Terrestrial laser scanning and 3D imaging: Heritage case study – The Black Gate, Newcastle Upon Tyne

This paper offers a case study on the recording of a section of wall on a complex heritage building, the Black Gate in Newcastle upon Tyne. The paper adopts case study methodology to assess the appropriateness of using a long range scanner based upon pulse technology for the recording of part of this historic structure and describes the scanning instruments adopted as well as the selection of appropriate software for the pre-processing and documentation. The study offers an overview of the survey planning stages, field operation, and processing of 3D point cloud data using the third party software adopted, including problems encountered. Issues emerging are discussed, in both the 2D and 3D modelling of detailed surfaces from point cloud data, and in the process of software selection, data preparation and export, pre-processing of point cloud data, meshing and the creation of 2D geometry and 3D animations. The paper describes the end results offered as deliverables for this project, and offers recommendations for a working method that can produce data suitable for producing stone-by-stone elevation drawings. The work processes and cost / time indicators are included in this case study and conclusions will consider whether the technique adopted could lead to an improved solution for heritage recording compared to those traditional techniques which are currently employed to produce stone-by-stone elevations. Areas for future research are identified

On the statistical analysis of the rock magnetic S-ratio

The S-ratio is a rock magnetic parameter employed to provide a relative measure of the contributions of low and high coercivity material to a sample's saturation isothermal remanent magnetization (SIRM). The current form of expressing the S-ratio involves reporting a single value that represents the relative contribution of the low coercivity material, such as magnetite, to the overall SIRM. Expressing the S-ratio in this form is somewhat misleading, suggesting that the derived values are real numbers held in a Euclidian sample space. In fact, S-ratio data are constrained to a 1-D unit-simplex, meaning that many of the descriptive statistics reported for collections of data, for example, means and standard deviations, are in error because the employed statistical methods are designed for unconstrained data only. A simple example of this problem will be given, followed by a demonstration of how meaningful statistics for the S-ratio can be obtained using the additive-log-ratio transform of Aitchison

A Preisach method for estimating absolute paleofield intensity under the constraint of using only isothermal measurements: 1. Theoretical framework

The theoretical framework for a new nonheating method of determining absolute ancient magnetic field intensities (paleointensities) is described. The approach is based on a thermally activated Preisach model for interacting, randomly orientated single-domain grains with uniaxial anisotropy. The model includes theoretical features not accommodated by previous nonheating paleointensity methods; for example, it includes magnetostatic interactions, allows for variable cooling rates, and can identify, isolate, and reject unstable remanence carriers, i.e., multidomain and superparamagnetic contributions. The input Preisach distribution from which the acquisition of a thermal remanent magnetization (TRM) of a given rock sample can be simulated is obtained from information contained in the sample's first-order reversal curve distribution. The paleointensity estimate is determined by comparing the alternating field demagnetization spectrum of the sample's natural remanent magnetization and its simulated TRM. In the companion paper, the protocol is rigorously tested using a suite of historical samples

New methods for unmixing sediment grain size data

Grain size distribution (GSD) data are widely used in Earth sciences and although large data sets are regularly generated, detailed numerical analyses are not routine. Unmixing GSDs into components can help understand sediment provenance and depositional regimes/processes. End-member analysis (EMA), which fits one set of end-members to a given data set, is a powerful way to unmix GSDs into geologically meaningful parts. EMA estimates end-members based on covariability within a data set and can be considered as a nonparametric approach. Available EMA algorithms, however, either produce suboptimal solutions or are time consuming. We introduce unmixing algorithms inspired by hyperspectral image analysis that can be applied to GSD data and which provide an improvement over current techniques. Nonparametric EMA is often unable to identify unimodal grain size subpopulations that correspond to single sediment sources. An alternative approach is single-specimen unmixing (SSU), which unmixes individual GSDs into unimodal parametric distributions (e.g., lognormal). We demonstrate that the inherent nonuniqueness of SSU solutions renders this approach unviable for estimating underlying mixing processes. To overcome this, we develop a new algorithm to perform parametric EMA, whereby an entire data set can be unmixed into unimodal parametric end-members (e.g., Weibull distributions). This makes it easier to identify individual grain size subpopulations in highly mixed data sets. To aid investigators in applying these methods, all of the new algorithms are available in AnalySize, which is GUI software for processing and unmixing grain size data

Analyzing paleomagnetic data: To anchor or not to anchor?

Paleomagnetic directions provide the basis for use of paleomagnetism in chronological andtectonic reconstructions and for constraining past geomagnetic field behavior over a variety of timescales.Crucial to paleomagnetic analysis is the separation and quantification of a characteristic remanentmagnetization (ChRM), which relates to a process of interest, from other remanence components. Principalcomponent analysis (PCA) of stepwise demagnetization data is employed routinely in these situations toestimate magnetic remanence direc tions and their uncertainties. A given ChRM is often assumed to trendtoward the origin of a vector demagnetization diagram and prevailing data analysis frameworks allowremanence directions to be estimated based on PCA fits that are forced to pass through the origin of suchdiagrams, a process referred to as “anchoring.” While this approach is adopted commonly, little attentionhas been paid to the effects of anchoring and the influence it has on both estimated remanence direc tionsand their associated uncertainties. In almost all cases, anchoring produces an artificially low uncertaintyestimation compared to an unanchored fit. Bayesian model selection demonstrates that the effectsof anchoring cannot typically be justified from a statistical standpoint. We present an alternative toanchoring that constrains the best fit remanence direction to pass through the origin of a vectordemagnetization diagram without unreasonably distorting the representation of the demagnetization dataThis work was supported by the Australian Research Council (grant DP120103952)

Characterizing magnetofossils from first-order reversal curve (FORC) central ridge signatures

The central ridge structure of a first-order reversal curve (FORC) distribution is indicative of uniaxial noninteracting single domain magnetic particles, which provides the opportunity to identify and characterize biogenic magnetic mineral remains (magnetofossils) in sediments. Recent studies have shown that magnetofossils are widespread in the geological record and that they carry useful environmental information and contribute to paleomagnetic recording, which makes it essential to quantify how these biogenic components contribute to the magnetic properties of sediments. We present results from six sedimentary sequences whose magnetic mineral assemblages contain a significant magnetofossil contribution. Using principal component analysis, we find that the central ridge properties exhibit both intra-sequnce and inter-sequence variability that may be ascribed to external environmental factors. While samples from individual sediment sequences tend to cluster together, there is a continuum of inter-sequence behavior that appears to be related to a variety of magnetofossil properties. We demonstrate the complexity of biogenic magnetic components in sedimentary environments, but also the power and potential of FORC central ridges for understanding magnetic mixtures and unraveling environmental information. Key Points First-order reversal curve central ridges carry magnetofossil information Central ridge form varies within and between different sediment sequences Central ridge magnetofossil characterization provides environmental informatio

A statistical simulation of magnetic particle alignment in sediments

Sedimentary magnetizations are fundamental to palaeomagnetism, but the mechanisms that control remanence acquisition remain poorly constrained. Observed sedimentary natural remanent magnetizations are often orders of magnitude smaller than the saturatio

Quantication of magnetic coercivity components by the analysis of acquisition curves of isothermal remanent magnetisation

A new method of analysing isothermal remanent magnetisation (IRM) acquisition curves based on cumulative log Gaussian analysis [Robertson and France, Phys. Earth Planet. Inter. 82 (1994) 223-234] is proposed. It is based on the curve fitting of the IRM acquisition curve versus the logarithm of the applied field with: (i) the acquisition curve on a linear scale, (ii) the acquisition curve expressed as a gradient, and (iii) the acquisition curve on a probability scale. Even when a sample is not saturated, its magnetic properties can be defined, although with less certainty. The number of magnetic components required for an optimal fit to a measured IRM acquisition curve is evaluated statistically. The method discriminates on the basis of different mineral coercivity. Therefore, additional rock-magnetic tests are still required to separate minerals with similar coercivities

Substitution, delegation or addition? Implications of workforce skill mix on efficiency and interruptions in computed tomography

Objectives: This study evaluated multiple computed tomography (CT) workforce models to identify any implications on efficiency (length of stay, scan frequency and workforce cost) and scanning radiographer interruptions through substituting or supplementing with a trained CT assistant. Methods: The study was conducted in a CT unit of a tertiary Queensland hospital and prospectively compared four workforce models, including usual practice: Model 1 used an administrative assistant (AA) and one radiographer Model 2 substituted a medical imaging assistant (MIA) for the AA Model 3 was usual practice, consisting of two radiographers and Model 4 included two radiographers, with a supplemented MIA. Observational data were collected over 7 days per model and were cross-checked against electronic records. Data for interruption type and frequency, as well as scan type and duration, were collected. Annual workforce costs were calculated as measures of efficiency. Results: Similar scan frequency and parameters (complexity) occurred across all models, averaging 164 scans (interquartile range 160-172 scans) each. The median times from patient arrival to examination completion in Models 1-4 were 47, 35, 46 and 33 min respectively. There were between 34 and 104 interruptions per day across all models, with the 'assistant role' fielding the largest proportion. Model 4 demonstrated the highest workforce cost, and Model 2 the lowest. Conclusion: This study demonstrated that assistant models offer similar patient throughput to usual practice at a reduced cost. Model 2 was the most efficient of all two-staff models (Models 1-3), offering the cheapest workforce, slightly higher throughput and faster examination times. Not surprisingly, the additional staff model (Model 4) offered greater overall examination times and throughput, with fewer interruptions, although workforce cost and possible role ambiguity were both limitations of this model. These findings may assist decision makers in selecting the optimal workforce design for their own individual contexts. What is known about the topic?: Innovative solutions are required to address ongoing health workforce sustainability concerns. Workforce substitution models using trained assistants have demonstrated numerous benefits internationally, with translation to the Australian allied health setting showing promise. What does this paper add?: Building on existing research, this study provides clinical workforce alternatives that maintain patient throughput while offering cost efficiencies. This study also quantified the many daily interruptions that occur within the CT setting, highlighting a potential clinical risk. To the best of our knowledge, this study is the first to empirically test the use of allied health assistants within CT. What are the implications for practitioners?: Role substitution in CT may offer solutions to skills shortages, increasing expenditure and service demand. Incorporating appropriate assistant workforce models can maintain throughput while demonstrating implications for efficiency and interruptions, potentially affecting staff stress and burnout. In addition, the assistant's scope and accepted level of interruptions should be considerations when choosing the most appropriate model

Measuring, Processing, and Analyzing Hysteresis Data

Magnetic hysteresis loops are important in theoretical and applied rock magnetism with applications to paleointensities, paleoenvironmental analysis, and tectonic studies, among many others. Information derived from these data is among the most ubiquitous rock magnetic data used by the Earth science community. Despite their prevalence, there are no general guidelines to aid scientists in obtaining the best possible data and no widely available software to allow the efficient analysis of hysteresis loop data using the most advanced and appropriate methods. Here we outline detrimental factors and simple approaches to measuring better hysteresis data and introduce a new software package called Hysteresis Loop analysis box (HystLab) for processing and analyzing loop data. Capable of reading a wide range of data formats, HystLab provides an easy‐to‐use interface allowing users to visualize their data and perform advanced processing, including loop centering, drift correction, high‐field slope corrections, and loop fitting to improve the results from noisy specimens. A large number of hysteresis loop properties and statistics are calculated by HystLab and can be exported to text files for further analysis. All plots generated by HystLab are customizable and user preferences can be saved for future use. In addition, all plots can be exported to encapsulated postscript files that are publication ready with little or no adjustment. HystLab is freely available for download at https://github.com/greigpaterson/HystLab and in combination with our simple measurement guide should help the paleomagnetic and rock magnetic communities get the most from their hysteresis data.G. A. P. acknowledges funding from a NERC Independent Research Fellowship (NE/P017266/1) and NSFC grants 41574063 and 41621004, and CAS project XDB18010203. M. J. acknowledges support of the Institute for Rock Magnetism, funded by the NSF Instruments and Facilities program and by the University of Minnesota. The data presented here are available with the HystLab software package (https:// github.com/greigpaterson/HystLab)