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Atom probe tomography (APT) is a powerful technique to characterize buried three-dimensional nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure–property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the density-based spatial clustering of applications with noise algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the nonuniformity of the atomic density in the APT reconstruction itself (e.g., crystallographic poles and other field evaporation artifacts). This clustering method relies heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures, and an automatic cluster extraction algorithm to analyze clusters of varying atomic density in APT data. This approach requires only one free parameter, and other inputs can be estimated or bounded based on physical parameters, such as the lattice parameter and solute concentration. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen.
This research aims to explore the submerged landscapes of the Pilbara of western Australia, using predictive archaeological modelling, airborne LiDAR, marine acoustics, coring and diver survey. It includes excavation and geophysical investigation of a submerged shell midden in Denmark to establish guidelines for the underwater discovery of such sites elsewhere.
A gravity survey was conducted on the Windmill Islands, East Antarctica, during the 2004–05 summer season. The aim of the study was to investigate the subsurface geology of the Windmill Islands area. Ninety-seven gravity stations were established. Additionally, 49 observations from a survey in 1993–94 were re-reduced and merged with the 2004–05 data. A three-dimensional subsurface model was constructed from the merged gravity dataset to determine the subsurface geology of the Windmill Islands. The main country rock in the Windmill Islands is a Garnet-bearing Granite Gneiss. A relatively dense intrusive charnockite unit, the Ardery Charnockite, generates the dominant gravity high of the study area and has been modelled to extend to depths of 7–13 km. It has moderate to steep contacts against the surrounding Garnet-bearing Granite Gneiss. The Ardery Charnockite surrounds a less dense granite pluton, the Ford Granite, which is modelled to a depth of 6–12 km and creates a localized gravity low. This granitic pluton extends at depth towards the east. The modelling process has also shown that Mitchell Peninsula is linked to the adjacent Law Dome ice cap by an ‘ice ramp’ of approximately 100 m thickness.
Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence of other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare Bayesian parameter estimates obtained from a likelihood for complete binary networks with those obtained from likelihoods that are derived from the FRN scheme, and therefore accommodate the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, particularly for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design.
Walnuts contain a number of potentially neuroprotective compounds like vitamin E, folate, melatonin, several antioxidative polyphenols and significant amounts of n-3 α-linolenic fatty acid. The present study sought to determine the effect of walnuts on verbal and non-verbal reasoning, memory and mood. A total of sixty-four college students were randomly assigned to two treatment sequences in a crossover fashion: walnuts–placebo or placebo–walnuts. Baseline data were collected for non-verbal reasoning, verbal reasoning, memory and mood states. Data were collected again after 8 weeks of intervention. After 6 weeks of washout, the intervention groups followed the diets in reverse order. Data were collected once more at the end of the 8-week intervention period. No significant increases were detected for mood, non-verbal reasoning or memory on the walnut-supplemented diet. However, inferential verbal reasoning increased significantly by 11·2 %, indicating a medium effect size (P = 0·009; d = 0·567). In young, healthy, normal adults, walnuts do not appear to improve memory, mood or non-verbal reasoning abilities. However, walnuts may have the ability to increase inferential reasoning.
To a combinatorialist, a design is usually a 2-design or balanced incomplete-block design. However, 2-designs do not necessarily exist in all cases where a statistician might wish to use one to design an experiment. As a result, statisticians need to consider structures much more general than the combinatorialist's designs, and to decide which one is “best” in a given situation. This leads to the theory of optimal designs. There are several concepts of optimality, and no general consensus about which one to use in any particular situation.
For block designs with fixed block size k, all these optimality criteria are determined by a graph, the concurrence graph of the design, and more specifically, by the eigenvalues of the Laplacian matrix of the graph. It turns out that the optimality criteria most used by statisticians correspond to properties of this graph which are interesting in other contexts: D-optimality involves maximizing the number of spanning trees; A-optimality involves minimizing the sum of resistances between all pairs of terminals (when the graph is regarded as an electrical circuit, with each edge being a one-ohm resistor); and E-optimality involves maximizing the smallest eigenvalue of the Laplacian (the corresponding graphs are likely to have good expansion and random walk properties). If you are familiar with these properties, you may expect that related “nice” properties such as regularity and large girth (or even symmetry) may tend to hold; some of our examples may come as a surprise!
The white-beaked dolphin, Lagenorhynchus albirostris, is commonly found throughout the North Sea and shelf waters of the North Atlantic. Little is known about the behaviour and ecology of this species, especially in British coastal waters. In this paper we present details of the seasonal and geographical distribution of white-beaked dolphins around the UK, along with new information on their diet and habitat use. Analysis of historical stranding records show a segregation of the sexes, with a significant difference between when males and females strand in UK waters. There has been a steady decline in reported strandings since the 1970s and seasonal differences in the distribution of strandings suggest that sea temperature may limit white-beaked dolphin distribution around the British coast. Stomach contents' analysis, from dolphins stranded mainly on the Scottish east coast, identified haddock and whiting as the predominant fish species being taken. Boat surveys were performed along the north-east Scottish coast to examine relationships between topography, environmental conditions, dolphin presence and group size. Dolphin presence was related to seabed slope and aspect while variation in temperature explained almost 45% of variation in observed group size, with smaller groups associated with higher sea temperatures.
The recent drive within the UK National Health Service to improve psychosocial care for people with mental illness is both understandable and welcome: evidence-based psychological and social interventions are extremely important in managing psychiatric illness. Nevertheless, the accompanying downgrading of medical aspects of care has resulted in services that often are better suited to offering non-specific psychosocial support, rather than thorough, broad-based diagnostic assessment leading to specific treatments to optimise well-being and functioning. In part, these changes have been politically driven, but they could not have occurred without the collusion, or at least the acquiescence, of psychiatrists. This creeping devaluation of medicine disadvantages patients and is very damaging to both the standing and the understanding of psychiatry in the minds of the public, fellow professionals and the medical students who will be responsible for the specialty's future. On the 200th birthday of psychiatry, it is fitting to reconsider the specialty's core values and renew efforts to use psychiatric skills for the maximum benefit of patients