Electrolyte jet machining for surface texturing of Inconel 718

Electrolyte jet machining is an emerging non-conventional machining process which is capable of selectively applying multi-scale surface textures. Surfaces processed in this way do not suffer from thermal damage and hence this technique is highly suited to finishing procedures in high value manufacturing across the aerospace and biomedical sectors. Furthermore, input variables can be modified dynamically to create functional graduation across component surfaces. In this study, the development and design of a custom-built EJM system is described, and the capability of the EJM platform to machine and create surface textures in Inconel 718, a widely used nickel based super alloy, is investigated. Through control of machine path programming and parameter variation, multi-scale surface textures are created which have the potential to enhance bonding with subsequent coating layers and also provide fluid dynamic advantage

Spheroidisation of metal powder by pulsed electron beam irradiation

A new powder spheroidisation process has been demonstrated using a large-area, pulsed electron beam technique. This was used to dramatically improve the surface morphology of Stellite 6 metal powder. Powder surface asperities up to 20 μm size can be eliminated by melting and incorporation into the near-surface of the particle. Surface finish is significantly improved. Agitation and rotation of particles due to a beam-induced stress wave enables the irradiation of multiples sides of particles, resulting in uniformly smoothed particles after sufficient pulses. Elemental analysis revealed no measurable contamination as a result of the process. Transmission electron microscopy showed a dense layer is produced within a zone up to 3 μm beneath the surface, with a substantially reduced grain size from ca. 2 μm diameter in the bulk to ca. 40 nm. Elemental homogenisation also was accompanied by grain refinement. The irradiated Stellite 6 showed a reduced basic flowability energy (583 mJ compared to 627 mJ for the untreated), explained by reduced particle-particle cohesion and interlocking, and an increased conditioned bulk density of 4.57 g/ml compared to 4.33 g/ml due to satellite/asperity reduction

Three-dimensional mapping of soil chemical characteristics at micrometric scale by combining 2D SEM-EDX data and 3D X-ray CT images

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution

A study of psychiatrists’ concepts of mental illness

Background: There are multiple models of mental illness that inform professional and lay understanding. Few studies have formally investigated psychiatrists' attitudes. We aimed to measure how a group of trainee psychiatrists understand familiar mental illnesses in terms of propositions drawn from different models. Method: We used a questionnaire study of a sample of trainees from South London and Maudsley National Health Service (NHS) Foundation Trust designed to assess attitudes across eight models of mental illness (e.g. biological, psychodynamic) and four psychiatric disorders. Methods for analysing repeated measures and a principal components analysis (PCA) were used. Results: No one model was endorsed by all respondents. Model endorsement varied with disorder. Attitudes to schizophrenia were expressed with the greatest conviction across models. Overall, the ‘biological’ model was the most strongly endorsed. The first three components of the PCA (interpreted as dimensions around which psychiatrists, as a group, understand mental illness) accounted for 56% of the variance. Each main component was classified in terms of its distinctive combination of statements from different models: PC1 33% biological versus non-biological; PC2 12% ‘eclectic’ (combining biological, behavioural, cognitive and spiritual models); and PC3 10% psychodynamic versus sociological. Conclusions: Trainee psychiatrists are most committed to the biological model for schizophrenia, but in general are not exclusively committed to any one model. As a group, they organize their attitudes towards mental illness in terms of a biological/non-biological contrast, an ‘eclectic’ view and a psychodynamic/sociological contrast. Better understanding of how professional group membership influences attitudes may facilitate better multidisciplinary working

Police, public, and offender perceptions of body-worn video: a single jurisdictional multiple-perspective analysis

Objectives. Police, public, and offender survey responses from a single jurisdiction give a multiple-perspective insight into the use of body-worn video (BWV) cameras by police. Methods. Police attitudinal data was collected from before (n = 190), during (n = 139), and at the conclusion (n = 221) of a BWV implementation trial. Public attitudes were collected at the conclusion of the BWV implementation trial via online survey (n = 995 respondents) and intercept survey (n = 428 respondents). Offender attitudes (n = 302) were collected in police custody over a 6-month period immediately preceding the BWV trial. Results. The extent to which police felt BWV influenced their behavior tempered during the trial. All three perspectives were supportive of the use of BWV. The public who had encountered BWV-wearing officers and the offender sample indicated limited belief that BWV would reduce bad behavior. There was also clear contention about the policy and practice decisions around recording. Conclusions. These findings have significance for BWV trials, commenting on the importance of (a) collecting police attitudes at multiple points, (b) separating the attitudes of public who did encounter police wearing BWV, and (c) data collection and policy for evaluation outcomes

The structure of HI in galactic disks: Simulations vs observations

We generate synthetic HI Galactic plane surveys from spiral galaxy simulations which include stellar feedback processes. Compared to a model without feedback we find an increased scale height of HI emission (in better agreement with observations) and more realistic spatial structure (including supernova blown bubbles). The synthetic data show HI self-absorption with a morphology similar to that seen in observations. The density and temperature of the material responsible for HI self-absorption is consistent with observationally determined values, and is found to be only weakly dependent on absorption strength and star formation efficiency.Comment: 12 pages, 7 figures. Accepted for publication in MNRA

Development of childhood asthma prediction models using machine learning approaches

Background: Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models. This study applied ML approaches to predict school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model). Methods: Clinical and environmental exposure data was collected from children enrolled in the Isle of Wight Birth Cohort (N = 1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified an optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art ML classification algorithms were used to develop prognostic models. Training was performed by applying fivefold cross-validation, imputation, and resampling. Predictive performance was evaluated on the test set. Models were further externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort. Results: RFE identified eight and twelve predictors for the CAPE and CAPP models, respectively. Support Vector Machine (SVM) algorithms provided the best performance for both the CAPE (area under the receiver operating characteristic curve, AUC = 0.71) and CAPP (AUC = 0.82) models. Both models demonstrated good generalisability in MAAS (CAPE 8-year = 0.71, 11-year = 0.71, CAPP 8-year = 0.83, 11-year = 0.79) and excellent sensitivity to predict a subgroup of persistent wheezers. Conclusion: Using ML approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma and predict persistent wheeze.</p

Prediction of 7-year psychopathology from mother-infant joint attention behaviours: a nested case–control study

&lt;br&gt;Background: To investigate whether later diagnosis of psychiatric disorder can be predicted from analysis of mother-infant joint attention (JA) behaviours in social-communicative interaction at 12 months.&lt;/br&gt; &lt;br&gt;Method: Using data from a large contemporary birth cohort, we examined 159 videos of a mother-infant interaction for joint attention behaviour when children were aged one year, sampled from within the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Fifty-three of the videos involved infants who were later considered to have a psychiatric disorder at seven years and 106 were same aged controls. Psychopathologies included in the case group were disruptive behaviour disorders, oppositional-conduct disorder, attention-deficit/hyperactivity disorder, pervasive development disorder, anxiety and depressive disorders. Psychiatric diagnoses were obtained using the Development and Wellbeing Assessment when the children were seven years old.&lt;/br&gt; &lt;br&gt;Results: None of the three JA behaviours (shared look rate, shared attention rate and shared attention intensity) showed a significant association with the primary outcome of case–control status. Only shared look rate predicted any of the exploratory sub-diagnosis outcomes and was found to be positively associated with later oppositional-conduct disorders (OR [95% CI]: 1.5 [1.0, 2.3]; p = 0.041).&lt;/br&gt;&lt;br&gt;Conclusions: JA behaviours did not, in general, predict later psychopathology. However, shared look was positively associated with later oppositional-conduct disorders. This suggests that some features of JA may be early markers of later psychopathology. Further investigation will be required to determine whether any JA behaviours can be used to screen for families in need of intervention.&lt;/br&gt

Reduced LIMK2 expression in colorectal cancer reflects its role in limiting stem cell proliferation

Objective: Colorectal cancer (CRC) is a major contributor to cancer mortality and morbidity. LIM kinase 2 (LIMK2) promotes tumour cell invasion and metastasis. The objectives of this study were to determine how LIMK2 expression is associated with CRC progression and patient outcome, and to use genetically modified Drosophila and mice to determine how LIMK2 deletion affects gastrointestinal stem cell regulation and tumour development.&lt;p&gt;&lt;/p&gt; Design: LIMK2 expression and activity were measured by immunostaining tumours from CRC-prone mice, human CRC cell lines and 650 human tumours. LIMK knockdown in Drosophila or Limk2 deletion in mice allowed for assessment of their contributions to gastrointestinal stem cell homeostasis and tumour development.&lt;p&gt;&lt;/p&gt; Results: LIMK2 expression was reduced in intestinal tumours of cancer-prone mice, as well as in human CRC cell lines and tumours. Reduced LIMK2 expression and substrate phosphorylation were associated with shorter patient survival. Genetic analysis in Drosophila midgut and intestinal epithelial cells isolated from genetically modified mice revealed a conserved role for LIMK2 in constraining gastrointestinal stem cell proliferation. Limk2 deletion increased colon tumour size in a colitis-associated colorectal mouse cancer model.&lt;p&gt;&lt;/p&gt; Conclusions: This study revealed that LIMK2 expression and activity progressively decrease with advancing stage, and supports the hypothesis that there is selective pressure for reduced LIMK2 expression in CRC to relieve negative constraints imposed upon gastrointestinal stem cells.&lt;p&gt;&lt;/p&gt

Acute skin toxicity associated with a 1-week schedule of whole breast radiotherapy compared with a standard 3-week regimen delivered in the UK FAST-Forward Trial

BACKGROUND AND PURPOSE: FAST-Forward is a phase 3 clinical trial testing a 1-week course of whole breast radiotherapy against the UK standard 3-week regimen after primary surgery for early breast cancer. Two acute skin toxicity substudies were undertaken to test the safety of the test schedules with respect to early skin reactions. MATERIAL AND METHODS: Patients were randomly allocated to 40Gy/15 fractions (F)/3-weeks, 27Gy/5F/1-week or 26Gy/5F/1-week. Acute breast skin reactions were graded using RTOG (first substudy) and CTCAE criteria v4.03 (second substudy) weekly during treatment and for 4weeks after treatment ended. Primary endpoint was the proportion of patients within each treatment group with grade ⩾3 toxicity (RTOG and CTCAE, respectively) at any time from the start of radiotherapy to 4weeks after completion. RESULTS: 190 and 162 patients were recruited. In the first substudy, evaluable patients with grade 3 RTOG toxicity were: 40Gy/15F 6/44 (13.6%); 27Gy/5F 5/51 (9.8%); 26Gy/5F 3/52 (5.8%). In the second substudy, evaluable patients with grade 3 CTCAE toxicity were: 40Gy/15F 0/43; 27Gy/5F 1/41 (2.4%); 26Gy/5F 0/53. CONCLUSIONS: Acute breast skin reactions with two 1-week schedules of whole breast radiotherapy under test in FAST-Forward were mild