93 research outputs found
The Detection of Defects in a Niobium Tri-layer Process
Niobium (Nb) LTS processes are emerging as the technology for future ultra high-speed systems especially in the digital domain. As the number of Josephson Junctions (JJ) per chip has recently increased to around 90000, the quality of the process has to be assured so as to realize these complex circuits. Until now, very little or no information is available in the literature on how to achieve this. In this paper we present an approach and results of a study conducted on an RSFQ process. Measurements and SEM inspection were carried out on sample chips and a list of possible defects has been identified and described in detail. We have also developed test-structures for detection of the top-ranking defects, which will be used for yield analysis and the determination of the probability distribution of faults in the process. A test chip has been designed, based on the results of this study, and certain types of defects were introduced in the design to study the behavior of faulty junctions and interconnections
Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium
International audienceOperational applications of a hydrological model often require the prediction of stream flow in (future) time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders), with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the simulation of a large river basin. Keywords: hydrological model, regionalisation, parameterisation, spatial variabilit
Testable Design and Testing of High-Speed Superconductor Microelectronics
True software-defined radio cellular base stations require extremely fast data converters, which can not currently be implemented in semiconductor technology. Superconductor niobium-based delta ADCs have shown to be able to perform this task. The problem of testing these devices is a severe task, as very little is known about possible defects in this technology. This paper shows an approach for gaining information on these defects and illustrates how BIST can be a solution of detecting defects in ADCs under extreme conditions
Effects of watershed and riparian zone characteristics on nutrient concentrations in the River Scheldt Basin
International audienceThe relative influence of a set of watershed characteristics on surface water nutrient concentrations was examined in 173 watersheds within two subcatchments (Upper-Scheldt and Nete) of the River Scheldt Basin (Flanders, Belgium). Each watershed was described by seasonal rainfall, discharge loading of point sources, morphological characteristics (area, average slope, drainage density, elongation), land use and soil properties (soil texture and drainage). Partial regression analysis revealed that soil drainage variables had the strongest influence on nutrient concentrations. Additional influence was exerted by land use and point source loading variables. Nitrate concentrations were positively correlated with effluent loadings coming from wastewater treatment plants and with the area of agricultural land. Phosphate concentrations were best explained by effluent loadings of industrial point sources and by the area of urban land. Land use close to the river was not a better predictor of nitrate and phosphate concentrations than land use away from the river. This suggests that the mediating impact of riparian zones is rather explained by the hydrologic pathways within the buffer strip
Quality of life after treatment with immune checkpoint inhibitors for lung cancer:the impact of age
Introduction: Immune checkpoint inhibitors (ICIs) have revolutionized lung cancer treatment. However, it remains unclear as to whether changes in Health-Related Quality-of-Life (HRQoL) are associated with the age of lung cancer patients treated using ICIs. This study aimed to evaluate this possible association and to compare ICI-treated patients’ HRQoL scores with normative data of an age-matched non-cancer general population.Methods: Lung cancer patients from the OncoLifeS data-biobank were included if they were treated with ICIs, irrespective of other treatments, at the University Medical Center Groningen between 2015 and 2021 and had completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTCQLQ-C30), both at the start of ICI treatment and after six months. Association of age as a continuous variable (per 10 years) and changes in HRQoL scores between baseline and 6 months was assessed using multivariable regression analyses. Clinical relevance of differences in HRQoL scores between OncoLifeS and the general population was classified into trivial, small, medium, and large, for three age groups (<60, 60–69 and ≥ 70 years).Results: 151 patients were included with a mean age of 65.8 years. An increase in age per 10 years was associated with a larger decrease in the summary HRQoL score(β = -3.28,CI95%-6.42;-0.14), physical(β = -4.8, CI95% −8.71;-0.88), cognitive(β = −4.51,CI95%-8.24;−0.78), role functioning(β = −5.41,CI95%-10.78;−0.05), symptom burden(β = −3.66,CI95%-6.6;-0.73), and smaller negative changes in financial difficulties(β = 6.5 95 % CI 3.16; 9.85). OncoLifeS HRQoL scores were lower than those of the general population and differences were most often classified as large and medium.Conclusion: Older lung cancer patients experience larger deteriorations in most HRQoL domains after 6 months of ICI treatment. Also, these patients showed significantly lower HRQoL scores compared to the general population.</p
Influenza season influence on outcome of new nodules in the NELSON study
We evaluated the impact of the influenza season on outcome of new lung nodules in a LDCT lung cancer screening trial population. NELSON-trial participants with ≥ 1 new nodule detected in screening rounds two and three were included. Outcome (resolution or persistence) of new nodules detected per season was calculated and compared. Winter (influenza season) was defined as 1st October to 31st March, and compared to the summer (hay-fever season), 1st April to 30th September. Overall, 820 new nodules were reported in 529 participants. Of the total new nodules, 482 (59%) were reported during winter. When considering the outcome of all new nodules, there was no statistically significant association between summer and resolving nodules (OR 1.07 [CI 1.00-1.15], p = 0.066), also when looking at the largest nodule per participant (OR 1.37 [CI 0.95-1.98], p = 0.094). Similarly, there was no statistically significant association between season and screen detected cancers (OR 0.47 [CI 0.18-1.23], p = 0.123). To conclude, in this lung cancer screening population, there was no statistically significant association between influenza season and outcome of new lung nodules. Hence, we recommend new nodule management strategy is not influenced by the season in which the nodule is detected.</p
Seasonal prevalence and characteristics of low-dose CT detected lung nodules in a general Dutch population
We investigated whether presence and characteristics of lung nodules in the general population using low-dose computed tomography (LDCT) varied by season. Imaging in Lifelines (ImaLife) study participants who underwent chest LDCT-scanning between October 2018 and October 2019 were included in this sub-study. Hay fever season (summer) was defined as 1st April to 30th September and Influenza season (winter) as 1st October to 31st March. All lung nodules with volume of ≥ 30 mm3 (approximately 3 mm in diameter) were registered. In total, 2496 lung nodules were found in 1312 (38%) of the 3456 included participants (nodules per participant ranging from 1 to 21, median 1). In summer, 711 (54%) participants had 1 or more lung nodule(s) compared to 601 (46%) participants in winter (p = 0.002). Of the spherical, perifissural and left-upper-lobe nodules, relatively more were detected in winter, whereas of the polygonal-, irregular-shaped and centrally-calcified nodules, relatively more were detected in summer. Various seasonal diseases with inflammation as underlying pathophysiology may influence presence and characteristics of lung nodules. Further investigation into underlying pathophysiology using short-term LDCT follow-up could help optimize the management strategy for CT-detected lung nodules in clinical practice
Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial
BACKGROUND There are limited data from randomized trials regarding whether volume-based, low-dose computed tomographic (CT) screening can reduce lung-cancer mortality among male former and current smokers. METHODS A total of 13,195 men (primary analysis) and 2594 women (subgroup analyses) between the ages of 50 and 74 were randomly assigned to undergo CT screening at T0 (baseline), year 1, year 3, and year 5.5 or no screening. We obtained data on cancer diagnosis and the date and cause of death through linkages with national registries in the Netherlands and Belgium, and a review committee confirmed lung cancer as the cause of death when possible. A minimum follow-up of 10 years until December 31, 2015, was completed for all participants. RESULTS Among men, the average adherence to CT screening was 90.0%. On average, 9.2% of the screened participants underwent at least one additional CT scan (initially indeterminate). The overall referral rate for suspicious nodules was 2.1%. At 10 years of follow-up, the incidence of lung cancer was 5.58 cases per 1000 personyears in the screening group and 4.91 cases per 1000 person-years in the control group; lung-cancer mortality was 2.50 deaths per 1000 person-years and 3.30 deaths per 1000 person-years, respectively. The cumulative rate ratio for death from lung cancer at 10 years was 0.76 (95% confidence interval [CI], 0.61 to 0.94; P = 0.01) in the screening group as compared with the control group, similar to the values at years 8 and 9. Among women, the rate ratio was 0.67 (95% CI, 0.38 to 1.14) at 10 years of follow-up, with values of 0.41 to 0.52 in years 7 through 9. CONCLUSIONS In this trial involving high-risk persons, lung-cancer mortality was significantly lower among those who underwent volume CT screening than among those who underwent no screening. There were low rates of follow-up procedures for results suggestive of lung cancer. (Funded by the Netherlands Organization of Health Research and Development and others; NELSON Netherlands Trial Register number, NL580.)
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