4 resultados para Sub-sampling

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

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Ice cores provide a robust reconstruction of past climate. However, development of timescales by annual-layer counting, essential to detailed climate reconstruction and interpretation, on ice cores collected at low-accumulation sites or in regions of compressed ice, is problematic due to closely spaced layers. Ice-core analysis by laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) provides sub-millimeter-scale sampling resolution (on the order of 100μm in this study) and the low detection limits (ng L–1) necessary to measure the chemical constituents preserved in ice cores. We present a newly developed cryocell that can hold a 1m long section of ice core, and an alternative strategy for calibration. Using ice-core samples from central Greenland, we demonstrate the repeatability of multiple ablation passes, highlight the improved sampling resolution, verify the calibration technique and identify annual layers in the chemical profile in a deep section of an ice core where annual layers have not previously been identified using chemistry. In addition, using sections of cores from the Swiss/Italian Alps we illustrate the relationship between Ca, Na and Fe and particle concentration and conductivity, and validate the LA-ICP-MS Ca profile through a direct comparison with continuous flow analysis results.

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BACKGROUND The objective of the study was to evaluate the implications of different classifications of rheumatic heart disease on estimated prevalence, and to systematically assess the importance of incidental findings from echocardiographic screening among schoolchildren in Peru. METHODS We performed a cluster randomized observational survey using portable echocardiography among schoolchildren aged 5 to 16 years from randomly selected public and private schools in Arequipa, Peru. Rheumatic heart disease was defined according to the modified World Health Organization (WHO) criteria and the World Heart Federation (WHF) criteria. FINDINGS Among 1395 eligible students from 40 classes and 20 schools, 1023 (73%) participated in the present survey. The median age of the children was 11 years (interquartile range [IQR] 8-13 years) and 50% were girls. Prevalence of possible, probable and definite rheumatic heart disease according to the modified WHO criteria amounted to 19.7/1000 children and ranged from 10.2/1000 among children 5 to 8 years of age to 39.8/1000 among children 13 to 16 years of age; the prevalence of borderline/definite rheumatic heart disease according to the WHF criteria was 3.9/1000 children. 21 children (2.1%) were found to have congenital heart disease, 8 of which were referred for percutaneous or surgical intervention. CONCLUSIONS Prevalence of RHD in Peru was considerably lower compared to endemic regions in sub-Saharan Africa, southeast Asia, and Oceania; and paralleled by a comparable number of undetected congenital heart disease. Strategies to address collateral findings from echocardiographic screening are necessary in the setup of active surveillance programs for RHD. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT02353663.