Rapidly Solidified Sm–Co–V Nanocomposite Permanent Magnets

Alloys around the Sm–Co eutectic composition provide an opportunity to form two-phase nanocomposite permanent magnets consisting of nanoscale Co fibers embedded in Sm2Co17.While ternary alloying elements may refine the scale of the structure, they may also disrupt the eutectic growth and lead to the formation of primary Co. Thus, microstructural selection maps were constructed for conventionally solidified Sm–Co–V alloys. It was found that V additions enlarged the primary Sm2Co17-forming region and, at (Sm0.09Co0.91)97 V3, resulted in a eutectic structure. Upon rapid solidification, this alloy was determined to have a coercivity of 5 kOe with a high remanent ratio. However, the V addition reduced the magnetization, which limited the energy product to 4.3 MG Oe. The rapidly solidified structure consisted of primary SmCo7 dendrites along with an intergranular Co region, suggesting that eutectic structure formation is skewed by underlying metastable phase relationships

Rapidly Solidified Sm–Co–V Nanocomposite Permanent Magnets

Alloys around the Sm–Co eutectic composition provide an opportunity to form two-phase nanocomposite permanent magnets consisting of nanoscale Co fibers embedded in Sm2Co17.While ternary alloying elements may refine the scale of the structure, they may also disrupt the eutectic growth and lead to the formation of primary Co. Thus, microstructural selection maps were constructed for conventionally solidified Sm–Co–V alloys. It was found that V additions enlarged the primary Sm2Co17-forming region and, at (Sm0.09Co0.91)97 V3, resulted in a eutectic structure. Upon rapid solidification, this alloy was determined to have a coercivity of 5 kOe with a high remanent ratio. However, the V addition reduced the magnetization, which limited the energy product to 4.3 MG Oe. The rapidly solidified structure consisted of primary SmCo7 dendrites along with an intergranular Co region, suggesting that eutectic structure formation is skewed by underlying metastable phase relationships

Supporting Roma Voices

The Supporting Roma Voice project has aimed to address emerging knowledge gaps in the way in which the inclusion of migrant Roma in the UK is being addressed. Specifically, research by Brown, Scullion and Martin (2013) identified a demand from public authorities for social inclusion work directed towards migrant Roma communities to be developed and delivered by members of migrant Roma communities themselves. However, what was also lacking was an adequate evidence base about the settlement of migrant Roma in the UK and the varied experiences associated with this transition. This report explores the views and experiences of a large number of Roma people who have migrated to the UK in recent years. The research was designed in partnership with a team of researchers from the Roma communities and undertaken wholly by these researchers. The research study aimed to explore the following issues: - The settlement and integration experiences of Roma migrants living in areas across the UK. - The specific areas of community relations, housing, education, employment and social welfare and their role in settlement in the UK. - The provision of knowledge that would enable local authorities and other services to enhance the settlement experience of Roma migrants now and in the future. A total of 159 people participated in 19 focus groups, which took place in the following locations: Glasgow, Leicester, London, Oldham, Salford and Sheffield. It should be noted that owing to the heterogeneity of the Roma population this report does not attempt to make definitive statements about the situation and views of all Roma migrants in the UK. This report was co-authored by members of the academic team in partnership with community researchers. The fieldwork was undertaken in early 2016 prior to the UK’s referendum on staying in the European Union

Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach

BACKGROUND: Screening for Barrett's oesophagus relies on endoscopy, which is invasive and few who undergo the procedure are found to have the condition. We aimed to use machine learning techniques to develop and externally validate a simple risk prediction panel to screen individuals for Barrett's oesophagus. METHODS: In this prospective study, machine learning risk prediction in Barrett's oesophagus (MARK-BE), we used data from two case-control studies, BEST2 and BOOST, to compile training and validation datasets. From the BEST2 study, we analysed questionnaires from 1299 patients, of whom 880 (67·7%) had Barrett's oesophagus, including 40 with invasive oesophageal adenocarcinoma, and 419 (32·3%) were controls. We randomly split (6:4) the cohort using a computer algorithm into a training dataset of 776 patients and a testing dataset of 523 patients. We compiled an external validation cohort from the BOOST study, which included 398 patients, comprising 198 patients with Barrett's oesophagus (23 with oesophageal adenocarcinoma) and 200 controls. We identified independently important diagnostic features of Barrett's oesophagus using the machine learning techniques information gain and correlation-based feature selection. We assessed multiple classification tools to create a multivariable risk prediction model. Internal validation of the model using the BEST2 testing dataset was followed by external validation using the BOOST external validation dataset. From these data we created a prediction panel to identify at-risk individuals. FINDINGS: The BEST2 study included 40 diagnostic features. Of these, 19 added information gain but after correlation-based feature selection only eight showed independent diagnostic value including age, sex, cigarette smoking, waist circumference, frequency of stomach pain, duration of heartburn and acidic taste, and taking antireflux medication, of which all were associated with increased risk of Barrett's oesophagus, except frequency of stomach pain, with was inversely associated in a case-control population. Logistic regression offered the highest prediction quality with an area under the receiver-operator curve (AUC) of 0·87 (95% CI 0·84–0·90; sensitivity set at 90%; specificity of 68%). In the testing dataset, AUC was 0·86 (0·83–0·89; sensitivity set at 90%; specificity of 65%). In the external validation dataset, the AUC was 0·81 (0·74–0·84; sensitivity set at 90%; specificity of 58%). INTERPRETATION: Our diagnostic model offers valid predictions of diagnosis of Barrett's oesophagus in patients with symptomatic gastro-oesophageal reflux disease, assisting in identifying who should go forward to invasive confirmatory testing. Our predictive panel suggests that overweight men who have been taking antireflux medication for a long time might merit particular consideration for further testing. Our risk prediction panel is quick and simple to administer but will need further calibration and validation in a prospective study in primary care. FUNDING: Charles Wolfson Charitable Trust and Guts UK

Core outcome set for surgical trials in gastric cancer (GASTROS study): international patient and healthcare professional consensus

Background: Surgery is the primary treatment that can offer potential cure for gastric cancer, but is associated with significant risks. Identifying optimal surgical approaches should be based on comparing outcomes from well designed trials. Currently, trials report different outcomes, making synthesis of evidence difficult. To address this, the aim of this study was to develop a core outcome set (COS)-a standardized group of outcomes important to key international stakeholders-that should be reported by future trials in this field.Methods: Stage 1 of the study involved identifying potentially important outcomes from previous trials and a series of patient interviews. Stage 2 involved patients and healthcare professionals prioritizing outcomes using a multilanguage international Delphi survey that informed an international consensus meeting at which the COS was finalized.Results: Some 498 outcomes were identified from previously reported trials and patient interviews, and rationalized into 56 items presented in the Delphi survey. A total of 952 patients, surgeons, and nurses enrolled in round 1 of the survey, and 662 (70 per cent) completed round 2. Following the consensus meeting, eight outcomes were included in the COS: disease-free survival, disease-specific survival, surgery-related death, recurrence, completeness of tumour removal, overall quality of life, nutritional effects, and 'serious' adverse events.Conclusion: A COS for surgical trials in gastric cancer has been developed with international patients and healthcare professionals. This is a minimum set of outcomes that is recommended to be used in all future trials in this field to improve trial design and synthesis of evidence