Mechanical Property Heterogeneity in Additively Manufactured Nickel Superalloy

Metallic additive manufacturing (AM) techniques do not produce a homogenous structure. Digital image correlation is used to quantify significant variations in mechanical properties in an AM nickel superalloy. Non-uniform properties at multiple length-scales are demonstrated, which could explain the poor mechanical properties common with AM alloys

A new method for quantifying anisotropic martensitic transformation strains accumulated during constrained cooling

Martensitic phase transformations during welding can play a major role in determining the final residual stresses and they can be anisotropic if the transformation occurs under stress. Traditionally, the Satoh test has been used to quantify the response, but it suffers from the fact that the temperature is not uniform along the specimen length, making it difficult to interpret the data. This shortcoming is overcome in our new experimental method using digital image correlation (DIC) to quantify the temperature dependent evolution of the transformation strain locally both parallel and perpendicular to an applied load, in this case for a high-strength low alloy (HSLA) steel and a tough, low transformation temperature weld consumable designed to mitigate tensile weld residual stresses. The method is able to separate the volumetric component of the transformation strain from the deviatoric transformation plasticity component. The volumetric component is shown to be independent of applied load, while the deviatoric component varies approximately linearly with applied load. For the HSLA steel studied here the method also reveals that the transformation start temperature rises under both tensile and compressive loading, confirming previous work. From a weld modelling viewpoint our method provides sufficient information to include the stress dependency of the anisotropic transformation strain in numerical finite element models of the weld process

The τ-plot, a multicomponent 1-D pole figure plot, to quantify the heterogeneity of plastic deformation

An approach is presented that allows multi-scale characterisations of heterogeneous deformation in crystalline materials by employing a range of characterisation techniques including: electron backscatter diffraction, digital image correlation and neutron diffraction powder measurements. The approach will be used to obtain critical information about the variations in parameters that characterise the deformed state in different crystallographic orientation texture components of a sample in a statistically significant way. These parameters include lattice strains, texture evolution, peak broadening, dislocation density, planar faults, phase changes and surface strain. This approach allows verification of models of plastic deformation to provide a more detailed view of plastic deformation heterogeneity at multiple length scales than obtained by other characterisation approaches. The approach demonstrated here is applied to two stainless steel alloys; an alloy that exhibits phase transformation during deformation and an alloy that remains the same phase all through deformation process

‘Neither invisible nor abnormal!’ Exploring the invisibility and pathologisation of LGBT people in the Greek National Health System

This article presents findings from a research study aiming at exploring in-depth experiences of lesbian, gay, bisexual and transgender (LGBT) individuals and communities in the Greek healthcare system. This was the first study of its kind in Greece. Data collected from interviews with LGBT groups and individuals, as well as doctors, suggest that homophobia and transphobia are profound factors of systematic exclusion and restriction from access to good quality healthcare. Our findings suggest that within the healthcare context, LGBT people are routinely invisibilised and/or pathologised. The authors emphasise the urgent need for challenging chronic and institutionalised invisibility experienced by LGBT people as a necessary precondition of social equality and genuine universalism within the Greek Health System

Memetic electromagnetism algorithm for surface reconstruction with rational bivariate Bernstein basis functions

Surface reconstruction is a very important issue with outstanding applications in fields such as medical imaging (computer tomography, magnetic resonance), biomedical engineering (customized prosthesis and medical implants), computer-aided design and manufacturing (reverse engineering for the automotive, aerospace and shipbuilding industries), rapid prototyping (scale models of physical parts from CAD data), computer animation and film industry (motion capture, character modeling), archaeology (digital representation and storage of archaeological sites and assets), virtual/augmented reality, and many others. In this paper we address the surface reconstruction problem by using rational Bézier surfaces. This problem is by far more complex than the case for curves we solved in a previous paper. In addition, we deal with data points subjected to measurement noise and irregular sampling, replicating the usual conditions of real-world applications. Our method is based on a memetic approach combining a powerful metaheuristic method for global optimization (the electromagnetism algorithm) with a local search method. This method is applied to a benchmark of five illustrative examples exhibiting challenging features. Our experimental results show that the method performs very well, and it can recover the underlying shape of surfaces with very good accuracy.This research is kindly supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project #TIN2012-30768, Toho University, and the University of Cantabria. The authors are particularly grateful to the Department of Information Science of Toho University for all the facilities given to carry out this work. We also thank the Editor and the two anonymous reviewers who helped us to improve our paper with several constructive comments and suggestions

Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

BACKGROUND: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. METHODS: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. RESULTS: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95–100) to 100% and specificity from 99% (95% CI 97–100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76–87) to 94% (95% CI 89–98) and specificity ranging from 76% (95% CI 70–82) to 92% (95% CI 88–96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. CONCLUSIONS: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people. Trial Registration NCT04509713 (clinicaltrials.gov)

Influence of country and city images on students’ perception of host universities and their satisfaction with the assigned destination for their exchange programmes

ABSTRACT: This research focuses on the effect that country image, city image and university image has on students’ a priori satisfaction with the assigned destination for their international exchange programme (Bachelor and Master). In particular, this study establishes six hypotheses related to the causal relationships among the different typologies of image and their effects on students’ satisfaction with the assigned destination to study at least one semester in a host university. In order to contrast these hypotheses, a quantitative research was carried out in the Spanish city of Santander (Spain), by obtaining a sample of 245 international students who participated in an exchange programme at the University of Cantabria. The research findings are: (1) students’ satisfaction with the assigned destination is positively influenced by the university image; (2) the university image is positively influenced by the city image; and (3) the city image is positively influenced by the country image

Reduced costs with bisoprolol treatment for heart failure - An economic analysis of the second Cardiac Insufficiency Bisoprolol Study (CIBIS-II)

Background Beta-blockers, used as an adjunctive to diuretics, digoxin and angiotensin converting enzyme inhibitors, improve survival in chronic heart failure. We report a prospectively planned economic analysis of the cost of adjunctive beta-blocker therapy in the second Cardiac Insufficiency BIsoprolol Study (CIBIS II). Methods Resource utilization data (drug therapy, number of hospital admissions, length of hospital stay, ward type) were collected prospectively in all patients in CIBIS . These data were used to determine the additional direct costs incurred, and savings made, with bisoprolol therapy. As well as the cost of the drug, additional costs related to bisoprolol therapy were added to cover the supervision of treatment initiation and titration (four outpatient clinic/office visits). Per them (hospital bed day) costings were carried out for France, Germany and the U.K. Diagnosis related group costings were performed for France and the U.K. Our analyses took the perspective of a third party payer in France and Germany and the National Health Service in the U.K. Results Overall, fewer patients were hospitalized in the bisoprolol group, there were fewer hospital admissions perpatient hospitalized, fewer hospital admissions overall, fewer days spent in hospital and fewer days spent in the most expensive type of ward. As a consequence the cost of care in the bisoprolol group was 5-10% less in all three countries, in the per them analysis, even taking into account the cost of bisoprolol and the extra initiation/up-titration visits. The cost per patient treated in the placebo and bisoprolol groups was FF35 009 vs FF31 762 in France, DM11 563 vs DM10 784 in Germany and pound 4987 vs pound 4722 in the U.K. The diagnosis related group analysis gave similar results. Interpretation Not only did bisoprolol increase survival and reduce hospital admissions in CIBIS II, it also cut the cost of care in so doing. This `win-win' situation of positive health benefits associated with cost savings is Favourable from the point of view of both the patient and health care systems. These findings add further support for the use of beta-blockers in chronic heart failure

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease