Test Station for a 30 m long Superconducting Link

The Large Hadron Collider (LHC) requires distribution of high electrical currents in the limited space of LHC tunnel. Four superconducting links of about 76 m length and one of 510 m will be installed in the tunnel to carry 6 kA and 600 A. For validation of the longest link a test station was designed which is presently under construction. The design will permit the test station to be adapted for other links and/or cables as well. It will operate either in pool boiling mode, in order to measure thermal loads, or in forced super-critical helium flow mode to simulate real operation. Inlet pressure is 1.2 bar to 3 bar. Inlet temperature is adjustable from 4.4 K up to about 20 K. The station is being prepared to validate the LHC model link, consisting of 48 superconducting cables, each operating at 600 A between 4.5 K and 5.4 K. This article describes features of the equipment

Conceptual design of the Cryogenic Electrical Feedboxes and the Superconducting Links of LHC

Powering the superconducting magnets of the LHC arcs and long straight sections is performed with more than 1000 electrical terminals supplying currents ranging from 120 A to 13’000 A and distributed in 44 cryogenic electrical feedboxes (DFB). Where space in the LHC tunnel is sufficient, the magnets are powered by locally installed cryogenic electrical feedboxes. Where there is no space for a DFB, the current will be supplied to the magnets by superconducting links (DSL) connecting the DFBs to the magnets on distances varying from 76 m to 510 m

COMMISSIONING AND FIRST OPERATION OF SUPERCONDUCTING LINKS AT THE LARGE HADRON COLLIDER (LHC)

The Large Hadron Collider (LHC) now under commissioning at CERN is a 26.7 km collider based on several thousand high-field superconducting magnets, the majority of which operating in superfluid helium below 2 K and some isolated magnets operating in normal helium at 4.5 K. Four superconducting links (DSLs) of about 76 m in length and one of about 517 m in length, were designed, constructed and installed over a three year period. Their purpose is to transport current over long distances whenever underground LHC space constraints prevents to put power converters, current feed boxes and magnets in each others’ proximity. The four 76 m long DSLs transport current between current feed boxes and several of the isolated magnets, whereas the 517 m long DSL transports current between two current feed boxes. The links are comprised of cryogenic, vacuum-insulated, transfer lines housing one or more superconducting cables. The operating temperatures are about 5 K for the DSL part that houses the cable and about 60 K for the heat shield. Their commissioning and performance results at first operational experience in the beginning of 2008 are discussed

The liquid helium storage system for the Large Hadron Collider.

The cryogenic system of the Large Hadron Collider (LHC) under operation at CERN has a total helium inventory of 140 t. Up to 50 t can be stored in gas storage tanks. The remaining inventory will be stored in a liquid helium storage system consisting of six 15-t liquid helium tanks in 4 locations. The two liquid helium tanks of specific low heat inleak design and the required infrastructure of the first location were recently commissioned. Four additional tanks shall be operational end 2010. The paper describes the features and characteristics of the liquid helium storage system and presents the measurement of the thermal performance of the two first tanks

Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data

IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation. OBJECTIVE: To validate CXR-LC using EMR data to identify individuals at high-risk for lung cancer to complement 2022 US Centers for Medicare & Medicaid Services (CMS) lung cancer screening eligibility guidelines. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study compared CXR-LC estimates with CMS screening guidelines using patient data from a large US hospital system. Included participants were persons who currently or formerly smoked cigarettes with an outpatient posterior-anterior chest radiograph between January 1, 2013, and December 31, 2014, with no history of lung cancer or screening CT. Data analysis was performed between May 2021 and June 2022. EXPOSURES: CXR-LC lung cancer screening eligibility (previously defined as having a 3.297% or greater 12-year risk) based on inputs (chest radiograph image, age, sex, and whether currently smoking) extracted from the EMR. MAIN OUTCOMES AND MEASURES: 6-year incident lung cancer. RESULTS: A total of 14 737 persons were included in the study population (mean [SD] age, 62.6 [6.8] years; 7154 [48.5%] male; 204 [1.4%] Asian, 1051 [7.3%] Black, 432 [2.9%] Hispanic, 12 330 [85.2%] White) with a 2.4% rate of incident lung cancer over 6 years (361 patients with cancer). CMS eligibility could be determined in 6277 patients (42.6%) using smoking pack-year and quit-date from the EMR. Patients eligible by both CXR-LC and 2022 CMS criteria had a high rate of lung cancer (83 of 974 patients [8.5%]), higher than those eligible by 2022 CMS criteria alone (5 of 177 patients [2.8%]; P < .001). Patients eligible by CXR-LC but not 2022 CMS criteria also had a high 6-year incidence of lung cancer (121 of 3703 [3.3%]). In the 8460 cases (57.4%) where CMS eligibility was unknown, CXR-LC eligible patients had a 5-fold higher rate of lung cancer than ineligible (127 of 5177 [2.5%] vs 18 of 2283 [0.5%]; P < .001). Similar results were found in subgroups, including female patients and Black persons. CONCLUSIONS AND RELEVANCE: Using routine chest radiographs and other data automatically extracted from the EMR, CXR-LC identified high-risk individuals who may benefit from lung cancer screening CT

Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data

IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation. OBJECTIVE: To validate CXR-LC using EMR data to identify individuals at high-risk for lung cancer to complement 2022 US Centers for Medicare & Medicaid Services (CMS) lung cancer screening eligibility guidelines. DESIGN, SETTING, AND PARTICIPANTS: This prognostic study compared CXR-LC estimates with CMS screening guidelines using patient data from a large US hospital system. Included participants were persons who currently or formerly smoked cigarettes with an outpatient posterior-anterior chest radiograph between January 1, 2013, and December 31, 2014, with no history of lung cancer or screening CT. Data analysis was performed between May 2021 and June 2022. EXPOSURES: CXR-LC lung cancer screening eligibility (previously defined as having a 3.297% or greater 12-year risk) based on inputs (chest radiograph image, age, sex, and whether currently smoking) extracted from the EMR. MAIN OUTCOMES AND MEASURES: 6-year incident lung cancer. RESULTS: A total of 14 737 persons were included in the study population (mean [SD] age, 62.6 [6.8] years; 7154 [48.5%] male; 204 [1.4%] Asian, 1051 [7.3%] Black, 432 [2.9%] Hispanic, 12 330 [85.2%] White) with a 2.4% rate of incident lung cancer over 6 years (361 patients with cancer). CMS eligibility could be determined in 6277 patients (42.6%) using smoking pack-year and quit-date from the EMR. Patients eligible by both CXR-LC and 2022 CMS criteria had a high rate of lung cancer (83 of 974 patients [8.5%]), higher than those eligible by 2022 CMS criteria alone (5 of 177 patients [2.8%]; P < .001). Patients eligible by CXR-LC but not 2022 CMS criteria also had a high 6-year incidence of lung cancer (121 of 3703 [3.3%]). In the 8460 cases (57.4%) where CMS eligibility was unknown, CXR-LC eligible patients had a 5-fold higher rate of lung cancer than ineligible (127 of 5177 [2.5%] vs 18 of 2283 [0.5%]; P < .001). Similar results were found in subgroups, including female patients and Black persons. CONCLUSIONS AND RELEVANCE: Using routine chest radiographs and other data automatically extracted from the EMR, CXR-LC identified high-risk individuals who may benefit from lung cancer screening CT

Impact of high ionizing dose on high-power white LEDs

National audienceVisible cameras operating at 1 MGy of g radiation require radiation tolerant illumination system. Here, commercially available high-power white LEDs have been tested under X and g radiations. The light power of white commercial LED was shown to slightly decrease (less than 10 %) in post irradiation measurements. A closer analysis, based on the ABC model for efficiency droop, reveals that irradiation essentially increases the amount of trap assisted recombination, impacting the LED quantum efficiency mostly at low supply voltage. This suggests that favoring the LED operation at higher supply voltage could be a good strategy to enhance the radiation hardness of LED-based illumination systems

Impact of high ionizing dose on high-power white LEDs

National audienceVisible cameras operating at 1 MGy of g radiation require radiation tolerant illumination system. Here, commercially available high-power white LEDs have been tested under X and g radiations. The light power of white commercial LED was shown to slightly decrease (less than 10 %) in post irradiation measurements. A closer analysis, based on the ABC model for efficiency droop, reveals that irradiation essentially increases the amount of trap assisted recombination, impacting the LED quantum efficiency mostly at low supply voltage. This suggests that favoring the LED operation at higher supply voltage could be a good strategy to enhance the radiation hardness of LED-based illumination systems