Local composition and nanoindentation response of δ-phase and adjacent γ′′-free zone in a Ni-based superalloy

Experimental differentiation of individual strengthening effects from the nanoscale precipitates in Alloy 718 remains challenging due to co-precipitation of γ′ and γ′′. Here, we examine a region adjacent to the δ-phase consisting of γ-matrix containing γ′-precipitates only. The width and compositional profile of this γ′′-free zone is uncovered via high-resolution characterization. Nanomechanical analyses reveal that the lack of γ′′-precipitates lower the hardness of the γ′′-free zone by 10–20%, while the δ-phase is found to be ∼80% harder than the γ-matrix. These findings may guide mechanical modelling and microstructural engineering of stronger superalloys critical to aerospace industry

Electron microscope loading and in situ nanoindentation of water ice at cryogenic temperatures

Interest in the technique of low temperature environmental nanoindentation has gained momentum in recent years. Low temperature indentation apparatuses can, for instance, be used for systematic measurements of the mechanical properties of ice in the laboratory, in order to accurately determine the inputs for the constitutive equations describing the rheologic behaviour of natural ice (i.e., the Glen flow law). These properties are essential to predict the movement of glaciers and ice sheets over time as a response to a changing climate. Herein, we introduce a new experimental setup and protocol for electron microscope loading and in situ nanoindentation of water ice. Preliminary testing on pure water ice yield elastic modulus and hardness measurements of 4.1 GPa and 176 MPa, respectively, which fall within the range of previously published values. Our approach demonstrates the potential of low temperature, in situ, instrumented nanoindentation of ice under controlled conditions in the SEM, opening the possibility for investigating individual structural elements and systematic studies across species and concentration of impurities to refine to constitutive equations for natural ice

Promoting Recovery from Substance Misuse through Engagement with Community Assets: Asset Based Community Engagement

© The Author(s) 2019. Evidence shows that engagement with community resources can aid the process of recovery from substance misuse, yet systematic approaches to mapping resources and building bridges to these for recovery populations are limited. If done successfully, engagement with resources that are pro-social and afford access to meaningful activities not only provides a platform for personal development, but also has the ability to trigger a social contagion of positive behaviour and improve connectedness within communities. The current paper uses Asset Based Community Development (ABCD) as the basis for an enhanced version called Asset Based Community Engagement (ABCE). The work of ABCD has been pivotal in encouraging citizen-led, strengths-based approaches to community development, yet scientific support for it remains limited. While this approach has gained much traction, it has been subject to criticism for being too optimistic and unsystematic. In response to this, the new framework, ABCE, offers a more structured approach to mapping community resources. It does however advance previous work by acknowledging the need to identify current levels of community engagement and barriers to engagement, in order to support empowerment, maximise personal capital and address barriers to engagement. Identifying barriers to engagement should not draw ABCE away from its strengths-based focus but instead, provide a platform for person-centred, holistic support to be provided to those in recovery. To support the new framework, a workbook has been developed, offering a practical output that is intended to be used by the individual in recovery alongside a member of staff within a professional service supporting the individual

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

Global parameter search reveals design principles of the mammalian circadian clock

Background: Virtually all living organisms have evolved a circadian (~24 hour) clock that controls physiological and behavioural processes with exquisite precision throughout the day/night cycle. The suprachiasmatic nucleus (SCN), which generates these ~24 h rhythms in mammals, consists of several thousand neurons. Each neuron contains a gene-regulatory network generating molecular oscillations, and the individual neuron oscillations are synchronised by intercellular coupling, presumably via neurotransmitters. Although this basic mechanism is currently accepted and has been recapitulated in mathematical models, several fundamental questions about the design principles of the SCN remain little understood. For example, a remarkable property of the SCN is that the phase of the SCN rhythm resets rapidly after a 'jet lag' type experiment, i.e. when the light/ dark (LD) cycle is abruptly advanced or delayed by several hours. Results: Here, we describe an extensive parameter optimization of a previously constructed simplified model of the SCN in order to further understand its design principles. By examining the top 50 solutions from the parameter optimization, we show that the neurotransmitters' role in generating the molecular circadian rhythms is extremely important. In addition, we show that when a neurotransmitter drives the rhythm of a system of coupled damped oscillators, it exhibits very robust synchronization and is much more easily entrained to light/dark cycles. We were also able to recreate in our simulations the fast rhythm resetting seen after a 'jet lag' type experiment. Conclusion: Our work shows that a careful exploration of parameter space for even an extremely simplified model of the mammalian clock can reveal unexpected behaviours and non-trivial predictions. Our results suggest that the neurotransmitter feedback loop plays a crucial role in the robustness and phase resetting properties of the mammalian clock, even at the single neuron level

IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Visual Dependency and Dizziness after Vestibular Neuritis

Symptomatic recovery after acute vestibular neuritis (VN) is variable, with around 50% of patients reporting long term vestibular symptoms; hence, it is essential to identify factors related to poor clinical outcome. Here we investigated whether excessive reliance on visual input for spatial orientation (visual dependence) was associated with long term vestibular symptoms following acute VN. Twenty-eight patients with VN and 25 normal control subjects were included. Patients were enrolled at least 6 months after acute illness. Recovery status was not a criterion for study entry, allowing recruitment of patients with a full range of persistent symptoms. We measured visual dependence with a laptop-based Rod-and-Disk Test and severity of symptoms with the Dizziness Handicap Inventory (DHI). The third of patients showing the worst clinical outcomes (mean DHI score 36–80) had significantly greater visual dependence than normal subjects (6.35° error vs. 3.39° respectively, p = 0.03). Asymptomatic patients and those with minor residual symptoms did not differ from controls. Visual dependence was associated with high levels of persistent vestibular symptoms after acute VN. Over-reliance on visual information for spatial orientation is one characteristic of poorly recovered vestibular neuritis patients. The finding may be clinically useful given that visual dependence may be modified through rehabilitation desensitization techniques

Are we under-utilizing the talents of primary care personnel? A job analytic examination

BACKGROUND: Primary care staffing decisions are often made unsystematically, potentially leading to increased costs, dissatisfaction, turnover, and reduced quality of care. This article aims to (1) catalogue the domain of primary care tasks, (2) explore the complexity associated with these tasks, and (3) examine how tasks performed by different job titles differ in function and complexity, using Functional Job Analysis to develop a new tool for making evidence-based staffing decisions. METHODS: Seventy-seven primary care personnel from six US Department of Veterans Affairs (VA) Medical Centers, representing six job titles, participated in two-day focus groups to generate 243 unique task statements describing the content of VA primary care. Certified job analysts rated tasks on ten dimensions representing task complexity, skills, autonomy, and error consequence. Two hundred and twenty-four primary care personnel from the same clinics then completed a survey indicating whether they performed each task. Tasks were catalogued using an adaptation of an existing classification scheme; complexity differences were tested via analysis of variance. RESULTS: Objective one: Task statements were categorized into four functions: service delivery (65%), administrative duties (15%), logistic support (9%), and workforce management (11%). Objective two: Consistent with expectations, 80% of tasks received ratings at or below the mid-scale value on all ten scales. Objective three: Service delivery and workforce management tasks received higher ratings on eight of ten scales (multiple functional complexity dimensions, autonomy, human error consequence) than administrative and logistic support tasks. Similarly, tasks performed by more highly trained job titles received higher ratings on six of ten scales than tasks performed by lower trained job titles. Contrary to expectations, the distribution of tasks across functions did not significantly vary by job title. CONCLUSION: Primary care personnel are not being utilized to the extent of their training; most personnel perform many tasks that could reasonably be performed by personnel with less training. Primary care clinics should use evidence-based information to optimize job-person fit, adjusting clinic staff mix and allocation of work across staff to enhance efficiency and effectiveness

A data mining approach for classifying DNA repair genes into ageing-related or non-ageing-related

<p>Abstract</p> <p>Background</p> <p>The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes), for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties.</p> <p>Results</p> <p>The main patterns discovered by the classification methods are as follows: (a) the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b) the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO) annotations; (c) GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d) interaction with the XRCC5 (Ku80) protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e) DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related.</p> <p>Conclusions</p> <p>The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.</p

The Impact of the COVID-19 Pandemic on Racial Disparities in Patients Undergoing Total Shoulder Arthroplasty in the United States

INTRODUCTION: The purpose of this study was to assess racial disparities in total shoulder arthroplasty (TSA) in the US and to determine whether these disparities were affected by the COVID-19 pandemic. METHODS: Centers for Medicare and Medicaid Services (CMS) 100% sample was used to examine primary TSA volume from April-December from 2019-2020. Utilization was assessed for White/Black/Hispanic/Asian populations to determine if COVID-19 affected these groups differently. A regression model adjusted for age/sex/CMS-Hierarchical Condition Categories (HCC) score, dual enrollment (proxy for socioeconomic status), time fixed effects, and Core-based Statistical Area (CBSA) fixed effects was used to study difference across groups. RESULTS: In 2019, TSA volume/1000 beneficiaries was 1.51 for White and 0.57 for non-White, a 2.6-fold difference. In 2020, the rate of TSA in White patients (1.30/1000) was 2.9 times higher than non-White (0.45/1000) during the COVID-19 pandemic (P\u3c0.01). There was an overall 14% decrease in TSA volume/1000 Medicare beneficiaries in 2020; non-White patients had a larger percentage decrease in TSA volume than White (21% vs. 14%, estimated difference;8.7%,p = 0.02). Black patients experienced the most pronounced disparity with estimated difference of 10.1%,p = 0.05, compared with White patients. Similar disparities were observed when categorizing procedures into anatomic and reverse TSA, but not proximal humerus fracture. CONCLUSIONS: During the COVID-19 pandemic, overall TSA utilization decreased by 14% with White patients experiencing a decrease of 14%, and non-White patients experiencing a decrease of 21%. This trend was observed for elective TSA while disparities were less apparent for proximal humerus fracture