96 research outputs found

    High efficiency GaAs-Ge tandem solar cells grown by MOCVD

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    High conversion efficiency and low weight are obviously desirable for solar cells intended for space applications. One promising structure is GaAs on Ge. The advantages of using Ge wafers as substrates include the following: they offer high efficiency by forming a two-junction tandem cell; low weight combined with superior strength allows usage of thin (3 mil) wafers; and they are a good substrate for GaAs, being lattice matched, thermal expansion matched, and available as large-area wafers

    PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques

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    Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single-valued population-based lung LAC, and better estimation is needed to improve quantification. Given the under-appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single-valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission-based schemes. Potential strategies for future developments are also presented

    Predicting radioactive waste glass dissolution with machine learning

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    The vitrification of high-level nuclear waste within borosilicate glass and its disposition within a multi-barrier repository deep underground is accepted as the best form of disposal. Here, the ability of machine learning to predict both static and dynamic glass leaching behavior is analysed using large-scale unstructured multi-source data, covering a diverse range of experimental conditions and glass compositions. Machine learning can accurately predict leaching behavior, predict missing data, and time forecast. Accuracy depends upon the type of learning algorithm, model input variables, and diversity or size of the underlying dataset. For static leaching, the bagged random forest method predicts well, even when either pH or glass composition are neglected as input variables, additionally showing potential in predicting independent glass dissolution data. For dynamic leaching, accuracy improves if replacing final pH with a species dissolution rate as an input variable, although results show no preferred output species (Si, Na, or Al)

    Assessing static glass leaching predictions from large datasets using machine learning

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    Radioactive waste vitrified within glass is planned to be ultimately disposed of within a geological disposal facility. This study has applied machine learning to predict static glass leaching using an international experimental database of approximately 450 glasses to train/test various algorithms. Machine learning can accurately predict B, Li, Na, and Si releases for this complex database with Tree-based algorithms (notably ‘BaggingRegressor’ and ‘RandomForestRegressor’ in Python). This is provided that leaching experiment results, including elemental releases, are incorporated within the algorithm training variables, given that this study finds inaccurate prediction solely using initial test parameters as features. The trained algorithms underwent additional testing using an external database with prediction showing worse performance, likely due to substantial MgO and Na2O pristine glass oxide compositional variations across databases, with B releases generally being overestimated and Na underestimated. The use of molar oxide content performed significantly better than weight-fraction oxide for learning

    Assessing the effect of radioactive waste glass dissolution on early-stage radionuclide migration using simplified geological repository Monte Carlo transport models

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    The vitrification of radioactive waste within glass and subsequent disposal within a geological disposal facility (GDF) requires a comprehensive understanding of the effect of glass dissolution on GDF performance. This paper aims to analyse the effect of both high-level and intermediate-level waste (HLW and ILW) glass dissolution source terms on radionuclide release into the geosphere just above the disposal vault (the ‘crown’). Radionuclide migration was simulated in GoldSim for HLW in either granite or clay host rocks with a bentonite buffer using carbon steel or copper canisters, whereas ILW simulations considered either granite or clay host rocks, in either bentonite buffer or cement backfill, using concrete or cast-iron canisters. Glass dissolution source terms were varied by coupling GoldSim and MATLAB to modify the initial, residual, and resumption dissolution rates of the glass or by applying the analytical GRAAL model to glass dissolution. HLW glass results indicate no preference of granite over clay host rocks for a given canister type but that a copper canister is preferable to steel. ILW results suggest that a granite–bentonite–cast-iron environment yields lowest crown activities with cast-iron preferable to concrete as the canister, bentonite preferable to cement as the buffer/backfill, and granite preferable to clay as the host rock. Varying glass dissolution source terms (initial, residual, and resumption dissolution rates) had an understood effect on radionuclide migration, although changes were arguably insignificant considering peak crown activity for both HLW and ILW

    Does the availability of positron emission tomography modify diagnostic strategies for solitary pulmonary nodules? An observational study in France

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    International audienceBACKGROUND: Previous studies showed that at the individual level, positron emission tomography (PET) has some benefits for patients and physicians in terms of cancer management and staging. We aimed to describe the benefits of (PET) in the management of solitary pulmonary nodules (SPNs) in a population level, in terms of the number of diagnostic and invasive tests performed, time to diagnosis and factors determining PET utilization. METHODS: In an observational study, we examined reports of computed tomography (CT) performed and mentioning "spherical lesion", "nodule" or synonymous terms. We found 11,515 reports in a before-PET period, 2002-2003, and 20,075 in an after-PET period, 2004-2005. Patients were followed through their physician, who was responsible for diagnostic management. RESULTS: We had complete data for 112 patients (73.7%) with new cases of SPN in the before-PET period and 250 (81.4%) in the after-PET period. Patients did not differ in mean age (64.9 vs. 64.8 years). The before-PET patients underwent a mean of 4 tests as compared with 3 tests for the after-PET patients (p = 0.08). Patients in the before-PET period had to wait 41.4 days, on average, before receiving a diagnosis as compared with 24.0 days, on average, for patients in the after-PET period who did not undergo PET (p < 0.001). In the after-PET period, 11% of patients underwent PET during the diagnostic process. A spiculated nodule was more likely to determine prescription for PET (p < 0.001). Multivariate analysis revealed that patients in both periods underwent fewer tests when PET was prescribed by general practitioners (p < 0.001) and if the nodule was not spiculated (p < 0.001). The proportion of unnecessary invasive approaches prescribed (47% vs. 49%) did not differ between the groups. CONCLUSION: In our study, 1 year after the availability of PET, the technology was not the first choice for diagnostic management of SPN. Even though we observed a tendency for reduced number of tests and mean time to diagnosis with PET, these phenomena did not fully relate to PET availability in health communities. In addition, the availability of PET in the management of SPN diagnosis did not reduce the overall rate of unnecessary invasive approaches

    Development of an inflammatory bowel disease (IBD) Patient‐Reported Experience Measure (PREM): A patient‐led consensus work and ‘think aloud’ study for a quality improvement programme

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    Background Patient-Reported Experience Measures (PREMs) are key in improving healthcare quality, but no PREM exists for inflammatory bowel disease (IBD). This study aimed to co-produce a PREM with IBD service users for IBD service evaluation and quality improvement programme. Methods A pool of 75 items was drawn from published survey instruments covering interactions with services and aspects of living with IBD. In Stage 1, during two workshops, eight expert service users reduced candidate items through a ranked-choice voting exercise and suggested further items. During Stage 2, 18 previously uninvolved people with IBD assessed the face and content validity of the candidate items in ‘Think Aloud’ interviews. During two final workshops (Stage 3), the expert service users removed, modified and added items based on the interview findings to produce a final version of the PREM. Results Stage 1 generated a draft working PREM mapped to the following four domains: Patient-Centred Care; Quality; Accessibility; Communication and Involvement. The PREM included a set of nine items created by the expert group which shifted the emphasis from ‘self-management’ to ‘living with IBD’. Stage 2 interviews showed that comprehension of the PREM was very good, although there were concerns about the wording, IBD-relevance and ambiguity of some items. During the final two workshops in Stage 3, the expert service users removed 7 items, modified 15 items and added seven new ones based on the interview findings, resulting in a 38-item PREM. Conclusions This study demonstrates how extensive service user involvement can inform PREM development. Patient or Public Contribution Patients were involved as active members of the research team and as research participants to co-produce and validate a PREM for IBD services. In Stage 1, eight expert service users (‘the expert group’) reduced candidate items for the PREM through a voting exercise and suggested new items. During Stage 2, 18 previously uninvolved people with IBD (the ‘think aloud’ participants) assessed the validity of the candidate items in ‘Think Aloud’ interviews as research participants. In Stage 3, the expert group removed, changed and added items based on the interview findings to produce a final version of the 38-item PREM. This study shows how service user involvement can meaningfully inform PREM development
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