972 resultados para Time measurements


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The volcanic aerosol plume resulting from the Eyjafjallajökull eruption in Iceland in April and May 2010 was detected in clear layers above Switzerland during two periods (17–19 April 2010 and 16–19 May 2010). In-situ measurements of the airborne volcanic plume were performed both within ground-based monitoring networks and with a research aircraft up to an altitude of 6000 m a.s.l. The wide range of aerosol and gas phase parameters studied at the high altitude research station Jungfraujoch (3580 m a.s.l.) allowed for an in-depth characterization of the detected volcanic aerosol. Both the data from the Jungfraujoch and the aircraft vertical profiles showed a consistent volcanic ash mode in the aerosol volume size distribution with a mean optical diameter around 3 ± 0.3 μm. These particles were found to have an average chemical composition very similar to the trachyandesite-like composition of rock samples collected near the volcano. Furthermore, chemical processing of volcanic sulfur dioxide into sulfate clearly contributed to the accumulation mode of the aerosol at the Jungfraujoch. The combination of these in-situ data and plume dispersion modeling results showed that a significant portion of the first volcanic aerosol plume reaching Switzerland on 17 April 2010 did not reach the Jungfraujoch directly, but was first dispersed and diluted in the planetary boundary layer. The maximum PM10 mass concentrations at the Jungfraujoch reached 30 μgm−3 and 70 μgm−3 (for 10-min mean values) duri ng the April and May episode, respectively. Even low-altitude monitoring stations registered up to 45 μgm−3 of volcanic ash related PM10 (Basel, Northwestern Switzerland, 18/19 April 2010). The flights with the research aircraft on 17 April 2010 showed one order of magnitude higher number concentrations over the northern Swiss plateau compared to the Jungfraujoch, and a mass concentration of 320 (200–520) μgm−3 on 18 May 2010 over the northwestern Swiss plateau. The presented data significantly contributed to the time-critical assessment of the local ash layer properties during the initial eruption phase. Furthermore, dispersion models benefited from the detailed information on the volcanic aerosol size distribution and its chemical composition.

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A precise synchronization of different climate records is indispensable for a correct dynamical interpretation of paleoclimatic data. A chronology for the TALDICE ice core from the Ross Sea sector of East Antarctica has recently been presented based on methane synchronization with Greenland and the EDC ice cores and δ18Oice synchronization with EDC in the bottom part (TALDICE-1). Using new high-resolution methane data obtained with a continuous flow analysis technique, we present a refined age scale for the age interval from 55–112 thousand years (ka) before present, where TALDICE is synchronized with EDC. New and more precise tie points reduce the uncertainties of the age scale from up to 1900 yr in TALDICE-1 to below 1100 yr over most of the refined interval and shift the Talos Dome dating to significantly younger ages during the onset of Marine Isotope Stage 3. Thus, discussions of climate dynamics at sub-millennial time scales are now possible back to 110 ka, in particular during the inception of the last ice age. Calcium data of EDC and TALDICE are compared to show the impact of the refinement to the synchronization of the two ice cores not only for the gas but also for the ice age scale.

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Multiple-breath washout (MBW)-derived lung clearance index (LCI) is a sensitive measure of ventilation inhomogeneity in patients with cystic fibrosis (CF), but LCI measurement is time consuming. We systematically assessed ways to shorten LCI measurements. In 68 school-aged children (44 with mild CF lung disease) three standard nitrogen (N2) MBWs were applied. We assessed repeatability and diagnostic performance of (1) LCI measured earlier from three MBW runs and (2) LCI measured at complete MBW (1/40th of starting N2 concentration) from two runs only. Compared with the standard LCI from three complete MBW runs, the new LCI based on three N2MBW runs until 1/20th, or two complete runs until 1/40th, provided similar or better repeatability as well as sensitivity and specificity for CF lung disease. Alternative ways to measure LCI reduced test duration in children with CF by 30% and 41%, respectively. LCI measurements can be reliably shortened in children. These new MBW protocols may advance the transition of LCI from research into clinical settings.

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We report on the wind radiometer WIRA, a new ground-based microwave Doppler-spectro-radiometer specifically designed for the measurement of middle-atmospheric horizontal wind by observing ozone emission spectra at 142.17504 GHz. Currently, wind speeds in five levels between 30 and 79 km can be retrieved which makes WIRA the first instrument able to continuously measure horizontal wind in this altitude range. For an integration time of one day the measurement error on each level lies at around 25 m s−1. With a planned upgrade this value is expected to be reduced by a factor of 2 in the near future. On the altitude levels where our measurement can be compared to wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF) very good agreement in the long-term statistics as well as in short time structures with a duration of a few days has been found. WIRA uses a passive double sideband heterodyne receiver together with a digital Fourier transform spectrometer for the data acquisition. A big advantage of the radiometric approach is that such instruments can also operate under adverse weather conditions and thus provide a continuous time series for the given location. The optics enables the instrument to scan a wide range of azimuth angles including the directions east, west, north, and south for zonal and meridional wind measurements. The design of the radiometer is fairly compact and its calibration does not rely on liquid nitrogen which makes it transportable and suitable for campaign use. WIRA is conceived in a way that it can be operated remotely and does hardly require any maintenance. In the present paper, a description of the instrument is given, and the techniques used for the wind retrieval based on the determination of the Doppler shift of the measured atmospheric ozone emission spectra are outlined. Their reliability was tested using Monte Carlo simulations. Finally, a time series of 11 months of zonal wind measurements over Bern (46°57′ N, 7°26′ E) is presented and compared to ECMWF wind data.

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Visualization and exploratory analysis is an important part of any data analysis and is made more challenging when the data are voluminous and high-dimensional. One such example is environmental monitoring data, which are often collected over time and at multiple locations, resulting in a geographically indexed multivariate time series. Financial data, although not necessarily containing a geographic component, present another source of high-volume multivariate time series data. We present the mvtsplot function which provides a method for visualizing multivariate time series data. We outline the basic design concepts and provide some examples of its usage by applying it to a database of ambient air pollution measurements in the United States and to a hypothetical portfolio of stocks.

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The aim of the current study was to examine the effect of theta burst repetitive transcranial magnetic stimulation (rTMS) on the blood oxygenation level-dependent (BOLD) activation during repeated functional magnetic resonance imaging (fMRI) measurements. Theta burst rTMS was applied over the right frontal eye field in seven healthy subjects. Subsequently, repeated fMRI measurements were performed during a saccade-fixation task (block design) 5, 20, 35, and 60 min after stimulation. We found that theta burst rTMS induced a strong and long-lasting decrease of the BOLD signal response of the stimulated frontal eye field at 20 and 35 min. Furthermore, less pronounced alterations of the BOLD signal response with different dynamics were found for remote oculomotor areas such as the left frontal eye field, the pre-supplementary eye field, the supplementary eye field, and both parietal eye fields. Recovery of the BOLD signal changes in the anterior remote areas started earlier than in the posterior remote areas. These results show that a) the major inhibitory impact of theta burst rTMS occurs directly in the stimulated area itself, and that b) a lower effect on remote, oculomotor areas can be induced.

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Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

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Nitrous oxide fluxes were measured at the Lägeren CarboEurope IP flux site over the multi-species mixed forest dominated by European beech and Norway spruce. Measurements were carried out during a four-week period in October–November 2005 during leaf senescence. Fluxes were measured with a standard ultrasonic anemometer in combination with a quantum cascade laser absorption spectrometer that measured N2O, CO2, and H2O mixing ratios simultaneously at 5 Hz time resolution. To distinguish insignificant fluxes from significant ones it is proposed to use a new approach based on the significance of the correlation coefficient between vertical wind speed and mixing ratio fluctuations. This procedure eliminated roughly 56% of our half-hourly fluxes. Based on the remaining, quality checked N2O fluxes we quantified the mean efflux at 0.8±0.4 μmol m−2 h−1 (mean ± standard error). Most of the contribution to the N2O flux occurred during a 6.5-h period starting 4.5 h before each precipitation event. No relation with precipitation amount could be found. Visibility data representing fog density and duration at the site indicate that wetting of the canopy may have as strong an effect on N2O effluxes as does below-ground microbial activity. It is speculated that above-ground N2O production from the senescing leaves at high moisture (fog, drizzle, onset of precipitation event) may be responsible for part of the measured flux.

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OBJECTIVE: Resonance frequency analysis (RFA) is a method of measuring implant stability. However, little is known about RFA of implants with long loading periods. The objective of the present study was to determine standard implant stability quotients (ISQs) for clinical successfully osseointegrated 1-stage implants in the edentulous mandible. MATERIALS AND METHODS: Stability measurements by means of RFA were performed in regularly followed patients who had received 1- stage implants for overdenture support. The time interval between implant placement and measurement ranged from 1 year up to 10 years. The short-term group comprised patients who were followed up to 5 years, while the long-term group included patients with an observation time of > 5 years up to 10 years. For further comparison RFA measurements were performed in a matching group with unloaded implants at the end of the surgical procedure. For statistical analysis various parameters that might influence the ISQs of loaded implants were included, and a mixed-effects model applied (regression analysis, P <.0125). RESULTS: Ninety-four patients were available with a total of 205 loaded implants, and 16 patients with 36 implants immediately after the surgical procedure. The mean ISQ of all measured implants was 64.5 +/- 7.9 (range, 58 to 72). Statistical analysis did not reveal significant differences in the mean ISQ related to the observation time. The parameters with overall statistical significance were the diameter of the implants and changes in the attachment level. In the short-term group, the gender and the clinically measured attachment level had a significant effect. Implant diameter had a significant effect in the long-term group. CONCLUSIONS: A mean ISQ of 64.5 +/- 7.9 was found to be representative for stable asymptomatic interforaminal implants measured by the RFA instrument at any given time point. No significant differences in ISQ values were found between implants with different postsurgical time intervals. Implant diameter appears to influence the ISQ of interforaminal implants.

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The use of conventional orifice-plate meter is typically restricted to measurements of steady flows. This study proposes a new and effective computational-experimental approach for measuring the time-varying (but steady-in-the-mean) nature of turbulent pulsatile gas flows. Low Mach number (effectively constant density) steady-in-the-mean gas flows with large amplitude fluctuations (whose highest significant frequency is characterized by the value fF) are termed pulsatile if the fluctuations have a direct correlation with the time-varying signature of the imposed dynamic pressure difference and, furthermore, they have fluctuation amplitudes that are significantly larger than those associated with turbulence or random acoustic wave signatures. The experimental aspect of the proposed calibration approach is based on use of Coriolis-meters (whose oscillating arm frequency fcoriolis >> fF) which are capable of effectively measuring the mean flow rate of the pulsatile flows. Together with the experimental measurements of the mean mass flow rate of these pulsatile flows, the computational approach presented here is shown to be effective in converting the dynamic pressure difference signal into the desired dynamic flow rate signal. The proposed approach is reliable because the time-varying flow rate predictions obtained for two different orifice-plate meters exhibit the approximately same qualitative, dominant features of the pulsatile flow.

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This work presents an innovative integration of sensing and nano-scaled fluidic actuation in the combination of pH sensitive optical dye immobilization with the electro-osmotic phenomena in polar solvents like water for flow-through pH measurements. These flow-through measurements are performed in a flow-through sensing device (FTSD) configuration that is designed and fabricated at MTU. A relatively novel and interesting material, through-wafer mesoporous silica substrates with pore diameters of 20 -200 nm and pore depths of 500 µm are fabricated and implemented for electro-osmotic pumping and flow-through fluorescence sensing for the first time. Performance characteristics of macroporous silicon (> 500 µm) implemented for electro-osmotic pumping include, a very large flow effciency of 19.8 µLmin-1V-1 cm-2 and maximum pressure effciency of 86.6 Pa/V in comparison to mesoporous silica membranes with 2.8 µLmin-1V-1cm-2 flow effciency and a 92 Pa/V pressure effciency. The electrical current (I) of the EOP system for 60 V applied voltage utilizing macroporous silicon membranes is 1.02 x 10-6A with a power consumption of 61.74 x 10-6 watts. Optical measurements on mesoporous silica are performed spectroscopically from 300 nm to 1000 nm using ellipsometry, which includes, angularly resolved transmission and angularly resolved reflection measurements that extend into the infrared regime. Refractive index (n) values for oxidized and un-oxidized mesoporous silicon sample at 1000 nm are found to be 1.36 and 1.66. Fluorescence results and characterization confirm the successful pH measurement from ratiometric techniques. The sensitivity measured for fluorescein in buffer solution is 0.51 a.u./pH compared to sensitivity of ~ 0.2 a.u./pH in the case of fluorescein in porous silica template. Porous silica membranes are efficient templates for immobilization of optical dyes and represent a promising method to increase sensitivity for small variations in chemical properties. The FTSD represents a device topology suitable for application to long term monitoring of lakes and reservoirs. Unique and important contributions from this work include fabrication of a through-wafer mesoporous silica membrane that has been thoroughly characterized optically using ellipsometry. Mesoporous silica membranes are tested as a porous media in an electro-osmotic pump for generating high pressure capacities due to the nanometer pore sizes of the porous media. Further, dye immobilized mesoporous silica membranes along with macroporous silicon substrates are implemented for continuous pH measurements using fluorescence changes in a flow-through sensing device configuration. This novel integration and demonstration is completely based on silicon and implemented for the first time and can lead to miniaturized flow-through sensing systems based on MEMS technologies.

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A non-hierarchical K-means algorithm is used to cluster 47 years (1960–2006) of 10-day HYSPLIT backward trajectories to the Pico Mountain (PM) observatory on a seasonal basis. The resulting cluster centers identify the major transport pathways and collectively comprise a long-term climatology of transport to the observatory. The transport climatology improves our ability to interpret the observations made there and our understanding of pollution source regions to the station and the central North Atlantic region. I determine which pathways dominate transport to the observatory and examine the impacts of these transport patterns on the O3, NOy, NOx, and CO measurements made there during 2001–2006. Transport from the U.S., Canada, and the Atlantic most frequently reaches the station, but Europe, east Africa, and the Pacific can also contribute significantly depending on the season. Transport from Canada was correlated with the North Atlantic Oscillation (NAO) in spring and winter, and transport from the Pacific was uncorrelated with the NAO. The highest CO and O3 are observed during spring. Summer is also characterized by high CO and O3 and the highest NOy and NOx of any season. Previous studies at the station attributed the summer time high CO and O3 to transport of boreal wildfire emissions (for 2002–2004), and boreal fires continued to affect the station during 2005 and 2006. The particle dispersion model FLEXPART was used to calculate anthropogenic and biomass-burning CO tracer values at the station in an attempt to identify the regions responsible for the high CO and O3 observations during spring and biomass-burning impacts in summer.

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Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

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Nearly 22 million Americans operate as shift workers, and shift work has been linked to the development of cardiovascular disease (CVD). This study is aimed at identifying pivotal risk factors of CVD by assessing 24 hour ambulatory blood pressure, state anxiety levels and sleep patterns in 12 hour fixed shift workers. We hypothesized that night shift work would negatively affect blood pressure regulation, anxiety levels and sleep patterns. A total of 28 subjects (ages 22-60) were divided into two groups: 12 hour fixed night shift workers (n=15) and 12 hour fixed day shift workers (n=13). 24 hour ambulatory blood pressure measurements (Space Labs 90207) were taken twice: once during a regular work day and once on a non-work day. State anxiety levels were assessed on both test days using the Speilberger’s State Trait Anxiety Inventory. Total sleep time (TST) was determined using self recorded sleep diary. Night shift workers demonstrated increases in 24 hour systolic (122 ± 2 to 126 ± 2 mmHg, P=0.012); diastolic (75 ± 1 to 79 ± 2 mmHg, P=0.001); and mean arterial pressures (90 ± 2 to 94 ± 2mmHg, P<0.001) during work days compared to off days. In contrast, 24 hour blood pressures were similar during work and off days in day shift workers. Night shift workers reported less TST on work days versus off days (345 ± 16 vs. 552 ± 30 min; P<0.001), whereas day shift workers reported similar TST during work and off days (475 ± 16 minutes to 437 ± 20 minutes; P=0.231). State anxiety scores did not differ between the groups or testing days (time*group interaction P=0.248), suggesting increased 24 hour blood pressure during night shift work is related to decreased TST, not short term anxiety. Our findings suggest that fixed night shift work causes disruption of the normal sleep-wake cycle negatively affecting acute blood pressure regulation, which may increase the long-term risk for CVD.