's beta i s a function of its duration, which systematically declines as the bond approaches maturity. This is also true, however, for a stock's beta. For stocks or bonds, the estimated beta is at best insignificantly different from the true average beta of the forecast o r prediction period. In addition, problems in derivation of duration based beta models are such that duration based beta models are not necessarily superior to OLS determined beta models. Given the greater familiarity and use of OLS regressiori models, this paper instead concentrates on problems and approaches to deriving OLS based bond betas. For the period analyzed the various violations of the assumptions of the linear regression model did not seriously affect estimation expected returns on risk. References[l] Alexander, Gordon, "Applying the Market Model to Long-Term Corporate

Objective: To evaluate the effect of the placement angle, diameter, length and bone density on the mechanical stability of orthodontic mini-implants by measuring their pull-out strengths. Design: A total of 120 mini-implants of four different dimensions made from titanium were used. They measured 1.3 × 6.0mm, 1.3 × 8.0 mm, 1.5 × 6.0 mm and 1.5 × 8.0 mm. Synthetic polyurethane bone blocks (Saw Bones, USA) in two different densities were used. Setting: Each size of mini-implant was inserted equidistantly into synthetic bone blocks of two different densities, in three different insertion angles of 30°, 60° and 90°. This resulted in 24 test groups with five mini-implants allocated to each group. Methods: The pull-out strength was measured using an Instron Universal Testing Machine exerting a vertical force parallel to the long axis of the mini-implant until removal or failure occurred. Peak load at failure of the mini-implant was recorded in kN. Results: Showed that mini-implants placed at an insertion angle of 30° offered least resistance to pull-out. Mini-implants 6.0 mm in length showed less pull-out strength compared to the longer 8.0-mm mini-implants. Mini-implants 1.3 mm in diameter provided similar pull-out values as 1.5-mm mini-implants. Bone densities of 0.20 g/cc and 0.32 g/cc did not affect the pull-out strength of mini-implants. Conclusion: From the study, it was concluded that a logical choice of mini-implant dimension and prudent use of placement technique can help achieve the treatment goals with a reduced hazard of mini-implant failure.