The effect of boron on oxide scale formation in a new polycrystalline superalloy

Boron addition to a new polycrystalline nickel-based superalloy promotes the formation of a hitherto unreported aluminoborate phase, in the scale produced by oxidation in air at 900 °C for ~ 10,000 h. Atom probe tomography provides unambiguous confirmation of this. The ramifications of its formation are discussed

Over-Selectivity is Related to Autism Quotient and Empathizing, But not to Systematizing

The relationships of autism quotient (AQ), systematizing (SQ), and empathizing (EQ), with over-selectivity were explored to assess whether over-selectivity is implicated in complex social skills, which has been assumed, but not experimentally examined. Eighty participants (aged 18–60) were trained on a simultaneous discrimination task (AB+CD−), and tested in extinction on the degree to which they had learned about both elements of the reinforced (AB) compound. Higher AQ and lower EQ scorers demonstrated greater over-selectivity, but there was no relationship between SQ and over-selectivity. These results imply that high AQ scorers perform similarly to individuals with ASD on this cognitive task, and that over-selectivity may be related to some complex social skills, like empathy

Hypertrophic pyloric stenosis: tips and tricks for ultrasound diagnosis

We describe a systematic approach to the ultrasound (US) examination of the antropyloric region in children. US is the modality of choice for the diagnosis of hypertrophic pyloric stenosis (HPS). The imaging features of the normal pylorus and the diagnostic findings in HPS are reviewed and illustrated in this pictorial essay. Common difficulties in performing the examination and tips to help overcome them will also be discussed

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

Automatic discovery of category-specific 3D keypoints from a collection of objects of a category is a challenging problem. The difficulty is added when objects are represented by 3D point clouds, with variations in shape and semantic parts and unknown coordinate frames. We define keypoints to be category-specific, if they meaningfully represent objects’ shape and their correspondences can be simply established order-wise across all objects. This paper aims at learning such 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category. In order to do so, we model shapes defined by the keypoints, within a category, using the symmetric linear basis shapes without assuming the plane of symmetry to be known. The usage of symmetry prior leads us to learn stable keypoints suitable for higher misalignments. To the best of our knowledge, this is the first work on learning such keypoints directly from 3D point clouds for a general category. Using objects from four benchmark datasets, we demonstrate the quality of our learned keypoints by quantitative and qualitative evaluations. Our experiments also show that the keypoints discovered by our method are geometrically and semantically consistent

Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

<p>Abstract</p> <p>Background</p> <p><it>Geobacter sulfurreducens </it>is a member of the <it>Geobacter </it>species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for <it>Geobacter sulfurreducens</it>. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of <it>G. sulfurreducens </it>using thermodynamic variability analysis.</p> <p>Findings</p> <p>As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in <it>E. coli </it>by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of <it>G. sulfurreducens </it>that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility) is significant for these reactions.</p> <p>Conclusions</p> <p>Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of Δ_rG' of every reaction in the model leading to the prediction of regulatory sites in the metabolic network, thereby characterizing the regulatory network in both a model organism such as <it>E. coli </it>as well as a non model organism such as <it>G. sulfurreducens</it>.</p

An Atom Probe Tomography study of site preference and partitioning in a nickel-based superalloy

Atom Probe Tomography (APT) has been utilised for an in-depth examination of the commercial polycrystalline Ni-based superalloy RR1000, assessing compositions of the primary, secondary and tertiary γ′ phases. Clear differences in the phase chemistries are noted, particularly for the tertiary γ′ to which much of the alloy strength is attributed. Trace amounts of Hf are found to segregate strongly to the primary and secondary γ′ phases, but also exhibit an extended diffusion profile across the γ-γ′ interface up to 80 nm wide. Ti, Al and Mo demonstrate similar, yet not as pronounced diffusion profiles, indicating assumed phase chemistries may not be representative of those regions adjacent to the γ-γ′ interface. Within γ′, unique element site-occupancy preferences for this alloy were identified. Finally, the grain boundary chemistry across a γ-γ interface and that of an intragranular boride were analysed, identifying the latter as a mixed M5B3 boride rich in Mo and Cr. These demonstrate further the depth of information on Ni-alloys accessible by APT, while the overall implications of results in comparison with other in-service/model alloys are also discussed

Occurrence and Treatment of Bone Atrophic Non-Unions Investigated by an Integrative Approach

Recently developed atrophic non-union models are a good representation of the clinical situation in which many nonunions develop. Based on previous experimental studies with these atrophic non-union models, it was hypothesized that in order to obtain successful fracture healing, blood vessels, growth factors, and (proliferative) precursor cells all need to be present in the callus at the same time. This study uses a combined in vivo-in silico approach to investigate these different aspects (vasculature, growth factors, cell proliferation). The mathematical model, initially developed for the study of normal fracture healing, is able to capture essential aspects of the in vivo atrophic non-union model despite a number of deviations that are mainly due to simplifications in the in silico model. The mathematical model is subsequently used to test possible treatment strategies for atrophic non-unions (i.e. cell transplant at post-osteotomy, week 3). Preliminary in vivo experiments corroborate the numerical predictions. Finally, the mathematical model is applied to explain experimental observations and identify potentially crucial steps in the treatments and can thereby be used to optimize experimental and clinical studies in this area. This study demonstrates the potential of the combined in silico-in vivo approach and its clinical implications for the early treatment of patients with problematic fractures

A meta-analytic review of stand-alone interventions to improve body image

Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions

On the microtwinning mechanism in a single crystal superalloy

© 2017 Acta Materialia Inc. The contribution of a microtwinning mechanism to the creep deformation behaviour of single crystal superalloy MD2 is studied. Microtwinning is prevalent for uniaxial loading along 〈011〉 at 800°C for the stress range 625 to 675 MPa and 825°C for 625 MPa. Using quantitative stereology, the twin fraction and twin thickness are estimated; this allows the accumulated creep strain to be recovered, in turn supporting the role of the microtwinning mode in conferring deformation. Atom probe tomography confirms the segregation of Cr and Co at the twin/parent interface, consistent with the lowering of the stacking fault energy needed to support twin lengthening and thickening. A model for diffusion-controlled growth of twins is proposed and it is used to recover the measured creep strain rate. The work provides the basis for a thermo-mechanical constitutive model of deformation consistent with the microtwinning mechanism