scholarly journals Improving atmospheric path attenuation estimates for radio propagation applications by microwave radiometric profiling

2021 ◽  
Vol 14 (4) ◽  
pp. 2737-2748
Author(s):  
Ayham Alyosef ◽  
Domenico Cimini ◽  
Lorenzo Luini ◽  
Carlo Riva ◽  
Frank S. Marzano ◽  
...  
Keyword(s):  
A Priori ◽  
Microwave Radiometer ◽  
Radio Propagation ◽  
Expected Improvement ◽  
Atmospheric Attenuation ◽  
V Band ◽  
W Band ◽  
Novel Approach ◽  
Atmospheric Path ◽  
The Mean

Abstract. Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate atmospheric attenuation at relative transparent channels for radio propagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at channels other than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing 1 year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K- and V–W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at the V band (54–58 GHz). The retrieval coefficients are then applied to a 1-year dataset of real V-band observations, and the estimated TMR at the K and V–W band is compared with estimates from nearly colocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32 %–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10 %–20 % for K-band channels and ∼30 % for V–W-band channels.

scholarly journals Improving atmospheric path-attenuation estimates for radiopropagation applications by microwave radiometric profiling

2020 ◽  
Author(s):  
Ayham Alyosef ◽  
Domenico Cimini ◽  
Lorenzo Luini ◽  
Carlo Riva ◽  
Frank S. Marzano ◽  
...  
Keyword(s):  
A Priori ◽  
Microwave Radiometer ◽  
Expected Improvement ◽  
Atmospheric Attenuation ◽  
V Band ◽  
W Band ◽  
Novel Approach ◽  
Atmospheric Path ◽  
The Mean ◽  
One Year

Abstract. Ground-based microwave radiometer (MWR) observations of downwelling brightness temperature (TB) are commonly used to estimate the atmospheric attenuation at relative transparent channels for radiopropagation and telecommunication purposes. The atmospheric attenuation is derived from TB by inverting the radiative transfer equation with a priori knowledge of the mean radiating temperature (TMR). TMR is usually estimated by either time-variant site climatology (e.g., monthly average computed from atmospheric thermodynamical profiles) or condition-variant estimation from surface meteorological sensors. However, information on TMR may also be extracted directly from MWR measurements at other channels than those used to estimate atmospheric attenuation. This paper proposes a novel approach to estimate TMR in clear and cloudy sky from independent MWR profiler measurements. A linear regression algorithm is trained with a simulated dataset obtained by processing one year of radiosonde observations of atmospheric thermodynamic profiles. The algorithm is trained to estimate TMR at K-, and V/W-band frequencies (22–31 and 72–82 GHz, respectively) from independent MWR observations at V-band (54–58 GHz). The retrieval coefficients are then applied to a one-year dataset of real V-band observations, and the estimated TMR at K- and V/W-band are compared with estimates from nearly collocated and simultaneous radiosondes. The proposed method provides TMR estimates in better agreement with radiosondes than a traditional method, with 32–38 % improvement depending on frequency. This maps into an expected improvement in atmospheric attenuation of 10–20 % for K-band and ~ 30 % for V/W-band channels.

scholarly journals Multispecies for multifunctions: combining four complementary species enhances multifunctionality of sown grassland

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthias Suter ◽  
Olivier Huguenin-Elie ◽  
Andreas Lüscher
Keyword(s):  
Forage Quality ◽  
N Cycling ◽  
Forage Production ◽  
Mixture Effects ◽  
Novel Approach ◽  
Overall Performance ◽  
The Mean ◽  
High Forage ◽  
Diversity Effects ◽  
Species Mixtures

AbstractAssessing the overall performance of ecosystems requires a quantitative evaluation of multifunctionality. We investigated plant species diversity effects on individual functions and overall multifunctionality in a grassland experiment with sown monocultures and mixtures comprising four key grass and legume species. Nitrogen fertilisation rates were 50, 150, and 450 kg N ha−1 yr−1 (N50, N150, N450). Ten functions were measured representing forage production, N cycling, and forage quality, all being related to either productivity or environmental footprint. Multifunctionality was analysed by a novel approach using the mean log response ratio across functions. Over three experimental years, mixture effects benefited all forage production and N cycling functions, while sustaining high forage quality. Thus, mixture effects did not provoke any trade-off among the analysed functions. High N fertilisation rates generally diminished mixture benefits. Multifunctionality of four-species mixtures was considerably enhanced, and mixture overall performance was up to 1.9 (N50), 1.8 (N150), and 1.6 times (N450) higher than in averaged monocultures. Multifunctionality of four-species mixtures at N50 was at least as high as in grass monocultures at N450. Sown grass–legume mixtures combining few complementary species at low to moderate N fertilisation sustain high multifunctionality and are a ‘ready-to-use’ option for the sustainable intensification of agriculture.

Maternal attendance patterns of Steller sea lions (Eumetopias jubatus) from stable and declining populations in Alaska

2003 ◽  
Vol 81 (2) ◽  
pp. 340-348 ◽  
Author(s):  
Linda L Milette ◽  
Andrew W Trites
Keyword(s):  
Prey Availability ◽  
A Priori ◽  
Population Decline ◽  
Perinatal Period ◽  
Eumetopias Jubatus ◽  
Steller Sea Lions ◽  
Sea Lions ◽  
First Feeding ◽  
Attendance Patterns ◽  
The Mean

Maternal attendance patterns of Alaskan Steller sea lions (Eumetopias jubatus) were compared during the summer breeding seasons in 1994 and 1995 at Sugarloaf Island (a declining population) and Lowrie Island (a stable population). Our goal was to determine whether there were differences in maternal attendance between the two populations that were consistent with the hypothesis that lactating Steller sea lions in the area of decline were food-limited during summer. Our a priori expectations were based on well-documented behavioural responses of otariids to reduced prey availability. We found that foraging trips were significantly shorter in the area of population decline, counter to initial predictions. The mean length of foraging trips in the declining area was 19.5 h compared with 24.9 h in the stable area. In contrast, the mean perinatal period (time between parturition and first feeding trip) was significantly longer in the area of decline (9.9 versus 7.9 days), again countering initial predictions. The mean length of shore visits for the declining population was also significantly longer (27.0 h compared with 22.6 h where the population was stable). For both populations, the mean time that mothers foraged increased as pups grew older, whereas the time that they spent on shore with their pups became shorter. Behavioural observations of maternal attendance patterns are inconsistent with the hypothesis that lactating Steller sea lions from the declining population had difficulty obtaining prey during summer.

scholarly journals The p38/MK2 Axis in Monocytes of Fibromyalgia Syndrome Patients: An Explorative Study

Medicina ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 396
Author(s):  
Boya Nugraha ◽  
Renate Scheibe ◽  
Christoph Korallus ◽  
Matthias Gaestel ◽  
Christoph Gutenbrunner
Keyword(s):  
Pain Management ◽  
P38 Mapk ◽  
Fibromyalgia Syndrome ◽  
Mapk Pathway ◽  
Mitogen Activated Protein Kinase ◽  
Pain Syndromes ◽  
Novel Approach ◽  
Mitogen Activated Protein ◽  
The Mean ◽  
Direct Target

Background and Objectives: The aetiology and pathomechanism of fibromyalgia syndrome 12 (FMS) as one of chronic pain syndromes still need to be further elucidated. Mitogen-activated protein kinase (MAPK) pathway has been proposed as a novel approach in pain management. Since the major symptom of fibromyalgia syndrome (FMS) patients is pain, it became of interest whether MAPK pathways, such as the stress-activated p38 MAPK/MK2 axis, are activated in FMS patients. Therefore, this study aimed at determining p38 MAPK/MK2 in FMS patients. Materials and Methods: Phosphorylation of MAPK-activated protein kinases 2 (MK2), a direct target of p38 MAPK, was measured in monocytes of FMS and healthy controls (HCs) to monitor the activity of this pathway. Results: The mean level of phosphorylated MK2 was fivefold higher in FMS patients as compared to HCs (p < 0.001). Subgroup analysis revealed that antidepressants did not influence the activity of MK2 in FMS patients. Conclusions: This result indicates that the p38/MK2 pathway could be involved in the pathomechanism of FMS, could act as a clinical marker for FMS, and could be a possible target for pain management in FMS patients.

scholarly journals Comparison of ozone profiles and influences from the tertiary ozone maximum in the night-to-day ratio above Switzerland

2017 ◽  
Vol 17 (17) ◽  
pp. 10259-10268 ◽  
Author(s):  
Lorena Moreira ◽  
Klemens Hocke ◽  
Niklaus Kämpfer
Keyword(s):  
Annual Variation ◽  
Lower Stratosphere ◽  
Microwave Radiometer ◽  
Relative Difference ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Ozone Maximum ◽  
Ozone Profile ◽  
Mesospheric Ozone ◽  
The Mean

Abstract. Stratospheric and middle-mesospheric ozone profiles above Bern, Switzerland (46.95° N, 7.44° E; 577 m) have been continually measured by the GROMOS (GROund-based Millimeter-wave Ozone Spectrometer) microwave radiometer since 1994. GROMOS is part of the Network for the Detection of Atmospheric Composition Change (NDACC). A new version of the ozone profile retrievals has been developed with the aim of improving the altitude range of retrieval profiles. GROMOS profiles from this new retrieval version have been compared to coincident ozone profiles obtained by the satellite limb sounder Aura Microwave Limb Sounder (MLS). The study covers the stratosphere and middle mesosphere from 50 to 0.05 hPa (from 21 to 70 km) and extends over the period from July 2009 to November 2016, which results in more than 2800 coincident profiles available for the comparison. On average, GROMOS and MLS comparisons show agreement generally over 20 % in the lower stratosphere and within 2 % in the middle and upper stratosphere for both daytime and nighttime, whereas in the mesosphere the mean relative difference is below 40 % during the daytime and below 15 % during the nighttime. In addition, we have observed the annual variation in nighttime ozone in the middle mesosphere, at 0.05 hPa (70 km), characterized by the enhancement of ozone during wintertime for both ground-based and space-based measurements. This behaviour is related to the middle-mesospheric maximum in ozone (MMM).

A Geometric Model of the Beating Heart

2007 ◽  
Vol 46 (03) ◽  
pp. 282-286 ◽  
Author(s):  
C. Lorenz ◽  
J. von Berg
Keyword(s):  
Computed Tomography ◽  
A Priori ◽  
Anatomical Landmarks ◽  
Motion Model ◽  
A Priori Information ◽  
Average Accuracy ◽  
Tomography Image ◽  
The Mean ◽  
Priori Information ◽  
Computed Tomography Image

Summary Objectives : A comprehensive model of the human heart that covers multiple surfaces, like those of the four chambers and the attached vessels, is presented. It also contains the coronary arteries and a set of 25 anatomical landmarks. The statistical model is intended to provide a priori information for automated diagnostic and interventional procedures. Methods : The end-diastolic phase of the model was adapted to fit 27 clinical multi-slice computed tomography images, thus reflecting the anatomical variability to be observed in that sample. A mean cardiac motion model was also calculated from a set of eleven multi-phase computed tomography image sets. A number of experiments were performed to determine the accuracy of model-based predictions done on unseen cardiac images. Results : Using an additional deformable surface technique, the model allows for determination of all chambers and the attached vessels on the basis of given anatomical landmarks with an average accuracy of 1.1 mm. After such an individualization of the model by surface adaptation the centerlines of the three main coronary arteries may be estimated with an average accuracy of 5.2 mm. The mean motion model was used to estimate the cardiac phase of an unknown multislice computed tomography image. Conclusion : The mean shape model of the human heart as presented here complements automated image analysis methods with the required a priori information about anatomical constraints to make them work fast and robustly.

scholarly journals Estimation of the mean normal measure from flat sections

2008 ◽  
Vol 40 (01) ◽  
pp. 31-48
Author(s):  
Markus Kiderlen
Keyword(s):  
A Priori ◽  
The Other ◽  
Consistent Estimator ◽  
Random Set ◽  
Normal Measure ◽  
Mild Assumption ◽  
The Mean ◽  
Vertical Sections ◽  
Almost All

We discuss the determination of the mean normal measure of a stationary random set Z ⊂ ℝ d by taking measurements at the intersections of Z with k-dimensional planes. We show that mean normal measures of sections with vertical planes determine the mean normal measure of Z if k ≥ 3 or if k = 2 and an additional mild assumption holds. The mean normal measures of finitely many flat sections are not sufficient for this purpose. On the other hand, a discrete mean normal measure can be verified (i.e. an a priori guess can be confirmed or discarded) using mean normal measures of intersections with m suitably chosen planes when m ≥ ⌊d / k⌋ + 1. This even holds for almost all m-tuples of k-dimensional planes are viable for verification. A consistent estimator for the mean normal measure of Z, based on stereological measurements in vertical sections, is also presented.

scholarly journals A regional CO2 observing system simulation experiment for the ASCENDS satellite mission

2014 ◽  
Vol 14 (23) ◽  
pp. 12897-12914 ◽  
Author(s):  
J. S. Wang ◽  
S. R. Kawa ◽  
J. Eluszkiewicz ◽  
D. F. Baker ◽  
M. Mountain ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Dispersion Model ◽  
A Priori ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Instrument Design ◽  
Satellite Mission ◽  
Model Framework ◽  
Satellite Systems ◽  
Novel Approach

Abstract. Top–down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in combination with the Weather Research and Forecasting (WRF) model in a regional Bayesian synthesis inversion. The regional Lagrangian particle dispersion model framework is well suited to make use of ASCENDS observations to constrain weekly fluxes in North America at a high resolution, in this case at 1° latitude × 1° longitude. We consider random measurement errors only, modeled as a function of the mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the grid scale and weekly resolution, the largest uncertainty reductions, on the order of 50%, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 μm candidate wavelength than for a 2.05 μm wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual biome scale range from ~40% to ~75% across our four instrument design cases and from ~65% to ~85% for the continent as a whole. Tests suggest that the quantitative results are moderately sensitive to assumptions regarding a priori uncertainties and boundary conditions. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr−1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

scholarly journals Monitoring distributed computing beyond the traditional time-series histogram

2020 ◽  
Vol 245 ◽  
pp. 03036
Author(s):  
M S Doidge ◽  
P. A. Love ◽  
J Thornton
Keyword(s):  
Time Series ◽  
Distributed Computing ◽  
Real Time ◽  
A Priori ◽  
Time Data ◽  
Use Of Time ◽  
Computing Services ◽  
Monitoring Tools ◽  
Novel Approach ◽  
Current Monitoring

In this work we describe a novel approach to monitor the operation of distributed computing services. Current monitoring tools are dominated by the use of time-series histograms showing the evolution of various metrics. These can quickly overwhelm or confuse the viewer due to the large number of similar looking graphs. We propose a supplementary approach through the sonification of real-time data streamed directly from a variety of distributed computing services. The real-time nature of this method allows operations staff to quickly detect problems and identify that a problem is still ongoing, avoiding the case of investigating an issue a-priori when it may already have been resolved. In this paper we present details of the system architecture and provide a recipe for deployment suitable for both site and experiment teams.

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