BEAST: Bayesian evolutionary analysis by sampling trees

<p>Abstract</p> <p>Background</p> <p>The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented.</p> <p>Results</p> <p>BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at <url>http://beast-mcmc.googlecode.com/</url> under the GNU LGPL license.</p> <p>Conclusion</p> <p>BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.</p

Joint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs

Understanding the 3D structure of a scene is of vital importance, when it comes to developing fully autonomous robots. To this end, we present a novel deep learning based framework that estimates depth, surface normals and surface curvature by only using a single RGB image. To the best of our knowledge this is the first work to estimate surface curvature from colour using a machine learning approach. Additionally, we demonstrate that by tuning the network to infer well designed features, such as surface curvature, we can achieve improved performance at estimating depth and normals.This indicates that network guidance is still a useful aspect of designing and training a neural network. We run extensive experiments where the network is trained to infer different tasks while the model capacity is kept constant resulting in different feature maps based on the tasks at hand. We outperform the previous state-of-the-art benchmarks which jointly estimate depths and surface normals while predicting surface curvature in parallel

The transformation of Moiloa's Reserve in the Western Transvaal: politics, production and resistance in a rural setting, 1919 - 1986

Paper presented at the Wits History Workshop: Structure and Experience in the Making of Apartheid, 6-10 February, 199

An analysis of commitment strategies in planning: The details

We compare the utility of different commitment strategies in planning. Under a 'least commitment strategy', plans are represented as partial orders and operators are ordered only when interactions are detected. We investigate claims of the inherent advantages of planning with partial orders, as compared to planning with total orders. By focusing our analysis on the issue of operator ordering commitment, we are able to carry out a rigorous comparative analysis of two planners. We show that partial-order planning can be more efficient than total-order planning, but we also show that this is not necessarily so

Applying artificial intelligence to the control of space telescopes (extended abstract)

The field of astronomy has recently benefited from the availability of space telescopes. The Hubble Space Telescope (HST), for instance, despite its problems, provides a unique and valuable view of the universe. However, unlike HST, a telescope need not be in low Earth orbit to escape our thickening atmosphere: it is currently technologically feasible to put a telescope on the moon, and there are excellent reasons for doing this. Either in low Earth orbit or on the moon, a space telescope represents an expensive and sought-after resource. Thus, the planning, scheduling, and control of these telescopes is an important problem that must be seriously studied

Heptagons from the Steinmann Cluster Bootstrap

We reformulate the heptagon cluster bootstrap to take advantage of the Steinmann relations, which require certain double discontinuities of any amplitude to vanish. These constraints vastly reduce the number of functions needed to bootstrap seven-point amplitudes in planar $\mathcal{N} = 4$ supersymmetric Yang-Mills theory, making higher-loop contributions to these amplitudes more computationally accessible. In particular, dual superconformal symmetry and well-defined collinear limits suffice to determine uniquely the symbols of the three-loop NMHV and four-loop MHV seven-point amplitudes. We also show that at three loops, relaxing the dual superconformal ($\bar{Q}$) relations and imposing dihedral symmetry (and for NMHV the absence of spurious poles) leaves only a single ambiguity in the heptagon amplitudes. These results point to a strong tension between the collinear properties of the amplitudes and the Steinmann relations.Comment: 43 pages, 2 figures. v2: typos corrected; version to appear in JHE

Comparison of Mixing Characteristics for Several Fuel Injectors at Mach 8, 12, and 15 Hypervelocity Flow Conditions

CFD analysis is presented of the mixing characteristics and performance of three fuel injectors at flight Mach numbers of 8, 12, and 15. The Reynolds-averaged simulations (RAS) were carried out using the VULCAN-CFD solver. The high Mach number flow conditions match those of the experiments conducted as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies relevant to flight Mach numbers greater than 8. The injectors include a fuel placement device, a strut, and a fluidic vortical mixer, a ramp. These fuel injectors accomplish the necessary task of distributing and mixing fuel into the supersonic cross-flow, albeit via different strategies. For comparison, a flush-wall injector is also included. This type of injector generally represents the simplest method of introducing fuel into a scramjet combustor. The three injectors represent the baseline configurations of the EIMP experiments. The mixing parameters of interest, such as mixing efficiency and total pressure recovery, are computed from the RAS and compared for the three flight conditions and injector configurations. In addition to mixing efficiency and total pressure recovery, the combustion efficiency and thrust potential are also computed for the reacting simulations. Plotting the total pressure recovery and thrust potential as a function of mixing efficiency provides added insight into critical aspects of combustor performance as the flight condition and injector type are varied

Excitation spectrum of bosons in a finite one-dimensional circular waveguide via the Bethe ansatz

The exactly solvable Lieb-Liniger model of interacting bosons in one-dimension has attracted renewed interest as current experiments with ultra-cold atoms begin to probe this regime. Here we numerically solve the equations arising from the Bethe ansatz solution for the exact many-body wave function in a finite-size system of up to twenty particles for attractive interactions. We discuss the novel features of the solutions, and how they deviate from the well-known string solutions [H. B. Thacker, Rev. Mod. Phys.\ \textbf{53}, 253 (1981)] at finite densities. We present excited state string solutions in the limit of strong interactions and discuss their physical interpretation, as well as the characteristics of the quantum phase transition that occurs as a function of interaction strength in the mean-field limit. Finally we compare our results to those of exact diagonalization of the many-body Hamiltonian in a truncated basis. We also present excited state solutions and the excitation spectrum for the repulsive 1D Bose gas on a ring.Comment: 13 pages, 12 figure