Problems of university‐based scientists associated with clinical trials

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116952/1/cpt1979255part2662.pd

DESIGN AND MANAGEMENT OF LARGE MULTICENTER CLINICAL TRIALS

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73282/1/j.1749-6632.1978.tb25600.x.pd

Formation of Pillars at the Boundaries between H II Regions and Molecular Clouds

We investigate numerically the hydrodynamic instability of an ionization front (IF) accelerating into a molecular cloud, with imposed initial perturbations of different amplitudes. When the initial amplitude is small, the imposed perturbation is completely stabilized and does not grow. When the initial perturbation amplitude is large enough, roughly the ratio of the initial amplitude to wavelength is greater than 0.02, portions of the IF temporarily separate from the molecular cloud surface, locally decreasing the ablation pressure. This causes the appearance of a large, warm HI region and triggers nonlinear dynamics of the IF. The local difference of the ablation pressure and acceleration enhances the appearance and growth of a multimode perturbation. The stabilization usually seen at the IF in the linear regimes does not work due to the mismatch of the modes of the perturbations at the cloud surface and in density in HII region above the cloud surface. Molecular pillars are observed in the late stages of the large amplitude perturbation case. The velocity gradient in the pillars is in reasonably good agreement with that observed in the Eagle Nebula. The initial perturbation is imposed in three different ways: in density, in incident photon number flux, and in the surface shape. All cases show both stabilization for a small initial perturbation and large growth of the second harmonic by increasing amplitude of the initial perturbation above a critical value.Comment: 21 pages, 8 figures, accepted for publication in ApJ. high resolution figures available upon reques

Stronger Constraints on the Evolution of the MBH−σ∗M_{\rm{BH}}-\sigma_* Relation up to z∼0.6z\sim0.6

We revisit the possibility of redshift evolution in the $M_{\rm{BH}}-\sigma_*$ relation with a sample of 22 Seyfert 1 galaxies with black holes (BHs) in the mass range $10^{6.3}-10^{8.3}~M_\odot$ and redshift range $0.03<z<0.57$ with spectra obtained from spatially resolved Keck/Low-Resolution Imaging Spectrometer observations. Stellar velocity dispersions were measured directly from the Mg Ib region, taking into consideration the effect of Fe II contamination, active galactic nucleus (AGN) dilution, and host-galaxy morphology on our measurements. BH masses are estimated using the H$\beta$ line width, and the luminosity at 5100 \overset{\lower.5em\circ}{\mathrm{A}} is estimated from surface brightness decomposition of the AGN from the host galaxy using high-resolution imaging from the Hubble Space Telescope. Additionally, we investigate the use of the [O III]$\lambda5007$ emission line width as a surrogate for stellar velocity dispersion, finding better correlation once corrected for Fe II contamination and any possible blueshifted wing components. Our selection criteria allowed us to probe lower-luminosity AGNs and lower-mass BHs in the non-local universe than those measured in previous single-epoch studies. We find that any offset in the $M_{\rm{BH}}-\sigma_*$ relation up to $z\sim0.6$ is consistent with the scatter of local BH masses, and address the sources of biases and uncertainties that contribute to this scatter.Comment: Accepted 14 May 2019 for publication in ApJ. 42 pages, 12 figures, 4 tables. Corrected for typographical error

Late Bayesian inference in mental transformations

Many skills rely on performing noisy mental computations on noisy sensory measurements. Bayesian models suggest that humans compensate for measurement noise and reduce behavioral variability by biasing perception toward prior expectations. Whether a similar strategy is employed to compensate for noise in downstream mental and sensorimotor computations is not known. We tested humans in a battery of tasks and found that tasks which involved more complex mental transformations resulted in increased bias, suggesting that humans are able to mitigate the effect of noise in both sensorimotor and mental transformations. These results indicate that humans delay inference in order to account for both measurement noise and noise in downstream computations.Alfred P. Sloan Foundation (BR-2014-102)Esther A. and Joseph Klingenstein FundSimons Foundation (542993SPI)McKnight Endowment Fund for NeuroscienceMcGovern Institute for Brain Research at MI

Contrasting Modes of Diversification in the Aux/IAA and ARF Gene Families

The complete genomic sequence for Arabidopsis provides the opportunity to combine phylogenetic and genomic approaches to study the evolution of gene families in plants. The Aux/IAA and ARF gene families, consisting of 29 and 23 loci in Arabidopsis, respectively, encode proteins that interact to mediate auxin responses and regulate various aspects of plant morphological development. We developed scenarios for the genomic proliferation of the Aux/IAA and ARF families by combining phylogenetic analysis with information on the relationship between each locus and the previously identified duplicated genomic segments in Arabidopsis. This analysis shows that both gene families date back at least to the origin of land plants and that the major Aux/IAA and ARF lineages originated before the monocot-eudicot divergence. We found that the extant Aux/IAA loci arose primarily through segmental duplication events, in sharp contrast to the ARF family and to the general pattern of gene family proliferation in Arabidopsis. Possible explanations for the unusual mode of Aux/IAA duplication include evolutionary constraints imposed by complex interactions among proteins and pathways, or the presence of long-distance cis-regulatory sequences. The antiquity of the two gene families and the unusual mode of Aux/IAA diversification have a number of potential implications for understanding both the functional and evolutionary roles of these genes

Magnetohydrodynamic scaling: From astrophysics to the laboratory

During the last few years, considerable progress has been made in simulating astrophysical phenomena in laboratory experiments with high-power lasers. Astrophysical phenomena that have drawn particular interest include supernovae explosions; young supernova remnants; galactic jets; the formation of fine structures in late supernovae remnants by instabilities; and the ablation-driven evolution of molecular clouds. A question may arise as to what extent the laser experiments, which deal with targets of a spatial scale of ∼100 μm and occur at a time scale of a few nanoseconds, can reproduce phenomena occurring at spatial scales of a million or more kilometers and time scales from hours to many years. Quite remarkably, in a number of cases there exists a broad hydrodynamic similarity (sometimes called the “Euler similarity”) that allows a direct scaling of laboratory results to astrophysical phenomena. A discussion is presented of the details of the Euler similarity related to the presence of shocks and to a special case of a strong drive. Constraints stemming from the possible development of small-scale turbulence are analyzed. The case of a gas with a spatially varying polytropic index is discussed. A possibility of scaled simulations of ablation front dynamics is one more topic covered in this paper. It is shown that, with some additional constraints, a simple similarity exists. © 2001 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71174/2/PHPAEN-8-5-1804-1.pd

Plastic Deformation in Laser-Induced Shock Compression of Monocrystalline Copper

Copper monocrystals were subjected to shock compression at pressures of 10–60 GPa by a short (3 ns initial) duration laser pulse. Transmission electron microscopy revealed features consistent with previous observations of shock-compressed copper, albeit at pulse durations in the µs regime. The results suggest that the defect structure is generated at the shock front. A mechanism for dislocation generation is presented, providing a realistic prediction of dislocation density as a function of pressure. The threshold stress for deformation twinning in shock compression is calculated from the constitutive equations for slip, twinning, and the Swegle-Grady relationship

A cerebellar mechanism for learning prior distributions of time intervals

Knowledge about the statistical regularities of the world is essential for cognitive and sensorimotor function. In the domain of timing, prior statistics are crucial for optimal prediction, adaptation and planning. Where and how the nervous system encodes temporal statistics is, however, not known. Based on physiological and anatomical evidence for cerebellar learning, we develop a computational model that demonstrates how the cerebellum could learn prior distributions of time intervals and support Bayesian temporal estimation. The model shows that salient features observed in human Bayesian time interval estimates can be readily captured by learning in the cerebellar cortex and circuit level computations in the cerebellar deep nuclei. We test human behavior in two cerebellar timing tasks and find prior-dependent biases in timing that are consistent with the predictions of the cerebellar model