Kinematic Plasticity during Flight in Fruit Bats: Individual Variability in Response to Loading

All bats experience daily and seasonal fluctuation in body mass. An increase in mass requires changes in flight kinematics to produce the extra lift necessary to compensate for increased weight. How bats modify their kinematics to increase lift, however, is not well understood. In this study, we investigated the effect of a 20% increase in mass on flight kinematics for Cynopterus brachyotis, the lesser dog-faced fruit bat. We reconstructed the 3D wing kinematics and how they changed with the additional mass. Bats showed a marked change in wing kinematics in response to loading, but changes varied among individuals. Each bat adjusted a different combination of kinematic parameters to increase lift, indicating that aerodynamic force generation can be modulated in multiple ways. Two main kinematic strategies were distinguished: bats either changed the motion of the wings by primarily increasing wingbeat frequency, or changed the configuration of the wings by increasing wing area and camber. The complex, individual-dependent response to increased loading in our bats points to an underappreciated aspect of locomotor control, in which the inherent complexity of the biomechanical system allows for kinematic plasticity. The kinematic plasticity and functional redundancy observed in bat flight can have evolutionary consequences, such as an increase potential for morphological and kinematic diversification due to weakened locomotor trade-offs

Moments under conjugate distributions in bioassay

Members of the conjugate family of distributions arising in bioassay experiments do not have moments. In particular the posterior mean of the ED50 fails to exist under a conjugate prior.Bayesian bioassay binary response conjugate prior ED50

Spatio-Time Interaction with Disease Mapping

this paper will be this following. a. Demographic effects (age will be used for illustration, though sex and race may also be added.) b. Spatial effects among different geographic units. c. Temporal effects on different demographic groups. d. Regional changes over time within demographic groups. e. Spatial correlation among regional changes over time for different demographic groups. f. Residual effects not explained by the mixed linear model. g. MCMC computing and Bayesian model fitting. Most papers on disease mapping in the past have focused on a and b: The residual effect in f has been considered by Ghosh et al. (1996) as a term in a generalized mixed linear model. A similar result is obtained through a Poisson--gamma model in Tsutakawa (1988). Here is the outline of the paper. In Section 2, we introduce a loglinear mixed model for mortality rates, where age effects are fixed and regional effects over time are random. An autoregressive model is used to model the random effects. The prior distributions for the variance components and spatial correlations are specified. In Section 3, we present conditions on the noninformative priors so that the posterior distributions are proper. In Section 4, estimation of the parameters via MCMC is proposed. The available conditional distributions are first found and some computational issues are discussed. Numerical results on age effects, regional effects, variance components, special correlations are interpreted. It will be seen that these estimates are quite robust in terms of the choices of hyperparameters. The convergence of Gibbs sampling is investigated along the line of Gelman and Rubin (1992) diagnostics. The model fitting is discussed in Section 5. Bayes factors are used to examine the importance of the fixed parameters..

The effect of uncertainty of item parameter estimation on ability estimates

ability estimation, Bayesian IRT, calibration, pretest, three-parameter logistic,

Bayesian estimation of item response curves

item responses, Bayesian estimation, EM algorithm,

SIBYLS - A SAXS and protein crystallography beamline at the ALS

The new Structurally Integrated BiologY for Life Sciences (SIBYLS) beamline at the Advanced Light Source will be dedicated to Macromolecular Crystallography (PX) and Small Angle X-ray Scattering (SAXS). SAXS will provide structural information of macromolecules in solutions and will complement high resolution PX studies on the same systems but in a crystalline state. The x-ray source is one of the 5 Tesla superbend dipoles recently installed at the ALS that allows for a hard x-ray program to be developed on the relatively low energy Advanced Light Source (ALS) ring (1.9 GeV). The beamline is equipped with fast interchangeable monochromator elements, consisting of either a pair of single Si(111) crystals for crystallography, or a pair of multilayers for the SAXS mode data collection (E/ΔE~;1/110). Flux rates with Si(111) crystals for PX are measured as 2x1011 hv/sec/400 mA through a 100μm pinhole at 12.4 KeV. For SAXS the flux is up to 3x1013 photons/sec/400 mA at 10 KeV with all apertures open when using the multilayer monochromator elements. The performance characteristics of this unique beamline will be described