Large-scale sources for negative hydrogen ions are required for the neutral beam injection of the ITER fusion device. Caesium is used for the conversion of hydrogen atoms into negative ions. The ...combination of moderate background vacuum conditions (10−7-10−6 mbar), the high reactivity of Cs, continuous evaporation of Cs and plasma-enabled redistribution of Cs and Cs+ forms a complex dynamics. ELISE (extraction from a large ion source experiment) is a half ITER-source scale experiment. A tunable diode laser absorption spectroscopy (TDLAS) diagnostic at the resonant Cs 62S1/2-62P3/2 transition (852 nm) has been applied to the source in order to measure the density of neutral Cs close to the conversion surface and thus gaining a better insight into the Cs dynamics. An inhomogeneous magnetic field created by permanent magnets ( 25-320 G) is located along the line-of-sight (LOS) of the TDLAS, leading to a varying effect of the Zeeman splitting of the concerning Cs states and thus the absorption line profile along the LOS. In long plasma pulses at ELISE, a change of the Cs absorption line profile takes place, which can be attributed to a variation of the Cs density profile along the LOS. In order to attribute a measured line profile to a certain magnetic field strength and thus a certain position along the LOS, absorption spectra with a defined B-field at a Cs vapor cell using the same diagnostic system have been measured. The strong broadening of the measured line profile at ELISE after several 10 s of plasma indicates that neutral Cs is mainly located in the area of high magnetic field strength, i.e. close to the side wall. A correlation between the measured Cs density and the source performance exists during the beginning of the pulse and is lost in this later phase.
Abstract Electrocardiographic (ECG) monitoring plays an important role in the management of patients with atrial fibrillation (AF). Automated real-time AF detection algorithm is an integral part of ...ECG monitoring during AF therapy. Before and after antiarrhythmic drug therapy and surgical procedures require ECG monitoring to ensure the success of AF therapy. This article reports our experience in developing a real-time AF monitoring algorithm and techniques to eliminate false-positive AF alarms. We start by designing an algorithm based on R-R intervals. This algorithm uses a Markov modeling approach to calculate an R-R Markov score. This score reflects the relative likelihood of observing a sequence of R-R intervals in AF episodes versus making the same observation outside AF episodes. Enhancement of the AF algorithm is achieved by adding atrial activity analysis. P-R interval variability and a P wave morphology similarity measure are used in addition to R-R Markov score in classification. A hysteresis counter is applied to eliminate short AF segments to reduce false AF alarms for better suitability in a monitoring environment. A large ambulatory Holter database (n = 633) was used for algorithm development and the publicly available MIT-BIH AF database (n = 23) was used for algorithm validation. This validation database allowed us to compare our algorithm performance with previously published algorithms. Although R-R irregularity is the main characteristic and strongest discriminator of AF rhythm, by adding atrial activity analysis and techniques to eliminate very short AF episodes, we have achieved 92% sensitivity and 97% positive predictive value in detecting AF episodes, and 93% sensitivity and 98% positive predictive value in quantifying AF segment duration.
During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO
2
) ...exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO
2
seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO
2
gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO
2
cycles from 48 European stations were available for 2017 and 2018. Earlier data were retrieved for comparison from international databases or national networks. Here, we show that the usual summer minimum in CO
2
due to the surface carbon uptake was reduced by 1.4 ppm in 2018 for the 10 stations located in the area most affected by the temperature anomaly, mostly in Northern Europe. Notwithstanding, the CO
2
transition phases before and after July were slower in 2018 compared to 2017, suggesting an extension of the growing season, with either continued CO
2
uptake by photosynthesis and/or a reduction in respiration driven by the depletion of substrate for respiration inherited from the previous months due to the drought. For stations with sufficiently long time series, the CO
2
anomaly observed in 2018 was compared to previous European droughts in 2003 and 2015. Considering the areas most affected by the temperature anomalies, we found a higher CO
2
anomaly in 2003 (+3 ppm averaged over 4 sites), and a smaller anomaly in 2015 (+1 ppm averaged over 11 sites) compared to 2018.
This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
QT-interval measurements have clinical importance for the electrocardiographic recognition of congenital and acquired heart disease and as markers of arrhythmogenic risk during drug therapy, but ...software algorithms for the automated measurement of electrocardiographic durations differ among manufacturers and evolve within manufacturers. To compare automated QT-interval measurements, simultaneous paired electrocardiograms were obtained in 218 subjects using digital recorders from the 2 major manufacturers of electrocardiographs used in the United States and analyzed by 2 currently used versions of each manufacturer’s software. The 4 automated QT and QTc durations were examined by repeated-measures analysis of variance with post hoc testing. Significantly larger automated QT-interval measurements were found with the most recent software of each manufacturer (12- to 24-ms mean differences from earlier algorithms). Systematic differences in QT measurements between manufacturers were significant for the earlier algorithms (11-ms mean difference) but not for the most recent software (1.3-ms mean difference). Similar relations were found for the rate-corrected QTc, with large mean differences between earlier and later algorithms (15 to 26 ms). Although there was a <2-ms mean difference between the most recent automated QTc measurements of the 2 manufacturers, the SD of the difference was 12 ms. In conclusion, reference values for automated electrocardiographic intervals and serial QT measurements vary among electrocardiographs and analysis software. Technically based differences in automated QT and QTc measurements must be considered when these intervals are used as markers of heart disease, prognosis, or arrhythmogenic risk.
Background: Commonly used techniques for QT measurement that identify T wave end using amplitude thresholds or the tangent method are sensitive to baseline drift and to variations of terminal T wave ...shape. Such QT measurement techniques commonly underestimate or overestimate the “true” QT interval.
Methods: To find the end of the T wave, the new Philips QT interval measurement algorithms use the distance from an ancillary line drawn from the peak of the T wave to a point beyond the expected inflection point at the end of the T wave. We have adapted and optimized modifications of this basic approach for use in three different ECG application areas: resting diagnostic, ambulatory Holter, and in‐hospital patient monitoring. The Philips DXL resting diagnostic algorithm uses an alpha‐trimming technique and a measure of central tendency to determine the median QT value of eight most reliable leads. In ambulatory Holter ECG analysis, generally only two or three channels are available. QT is measured on a root‐mean‐square vector magnitude signal. Finally, QT measurement in the real time in‐hospital application is among the most challenging areas of QT measurement. The Philips real time QT interval measurement algorithm employs features from both Philips DXL 12‐lead and ambulatory Holter QT algorithms with further enhancements.
Results: The diagnostic 12‐lead algorithm has been tested against the gold standard measurement database established by the CSE group with results surpassing the industrial ECG measurement accuracy standards. Holter and monitoring algorithm performance data on the PhysioNet QT database were shown to be similar to the manual measurements by two cardiologists.
Conclusion: The three variations of the QT measurement algorithm we developed are suitable for diagnostic 12‐lead, Holter, and patient monitoring applications.
In situ CO2 and CO measurements from five Integrated Carbon Observation System (ICOS) atmosphere stations have been analysed together with footprint model runs from the regional Stochastic ...Time-Inverted Lagrangian Transport (STILT) model to develop a dedicated strategy for flask sampling with an automated sampler. Flask sampling in ICOS has three different purposes, namely (1) to provide an independent quality control for in situ observations, (2) to provide representative information on atmospheric components currently not monitored in situ at the stations, and (3) to collect samples for 14CO2 analysis that are significantly influenced by fossil fuel CO2 (ffCO2) emission areas. Based on the existing data and experimental results obtained at the Heidelberg pilot station with a prototype flask sampler, we suggest that single flask samples are collected regularly every third day around noon or in the afternoon from the highest level of a tower station. Air samples shall be collected over 1 h, with equal temporal weighting, to obtain a true hourly mean. At all stations studied, more than 50 % of flasks collected around midday will likely be sampled during low ambient variability (<0.5 parts per million (ppm) standard deviation of 1 min values). Based on a first application at the Hohenpeißenberg ICOS site, such flask data are principally suitable for detecting CO2 concentration biases larger than 0.1 ppm with a 1σ confidence level between flask and in situ observations from only five flask comparisons. In order to have a maximum chance to also sample ffCO2 emission areas, additional flasks are collected on all other days in the afternoon. To check if theffCO2 component will indeed be large in these samples, we use the continuous in situ CO observations. The CO deviation from an estimated background value is determined the day after each flask sampling, and depending on this offset, an automated decision is made as to whether a flask shall be retained for14CO2 analysis. It turned out that, based on existing data,ffCO2 events of more than 4–5 ppm that would allow ffCO2 estimates with an uncertainty below 30 % were very rare at all stations studied, particularly in summer (only zero to five events per month from May to August). During the other seasons, events could be collected more frequently. The strategy developed in this project is currently being implemented at the ICOS stations.
What is inside the electrocardiograph? Gregg, Richard E., MSEE; Zhou, Sophia H., PhD; Lindauer, James M., MD ...
Journal of electrocardiology,
2008, 2008 Jan-Feb, 2008-1-00, 20080101, Letnik:
41, Številka:
1
Journal Article
Recenzirano
Abstract The details of digital recording and computer processing of a 12-lead electrocardiogram (ECG) remain a source of confusion for many health care professionals. A better understanding of the ...design and performance tradeoffs inherent in the electrocardiograph design might lead to better quality in ECG recording and better interpretation in ECG reading. This paper serves as a tutorial from an engineering point of view to those who are new to the field of ECG and to those clinicians who want to gain a better understanding of the engineering tradeoffs involved. The problem arises when the benefit of various electrocardiograph features is widely understood while the cost or the tradeoffs are not equally well understood. An electrocardiograph is divided into 2 main components, the patient module for ECG signal acquisition and the remainder for ECG processing which holds the main processor, fast printer, and display. The low-level ECG signal from the body is amplified and converted to a digital signal for further computer processing. The Electrocardiogram is processed for display by user selectable filters to reduce various artifacts. A high-pass filter is used to attenuate the very low frequency baseline sway or wander. A low-pass filter attenuates the high-frequency muscle artifact and a notch filter attenuates interference from alternating current power. Although the target artifact is reduced in each case, the ECG signal is also distorted slightly by the applied filter. The low-pass filter attenuates high-frequency components of the ECG such as sharp R waves and a high-pass filter can cause ST segment distortion for instance. Good skin preparation and electrode placement reduce artifacts to eliminate the need for common usage of these filters.
Abstract Background Classifying the location of an occlusion in the culprit artery during ST-elevation myocardial infarction (STEMI) is important for risk stratification to optimize treatment. We ...developed a new logistic regression (LR) algorithm for 3-group classification of occlusion location as proximal right coronary artery (RCA), middle-to-distal RCA or left circumflex (LCx) coronary artery with inferior myocardial infarction. We compared the performance of the new LR algorithm with the recently introduced decision tree classifier of Fiol et al ( Ann Noninvasive Electrocardiol . 2004;4:383-388) in the classification of the same 3 categories. Methods The new algorithm was developed on a set of electrocardiograms from an emergency department setting (n = 64) and tested on a different set from a prehospital setting (n = 68). All patients met the current STEMI criteria with angiographic confirmation of culprit artery and occlusion location. Using LR, 4 ST-segment deviation features were chosen by forward stepwise selection. Final LR coefficients were obtained by averaging more than 200 bootstrap iterations on the training set. In addition, a separate 4-feature classifier was designed adding ST features of V4 R and V8 , only available in the training set. Results The LR algorithm classified proximal RCA occlusion vs combined LCx occlusion and middle-to-distal RCA occlusion, with a sensitivity of 76% and specificity of 81% as compared with 71% and 62% for the Fiol classifier. The difference in specificity was statistically significant. The LR classifier trained with additional ST features of V4 R and V8 , but still limited to 4, improved the overall agreement in the training set from 65% to 70%. Conclusion Discrimination of proximal RCA lesion location from LCx or middle-to-distal RCA using the new LR classifier shows improvement over decision tree–type classification criteria. Automated identification of proximal RCA occlusion could speed up the risk stratification of patients with STEMI. The addition of leads V4 R and V8 should further improve the automated classification of the occlusion site in RCA and LCx.
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