A systematic study of the avian family Fringillidae, based on the structure of the skull

http://deepblue.lib.umich.edu/bitstream/2027.42/56326/1/MP081.pd

Off-line studies of the laser ionization of yttrium at the IGISOL facility

A laser ion source is under development at the IGISOL facility, Jyvaskyla, in order to address deficiencies in the ion guide technique. The key elements of interest are those of a refractory nature, whose isotopes and isomers are widely studied using both laser spectroscopic and high precision mass measurement techniques. Yttrium has been the first element of choice for the new laser ion source. In this work we present a new coupled dye-Ti:Sapphire laser scheme and give a detailed discussion of the results obtained from laser ionization of yttrium atoms produced in an ion guide via joule heating of a filament. The importance of not only gas purity, but indeed the baseline vacuum pressure in the environment outside the ion guide is discussed in light of the fast gas phase chemistry seen in the yttrium system. A single laser shot model is introduced and is compared to the experimental data in order to extract the level of impurities within the gas cell.Comment: 18 pages submitted to NIM

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Robot Egomotion from the Deformation of Active Contours

Traditional sources of information for image-based computer vision algorithms have been points, lines, corners, and recently SIFT features (Lowe, 2004), which seem to represent at present the state of the art in feature definition. Alternatively, the present work explores the possibility of using tracked contours as informative features, especially in applications no

Purposive sample consensus: A paradigm for model fitting with application to visual odometry

© Springer International Publishing Switzerland 2015. ANSAC (random sample consensus) is a robust algorithm for model fitting and outliers' removal, however, it is neither efficient nor reliable enough to meet the requirement of many applications where time and precision is critical. Various algorithms have been developed to improve its performance for model fitting. A new algorithm named PURSAC (purposive sample consensus) is introduced in this paper, which has three major steps to address the limitations of RANSAC and its variants. Firstly, instead of assuming all the samples have a same probability to be inliers, PURSAC seeks their differences and purposively selects sample sets. Secondly, as sampling noise always exists; the selection is also according to the sensitivity analysis of a model against the noise. The final step is to apply a local optimization for further improving its model fitting performance. Tests show that PURSAC can achieve very high model fitting certainty with a small number of iterations. Two cases are investigated for PURSAC implementation. It is applied to line fitting to explain its principles, and then to feature based visual odometry, which requires efficient, robust and precise model fitting. Experimental results demonstrate that PURSAC improves the accuracy and efficiency of fundamental matrix estimation dramatically, resulting in a precise and fast visual odometry

Impact of solid-electrolyte interphase reformation on capacity loss in silicon-based lithium-ion batteries

High-density silicon composite anodes show large volume changes upon charging/discharging triggering the reformation of the solid electrolyte interface (SEI), an interface initially formed at the silicon surface. The question remains how the reformation process and accompanied material evolution, in particular for industrial up-scalable cells, impacts cell performance. Here, we develop a correlated workflow incorporating X-ray microscopy, field-emission scanning electron microscopy tomography, elemental imaging and deep learning-based microstructure quantification suitable to witness the structural and chemical progression of the silicon and SEI reformation upon cycling. The nanometer-sized SEI layer evolves into a micron-sized silicon electrolyte composite structure at prolonged cycles. Experimental-informed electrochemical modelling endorses an underutilisation of the active material due to the silicon electrolyte composite growth affecting the capacity. A chemo-mechanical model is used to analyse the stability of the SEI/silicon reaction front and to investigate the effects of material properties on the stability that can affect the capacity loss

Understanding the agglomerate crystallisation of hexamine through X-ray microscopy and crystallographic modelling

© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/The detailed molecular-scale mechanism of the growth of organic crystals underpins a diversity of phenomena, such as the isolation and purification of high-quality materials for the pharmaceutical and fine chemical sectors. Recent advances in X-ray Microscopy (XRM) and complementary diffraction contrast tomography (DCT) have enabled the detailed characterisation of the micro-structure of hexamine agglomerates. Detailed XRM analysis of the growth history and micro-structure of such agglomerates reveals a highly orientated epitaxial inter-relationship between their constituent micro-crystallites. This is found to be consistent with a secondary nucleation growth mechanism associated with re-growth at the 3-fold corner sites within the crystals’ dominant {1 1 0} dodecahedral morphology. The agglomeration appears to heal upon further growth as the aligned agglomerated micro-crystals connect and fuse together but, in doing so, pockets of inter-crystallite mother liquor become trapped forming a symmetric pattern of solvent inclusions. The mechanistic origin of this phenomenon is rationalised with respect to historical data together with an analysis of the solid-state chemistry of the compound through the development of a ‘snow flake’ model. The latter draws upon hexamine's propensity for edge growth instabilities with increasing crystal size as well as its tendency for unstable growth at the facet corners along the 〈1 1 1〉 directions, a situation compounded by the lack of growth-promoting dislocations at the centers of the {1 1 0} habit surfaces. The agglomerative mechanism presented here could apply to other high symmetry crystal systems, particularly those whose crystal structures involve centred Bravais lattices and where the dominant inter-molecular interactions are angled towards the facet edges.Peer reviewe

Novel nuclear materials characterization workflows enabled by fs-laser milling

Research to support nuclear energy development faces many challenges. Understanding material microstructures is not only essential to predicting and understanding the in-service performance of materials used in nuclear energy production, but also in understanding aging and corrosion of these materials as they interact with their environment. However, microstructural characterization of nuclear materials poses unique obstacles. Unique materials and material combinations push traditional microstructural evaluation techniques to their limits. Radioactive samples make normally routine microstructural characterization tasks much more complex. Precious samples force rigorous, multi-scale analysis workflows. And, materials that face and must endure uniquely harsh operational environments increase the demands for deep microstructural understandings. In this context, multiscale characterization workflows and the technology that supports them play an integral role in advancing materials development for nuclear energy production. The advent of the femtosecond (fs) laser and its application to material ablation tasks has proven to be a game changer for materials research. With their extremely rapid milling rates (orders of magnitude faster than traditional ion beam approaches) and minimal heat affected zone (HAZ), the fs-laser has brought about a renaissance in advanced materials characterization capabilitie