Violation of cell lineage restriction compartments in the chick hindbrain

Previous cell lineage studies indicate that the repeated neuromeres of the chick hindbrain, the rhombomeres, are cell lineage restriction compartments. We have extended these results and tested if the restrictions are absolute. Two different cell marking techniques were used to label cells shortly after rhombomeres form (stage 9+ to 13) so that the resultant clones could be followed up to stage 25. Either small groups of cells were labelled with the lipophilic dye DiI or single cells were injected intracellularly with fluorescent dextran. The majority of the descendants labelled by either technique were restricted to within a single rhombomere. However, in a small but reproducible proportion of the cases (greater than 5%), the clones expanded across a rhombomere boundary. Neither the stage of injection, the stage of analysis, the dorsoventral position, nor the rhombomere identity correlated with the boundary crossing. Judging from the morphology of the cells, both neurons and non-neuronal cells were able to expand over a boundary. These results demonstrate that the rhombomere boundaries represent cell lineage restriction barriers which are not impenetrable in normal development

Multilevel Artificial Neural Network Training for Spatially Correlated Learning

Multigrid modeling algorithms are a technique used to accelerate relaxation models running on a hierarchy of similar graphlike structures. We introduce and demonstrate a new method for training neural networks which uses multilevel methods. Using an objective function derived from a graph-distance metric, we perform orthogonally-constrained optimization to find optimal prolongation and restriction maps between graphs. We compare and contrast several methods for performing this numerical optimization, and additionally present some new theoretical results on upper bounds of this type of objective function. Once calculated, these optimal maps between graphs form the core of Multiscale Artificial Neural Network (MsANN) training, a new procedure we present which simultaneously trains a hierarchy of neural network models of varying spatial resolution. Parameter information is passed between members of this hierarchy according to standard coarsening and refinement schedules from the multiscale modelling literature. In our machine learning experiments, these models are able to learn faster than default training, achieving a comparable level of error in an order of magnitude fewer training examples.Comment: Manuscript (24 pages) and Supplementary Material (4 pages). Updated January 2019 to reflect new formulation of MsANN structure and new training procedur

Accelerated Parameter Estimation with DALEχ\chi

We consider methods for improving the estimation of constraints on a high-dimensional parameter space with a computationally expensive likelihood function. In such cases Markov chain Monte Carlo (MCMC) can take a long time to converge and concentrates on finding the maxima rather than the often-desired confidence contours for accurate error estimation. We employ DALE$\chi$ (Direct Analysis of Limits via the Exterior of $\chi^2$) for determining confidence contours by minimizing a cost function parametrized to incentivize points in parameter space which are both on the confidence limit and far from previously sampled points. We compare DALE$\chi$ to the nested sampling algorithm implemented in MultiNest on a toy likelihood function that is highly non-Gaussian and non-linear in the mapping between parameter values and $\chi^2$. We find that in high-dimensional cases DALE$\chi$ finds the same confidence limit as MultiNest using roughly an order of magnitude fewer evaluations of the likelihood function. DALE$\chi$ is open-source and available at https://github.com/danielsf/Dalex.git

Observational Constraints on Trojans of Transiting Extrasolar Planets

Theoretical studies predict that Trojans are likely a frequent byproduct of planet formation and evolution. We present a novel method of detecting Trojan companions to transiting extrasolar planets which involves comparing the time of central eclipse with the time of the stellar reflex velocity null. We demonstrate that this method offers the potential to detect terrestrial-mass Trojans using existing ground-based observatories. This method rules out Trojan companions to HD 209458b and HD 149026b more massive than ~13 Earth masses and \~25 Earth masses at a 99.9% confidence level. Such a Trojan would be dynamically stable, would not yet have been detected by photometric or spectroscopic monitoring, and would be unrecognizable from radial velocity observations alone. We outline the future prospects for this method, and show that the detection of a "Hot Trojan" of any mass would place a significant constraint on theories of orbital migration.Comment: 6 pages, 2 figures, 1 table, accepted to ApJL. Added references, new transiting planets to table; minor correction

O-ring gasket test fixture

An apparatus is presented for testing O-ring gaskets under a variety of temperature, pressure, and dynamic loading conditions. Specifically, this apparatus has the ability to simulate a dynamic loading condition where the sealing surface in contact with the O-ring moves both away from and axially along the face of the O-ring