Efficient tracking of human poses using a manifold hierarchy

In this paper a 3D human pose tracking framework is presented. A new dimensionality reduction method (Hierarchical Temporal Laplacian Eigenmaps) is introduced to represent activities in hierarchies of low dimensional spaces. Such a hierarchy provides increasing independence between limbs, allowing higher flexibility and adaptability that result in improved accuracy. Moreover, a novel deterministic optimisation method (Hierarchical Manifold Search) is applied to estimate efficiently the position of the corresponding body parts. Finally, evaluation on public datasets such as HumanEva demonstrates that our approach achieves a 62.5mm-65mm average joint error for the walking activity and outperforms state-of-the-art methods in terms of accuracy and computational cost.

Structure of the adenylation domain of an NAD+-dependent DNA ligase

Background: DNA ligases catalyse phosphodiester bond formation between adjacent bases in nicked DNA, thereby sealing the nick. A key step in the catalytic mechanism is the formation of an adenylated DNA intermediate. The adenyl group is derived from either ATP (in eucaryotes and archaea) or NAD+4 (in bacteria). This difference in cofactor specificity suggests that DNA ligase may be a useful antibiotic target.

Results: The crystal structure of the adenylation domain of the NAD+-dependent DNA ligase from Bacillus stearothermophilus has been determined at 2.8 Å resolution. Despite a complete lack of detectable sequence similarity, the fold of the central core of this domain shares homology with the equivalent region of ATP-dependent DNA ligases, providing strong evidence for the location of the NAD+-binding site.

Conclusions: Comparison of the structure of the NAD+4-dependent DNA ligase with that of ATP-dependent ligases and mRNA-capping enzymes demonstrates the manifold utilisation of a conserved nucleotidyltransferase domain within this family of enzymes. Whilst this conserved core domain retains a common mode of nucleotide binding and activation, it is the additional domains at the N terminus and/or the C terminus that provide the alternative specificities and functionalities in the different members of this enzyme superfamily.

Effect of quantization of vibrations on the structural properties of crystals

We study the structural effects produced by the quantization of vibrational degrees of freedom in periodic crystals at zero temperature. To this end we introduce a methodology based on mapping a suitable subspace of the vibrational manifold and solving the Schrödinger equation in it. A number of increasingly accurate approximations ranging from the quasiharmonic approximation (QHA) to the vibrational self-consistent field (VSCF) method and the exact solution are described. A thorough analysis of the approximations is presented for model monatomic and hydrogen-bonded chains, and results are presented for a linear H-F chain where the potential-energy surface is obtained via first-principles electronic structure calculations. We focus on quantum nuclear effects on the lattice constant and show that the VSCF is an excellent approximation, meaning that correlation between modes is not extremely important. The QHA is excellent for covalently bonded mildly anharmonic systems, but it fails for hydrogen-bonded ones. In the latter, the zero-point energy exhibits a nonanalytic behavior at the lattice constant where the H atoms center, which leads to a spurious secondary minimum in the quantum-corrected energy curve. An inexpensive anharmonic approximation of noninteracting modes appears to produce rather good results for hydrogen-bonded chains for small system sizes. However, it converges to the incorrect QHA results for increasing size. Isotope effects are studied for the first-principles H-F chain. We show how the lattice constant and the H-F distance increase with decreasing mass and how the QHA proves to be insufficient to reproduce this behavior.

Branching ratios of x-ray photons from dielectronic recombination processes in H-like titanium ions

In dielectronic recombination of hydrogenlike ions an intermediate doubly excited heliumlike ion is formed. Since the K shell is empty, both excited electrons can decay sequentially to the ground state. In this paper we analyze the x-ray radiation emitted from doubly and singly excited heliumlike titanium ions produced inside the Tokyo electron beam ion trap. Theoretical population densities of the singly excited states after the first transition and the transition probabilities of these states into the ground state were also calculated. This allowed theoretical branching ratios to be determined for each manifold. These branching ratios are compared to the experimentally obtained x-ray distribution by fitting across the relevant peak using a convolution of the theoretically obtained resonance strengths and energies. By taking into account 2E1 transitions which are not observed in the experiment, the measured and calculated ratios agree well. This method provides a valuable insight into the transition dynamics of excited highly charged ions.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Fluorescence yields for 3lnl′ Rydberg series in ions belonging to the He isoelectronic sequence

Fluorescence yields are reported for 3lnl' Rydberg series members in He-like ions of N, O and Ne. Results are presented for singlet series members with n values between 3 and 9, i.e. up to the region of overlap with the states belonging to the 4l4l' manifold in these atoms. This data is required, for example, for the interpretation of charge-exchange experiments involving bare N, O and Ne nuclei. Fluorescence yields, averaged over all 3lnl' singlet states, larger than 50% are obtained from about n = 7.

Automatic decomposition and efficient semi-structured meshing of complex solids

In this paper, a novel approach to automatically sub-divide a complex geometry and apply an efficient mesh is presented. Following the identification and removal of thin-sheet regions from an arbitrary solid using the thick/thin decomposition approach developed by Robinson et al. [1], the technique here employs shape metrics generated using local sizing measures to identify long-slender regions within the thick body. A series of algorithms automatically partition the thick region into a non-manifold assembly of long-slender and complex sub-regions. A structured anisotropic mesh is applied to the thin-sheet and long-slender bodies, and the remaining complex bodies are filled with unstructured isotropic tetrahedra. The resulting semi-structured mesh possesses significantly fewer degrees of freedom than the equivalent unstructured mesh, demonstrating the effectiveness of the approach. The accuracy of the efficient meshes generated for a complex geometry is verified via a study that compares the results of a modal analysis with the results of an equivalent analysis on a dense tetrahedral mesh.

Automatic dimensional reduction and meshing of stiffened thin-wall structures

The creation of idealised, dimensionally reduced meshes for preliminary design and optimisation remains a time-consuming, manual task. A dimensionally reduced model is ideal for assessing design changes through modification of element properties without the need to create a new geometry or mesh. In this paper, a novel approach for automating the creation of mixed dimensional meshes is presented. The input to the process is a solid model which has been decomposed into a non-manifold assembly of smaller volumes with different meshing significance. Associativity between the original solid model and the dimensionally reduced equivalent is maintained. The approach is validated by means of a free-free modal analysis on an output mesh of a gas turbine engine component of industrial complexity. Extensions and enhancements to this work are also discussed.