Direct Experimental Evidence for Differing Reactivity Alterations of Minerals following Irradiation: The Case of Calcite and Quartz

Concrete, a mixture formed by mixing cement, water, and fine and coarse mineral aggregates is used in the construction of nuclear power plants (NPPs), e.g., to construct the reactor cavity concrete that encases the reactor pressure vessel, etc. In such environments, concrete may be exposed to radiation (e.g., neutrons) emanating from the reactor core. Until recently, concrete has been assumed relatively immune to radiation exposure. Direct evidence acquired on Ar$^+$-ion irradiated calcite and quartz indicates, on the contrary, that, such minerals, which constitute aggregates in concrete, may be significantly altered by irradiation. Specifically, while quartz undergoes disordering of its atomic structure resulting in a near complete lack of periodicity, i.e., similar to glassy silica, calcite only experiences random rotations, and distortions of its carbonate groups. As a result, irradiated quartz shows a reduction in density of around 15%, and an increase in chemical reactivity, described by its dissolution rate, similar to a glassy silica; i.e., an increase of around 3 orders of magnitude. Calcite however, shows little change in dissolution rates - although its density noted to reduce by around 9%. These differences are correlated with the nature of bonds in these minerals, i.e., being dominantly ionic or covalent, and the rigidity of the mineral's atomic network that is characterized by the number of topological constraints (n$_c$) that are imposed on the atoms in the network. The outcomes are discussed within the context of the durability of concrete structural elements formed with calcitic/quartzitic aggregates in nuclear power plants

Braided Rivers and Superconducting Vortex Avalanches

Magnetic vortices intermittently flow through preferred channels when they are forced in or out of a superconductor. We study this behavior using a cellular model, and find that the vortex flow can make braided rivers strikingly similar to aerial photographs of braided fluvial rivers, such as the Brahmaputra. By developing an analysis technique suitable for characterizing a self-affine (multi)fractal, the scaling properties of the braided vortex rivers in the model are compared with those of braided fluvial rivers. We suggest that avalanche dynamics leads to braiding in both cases.Comment: 4 pages, 3 figures. To appear in PR

Control of hyperglycaemia in paediatric intensive care (CHiP): study protocol.

BACKGROUND: There is increasing evidence that tight blood glucose (BG) control improves outcomes in critically ill adults. Children show similar hyperglycaemic responses to surgery or critical illness. However it is not known whether tight control will benefit children given maturational differences and different disease spectrum. METHODS/DESIGN: The study is an randomised open trial with two parallel groups to assess whether, for children undergoing intensive care in the UK aged <or= 16 years who are ventilated, have an arterial line in-situ and are receiving vasoactive support following injury, major surgery or in association with critical illness in whom it is anticipated such treatment will be required to continue for at least 12 hours, tight control will increase the numbers of days alive and free of mechanical ventilation at 30 days, and lead to improvement in a range of complications associated with intensive care treatment and be cost effective. Children in the tight control group will receive insulin by intravenous infusion titrated to maintain BG between 4 and 7.0 mmol/l. Children in the control group will be treated according to a standard current approach to BG management. Children will be followed up to determine vital status and healthcare resources usage between discharge and 12 months post-randomisation. Information regarding overall health status, global neurological outcome, attention and behavioural status will be sought from a subgroup with traumatic brain injury (TBI). A difference of 2 days in the number of ventilator-free days within the first 30 days post-randomisation is considered clinically important. Conservatively assuming a standard deviation of a week across both trial arms, a type I error of 1% (2-sided test), and allowing for non-compliance, a total sample size of 1000 patients would have 90% power to detect this difference. To detect effect differences between cardiac and non-cardiac patients, a target sample size of 1500 is required. An economic evaluation will assess whether the costs of achieving tight BG control are justified by subsequent reductions in hospitalisation costs. DISCUSSION: The relevance of tight glycaemic control in this population needs to be assessed formally before being accepted into standard practice

MX precipitate behavior in an irradiated advanced Fe-9Cr steel: Self-ion irradiation effects on phase stability

Reduced activation ferritic/martensitic (RAFM) steels are the leading candidate structural materials for first-wall and blanket components in fusion reactors. This work is the first in a series to provide a systematic roadmap of MX precipitate stability in RAFM steels under various ion irradiation conditions. Here, the MX-TiC precipitate behavior in an advanced Fe-9Cr RAFM steel is assessed under self-ion irradiation to damage levels ranging from 1 to 100 displacements per atom (dpa) at temperatures ranging from 300-600{\deg}C to isolate the effects of temperature and damage level on precipitate stability. The pre-existing MX-TiC precipitates are shown to exhibit temperature-dominated responses, including coarsening above 400{\deg}C at damage levels of 15 dpa, while damage levels studied at 50 dpa and higher showed dissolution across all temperature ranges studied. The effects of ballistic dissolution and diffusion on precipitate behavior are outlined as a function of precipitate characteristics (number density, size, and 25 volume fraction) and irradiation parameters with the use of the recoil resolution model of precipitate stability. This work provides critical insights into MX-TiC stability to high dose in-order to further optimize advanced steels with improved radiation resistance.Comment: 32 pages, 19 pages supplementa

Materials Swelling Revealed Through Automated Semantic Segmentation of Cavities in Electron Microscopy Images

Accurately quantifying swelling of alloys that have undergone irradiation is essential for understanding alloy performance in a nuclear reactor and critical for the safe and reliable operation of reactor facilities. However, typical practice is for radiation-induced defects in electron microscopy images of alloys to be manually quantified by domain-expert researchers. Here, we employ an end-to-end deep learning approach using the Mask Regional Convolutional Neural Network (Mask R-CNN) model to detect and quantify nanoscale cavities in irradiated alloys. We have assembled the largest database of labeled cavity images to date, which includes 400 images, >34k discrete cavities, and numerous alloy compositions and irradiation conditions. We have evaluated both statistical (precision, recall, and F1 scores) and materials property-centric (cavity size, density, and swelling) metrics of model performance, and performed in-depth analysis of materials swelling assessments. We find our model gives assessments of material swelling with an average (standard deviation) swelling mean absolute error based on random leave-out cross-validation of 0.30 (0.03) percent swelling. This result demonstrates our approach can accurately provide swelling metrics on a per-image and per-condition basis, which can provide helpful insight into material design (e.g., alloy refinement) and impact of service conditions (e.g., temperature, irradiation dose) on swelling. Finally, we find there are cases of test images with poor statistical metrics, but small errors in swelling, pointing to the need for moving beyond traditional classification-based metrics to evaluate object detection models in the context of materials domain applications

Assessment of a carbon dioxide laser for the measurement of thermal nociceptive thresholds following intramuscular administration of analgesic drugs in pain-free female cats

Objective: To assess the potential for using a thermal carbon dioxide (CO2) laser to 8 assess anti-nociception in pain-free cats. Animals: Sixty healthy adult female cats with a mean weight (± SD) of 3.3 k g (± 0. 6 11 kg). Methods: This is a prospective, blinded and randomised study. Cats were systematically allocated to one of six treatments 1) saline 0.2 ml/cat; 2) morphine 0.5 mg/kg; 3) buprenorphine 20 μg/kg; 4) medetomidine 2 μg/kg; 5) tramadol 2mg/kg; 6) ketoprofen 2 mg/kg. Latency to respond to thermal stimulation was assessed prior to intramuscular injection and at 6 time periods following injection (15-30; 30-45; 45- 18 60; 60-75; 90-105; 120-135 min). Thermal thresholds were assessed using time to respond behaviourally to stimulation with a 500 mW CO2 laser with maximum latency to respond set at 60 seconds. Differences in response latency for each treatment across the duration of the experiment were assessed using a Friedman's test. Differences between treatments at any given time were assessed using an independent Kruskal-Wallis test. Where significant effects were identified, pair-wise comparisons were conducted at 30-45, 60-75 and 120-135 min to further explain the direction of the effect. Results: Cats treated with morphine (χ2 = 12.90; df = 6; P = 0.045) and tramadol (χ2 = 20.28; df = 6; P = 0.002) showed significant increases in latency to respond over the duration of the test period. However, subsequent pairwise comparisons indicated that latencies at specific time points were only significantly different (P < 0.05) for tramadol at 60-75 and 90-105 min after administration. No significant pairwise comparisons were found within the morphine treatment group. Injection of saline, ketoprofen, medetomidine or buprenorphine showed no significant effect on latency to respond. Conclusions: This project further validates the CO 2 laser technique for use in cats. It can be used for assessment of thermal nociceptive thresholds in pain-free cats after analgesic administration and shows some promise in differentiating amongst analgesic treatments. It may provide a simpler alternative to existing systems although further exploration is required both in terms of its sensitivity and comparative utility (i.e. relative to other thermal threshold systems). Future experiments should seek to quantify the effects of skin temperature and sedation on latency to respond. Given that this technique was found to cause minor skin blistering in individuals that reached the 60 s exposure limit, a cut off time of <45 s is recommended

Accelerating Domain-Aware Electron Microscopy Analysis Using Deep Learning Models with Synthetic Data and Image-Wide Confidence Scoring

The integration of machine learning (ML) models enhances the efficiency, affordability, and reliability of feature detection in microscopy, yet their development and applicability are hindered by the dependency on scarce and often flawed manually labeled datasets and a lack of domain awareness. We addressed these challenges by creating a physics-based synthetic image and data generator, resulting in a machine learning model that achieves comparable precision (0.86), recall (0.63), F1 scores (0.71), and engineering property predictions (R2=0.82) to a model trained on human-labeled data. We enhanced both models by using feature prediction confidence scores to derive an image-wide confidence metric, enabling simple thresholding to eliminate ambiguous and out-of-domain images resulting in performance boosts of 5-30% with a filtering-out rate of 25%. Our study demonstrates that synthetic data can eliminate human reliance in ML and provides a means for domain awareness in cases where many feature detections per image are needed

Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies

Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low–BMI cases are larger than those estimated from high–BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×$10^{−9}$). The improvement varied across diseases with a 16% median increase in χ2 test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci

Functional similarities between pigeon \u27milk\u27 and mammalian milk : induction of immune gene expression and modification of the microbiota

Pigeon &lsquo;milk&rsquo; and mammalian milk have functional similarities in terms of nutritional benefit and delivery of immunoglobulins to the young. Mammalian milk has been clearly shown to aid in the development of the immune system and microbiota of the young, but similar effects have not yet been attributed to pigeon &lsquo;milk&rsquo;. Therefore, using a chicken model, we investigated the effect of pigeon &lsquo;milk&rsquo; on immune gene expression in the Gut Associated Lymphoid Tissue (GALT) and on the composition of the caecal microbiota. Chickens fed pigeon &lsquo;milk&rsquo; had a faster rate of growth and a better feed conversion ratio than control chickens. There was significantly enhanced expression of immune-related gene pathways and interferon-stimulated genes in the GALT of pigeon &lsquo;milk&rsquo;-fed chickens. These pathways include the innate immune response, regulation of cytokine production and regulation of B cell activation and proliferation. The caecal microbiota of pigeon &lsquo;milk&rsquo;-fed chickens was significantly more diverse than control chickens, and appears to be affected by prebiotics in pigeon &lsquo;milk&rsquo;, as well as being directly seeded by bacteria present in pigeon &lsquo;milk&rsquo;. Our results demonstrate that pigeon &lsquo;milk&rsquo; has further modes of action which make it functionally similar to mammalian milk. We hypothesise that pigeon &lsquo;lactation&rsquo; and mammalian lactation evolved independently but resulted in similarly functional products