50 research outputs found
MAGIC and Fermi-LAT gamma-ray results on unassociated HAWC sources
The HAWC Collaboration released the 2HWC catalogue of TeV sources, in which 19 show no association with any known high-energy (HE; E greater than or similar to 10 GeV) or very-high-energy (VHE; E greater than or similar to 300 GeV) sources. This catalogue motivated follow-up studies by both the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) and Fermi-LAT (Large Area Telescope) observatories with the aim of investigating gamma-ray emission over a broad energy band. In this paper, we report the results from the first joint work between High Altitude Water Cherenkov (HAWC), MAGIC, and Fermi-LAT on three unassociated HAWC sources: 2HWC J2006+341, 2HWC J1907+084*, and 2HWC J1852+013*. Although no significant detection was found in the HE and VHE regimes, this investigation shows that a minimum 1 degrees extension (at 95 per cent confidence level) and harder spectrum in the GeV than the one extrapolated from HAWC results are required in the case of 2HWC J1852+013*, whilst a simply minimum extension of 0.16 degrees (at 95 per cent confidence level) can already explain the scenario proposed by HAWC for the remaining sources. Moreover, the hypothesis that these sources are pulsar wind nebulae is also investigated in detail
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Solid breeder blanket option for the ITER conceptual design
A solid-breeder water-cooled blanket option was developed for ITER based on a multilayer configuration. The blanket uses beryllium for neutron multiplication and lithium oxide for tritium breeding. The material forms are sintered products for both material with 0.8 density factor. The lithium-6 enrichment is 90%. This blanket has the capability to accommodate a factor of two change in the neutron wall loading without violating the different design guidelines. The design philosophy adopted for the blanket is to produce the necessary tritium required for the ITER operation and to operate at power reactor conditions as much as possible. At the same time, the reliability and the safety aspects of the blanket are enhanced by the use of a low-pressure coolant and the separation of the tritium purge lines from the coolant system. The blanket modules are made by hot vacuum forming and diffusion bonding a double wall structure with integral cooling channels. The different aspects of the blanket design including tritium breeding, nuclear heat deposition, activation analyses, thermal-hydraulics, tritium inventory, structural analyses, and water coolant conditions are summarized in this paper. 12 refs., 2 figs., 1 tab
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ITER blanket and shield studies for high aspect ratio design option
The attractiveness of the high aspect ratio design (HARD) option for ITER has motivated a study to assess the blanket and shield design performance for this configuration relative to the ITER reference design. The blanket and shield have been configured to take an advantage of the HARD option. The layered solid breeder blanket concept with water-coolant and steel-structure and the water-steel shield have been used. The changes in the neutron wall loading distribution, the mechanical design, the net tritium breeding ratio, the total tritium inventory, and the nuclear heating profiles are evaluated. The tradeoff between the net tritium breeding ratio, and the fuel operating cost is analyzed. The mechanical design and the structural interaction between the first wall and the blanket is studied. 4 refs., 3 figs., 5 tabs
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
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US solid breeder blanket design for ITER
The US blanket design activity has focused on the developments and the analyses of a solid breeder blanket concept for ITER. The main function of this blanket is to produce the necessary tritium required for the ITER operation and the test program. Safety, power reactor relevance, low tritium inventory, and design flexibility are the main reasons for the blanket selection. The blanket is designed to operate satisfactorily in the physics and the technology phases of ITER without the need for hardware changes. Mechanical simplicity, predictability, performance, minimum cost, and minimum R D requirements are the other criteria used to guide the design process. The design aspects of the blanket are summarized in this paper. 2 refs., 7 figs., 3 tabs