scholarly journals A model-based interpretation of low-frequency changes in the carbon cycle during the last 120,000 years and its implications for the reconstruction of atmospheric Δ14C

2006 ◽  
Vol 7 (11) ◽  
pp. n/a-n/a ◽  
Author(s):  
Peter Köhler ◽  
Raimund Muscheler ◽  
Hubertus Fischer
Keyword(s):  
Carbon Cycle ◽  
Low Frequency ◽  
Model Based ◽  
Frequency Changes

scholarly journals Simulating low frequency changes in atmospheric CO<sub>2</sub> during the last 740 000 years

2006 ◽  
Vol 2 (2) ◽  
pp. 57-78 ◽  
Author(s):  
P. Köhler ◽  
H. Fischer
Keyword(s):  
Carbon Cycle ◽  
Southern Ocean ◽  
Ice Core ◽  
Low Frequency ◽  
Ice Cores ◽  
Deep Ocean ◽  
Natural Variability ◽  
Delayed Response ◽  
Marine Biota ◽  
Frequency Changes

Abstract. Atmospheric CO2 measured in Antarctic ice cores shows a natural variability of 80 to 100 ppmv during the last four glacial cycles and variations of approximately 60 ppmv in the two cycles between 410 and 650 kyr BP. We here use various paleo-climatic records from the EPICA Dome C Antarctic ice core and from oceanic sediment cores covering the last 740 kyr to force the ocean/atmosphere/biosphere box model of the global carbon cycle BICYCLE in a forward mode over this time in order to interpret the natural variability of CO2. Our approach is based on the previous interpretation of carbon cycle variations during Termination I (Köhler et al., 2005a). In the absense of a process-based sediment module one main simplification of BICYCLE is that carbonate compensation is approximated by the temporally delayed restoration of deep ocean [CO32−]. Our results match the low frequency changes in CO2 measured in the Vostok and the EPICA Dome C ice core for the last 650 kyr BP (r2≈0.75). During these transient simulations the carbon cycle reaches never a steady state due to the ongoing variability of the overall carbon budget caused by the time delayed response of the carbonate compensation to other processes. The average contributions of different processes to the rise in CO2 during Terminations I to V and during earlier terminations are: the rise in Southern Ocean vertical mixing: 36/22 ppmv, the rise in ocean temperature: 26/11 ppmv, iron limitation of the marine biota in the Southern Ocean: 20/14 ppmv, carbonate compensation: 15/7 ppmv, the rise in North Atlantic deep water formation: 13/0 ppmv, the rise in gas exchange due to a decreasing sea ice cover: −8/−7 ppmv, sea level rise: −12/−4 ppmv, and rising terrestrial carbon storage: −13/−6 ppmv. According to our model the smaller interglacial CO2 values in the pre-Vostok period prior to Termination V are mainly caused by smaller interglacial Southern Ocean SST and an Atlantic THC which stayed before MIS 11 (before 420 kyr BP) in its weaker glacial circulation mode.

SEM image sharpness analysis

1996 ◽  
Vol 54 ◽  
pp. 142-143
Author(s):  
M. T. Postek ◽  
A. E. Vladar
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Quantitative Information ◽  
Primary Electron ◽  
Image Sharpness ◽  
Critical Dimensions ◽  
Sem Image ◽  
Frequency Changes ◽  
Electron Microscopes ◽  
Scanning Electron

Fully automated or semi-automated scanning electron microscopes (SEM) are now commonly used in semiconductor production and other forms of manufacturing. The industry requires that an automated instrument must be routinely capable of 5 nm resolution (or better) at 1.0 kV accelerating voltage for the measurement of nominal 0.25-0.35 micrometer semiconductor critical dimensions. Testing and proving that the instrument is performing at this level on a day-by-day basis is an industry need and concern which has been the object of a study at NIST and the fundamentals and results are discussed in this paper.In scanning electron microscopy, two of the most important instrument parameters are the size and shape of the primary electron beam and any image taken in a scanning electron microscope is the result of the sample and electron probe interaction. The low frequency changes in the video signal, collected from the sample, contains information about the larger features and the high frequency changes carry information of finer details. The sharper the image, the larger the number of high frequency components making up that image. Fast Fourier Transform (FFT) analysis of an SEM image can be employed to provide qualitiative and ultimately quantitative information regarding the SEM image quality.

scholarly journals AmpliCI: a high-resolution model-based approach for denoising Illumina amplicon data

2020 ◽  
Author(s):  
Xiyu Peng ◽  
Karin S Dorman
Keyword(s):  
Sequence Similarity ◽  
Low Frequency ◽  
Computation Time ◽  
Amplicon Sequencing ◽  
Supplementary Information ◽  
Quality Information ◽  
Model Based ◽  
Main Challenge ◽  
Sequencing Quality ◽  
Resolution Model

Abstract Motivation Next-generation amplicon sequencing is a powerful tool for investigating microbial communities. A main challenge is to distinguish true biological variants from errors caused by amplification and sequencing. In traditional analyses, such errors are eliminated by clustering reads within a sequence similarity threshold, usually 97%, and constructing operational taxonomic units, but the arbitrary threshold leads to low resolution and high false-positive rates. Recently developed ‘denoising’ methods have proven able to resolve single-nucleotide amplicon variants, but they still miss low-frequency sequences, especially those near more frequent sequences, because they ignore the sequencing quality information. Results We introduce AmpliCI, a reference-free, model-based method for rapidly resolving the number, abundance and identity of error-free sequences in massive Illumina amplicon datasets. AmpliCI considers the quality information and allows the data, not an arbitrary threshold or an external database, to drive conclusions. AmpliCI estimates a finite mixture model, using a greedy strategy to gradually select error-free sequences and approximately maximize the likelihood. AmpliCI has better performance than three popular denoising methods, with acceptable computation time and memory usage. Availability and implementation Source code is available at https://github.com/DormanLab/AmpliCI. Supplementary information Supplementary material are available at Bioinformatics online.

Dynamic modulation of cerebrovascular resistance as an index of autoregulation under tilt and controlled Pet CO2

2002 ◽  
Vol 283 (3) ◽  
pp. R653-R662 ◽  
Author(s):  
Michael R. Edwards ◽  
J. Kevin Shoemaker ◽  
Richard L. Hughson
Keyword(s):  
Transfer Function ◽  
Function Analysis ◽  
Low Frequency ◽  
Mean Flow ◽  
Low Frequencies ◽  
Cerebrovascular Autoregulation ◽  
Cerebrovascular Resistance ◽  
Arterial Blood ◽  
Transfer Function Analysis ◽  
Frequency Changes

Transfer function analysis of the arterial blood pressure (BP)-mean flow velocity (MFV) relationship describes an aspect of cerebrovascular autoregulation. We hypothesized that the transfer function relating BP to cerebrovascular resistance (CVRi) would be sensitive to low-frequency changes in autoregulation induced by head-up tilt (HUT) and altered arterial Pco 2. Nine subjects were studied in supine and HUT positions with end-tidal Pco 2(Pet CO2 ) kept constant at normal levels: +5 and −5 mmHg. The BP-MFV relationship had low coherence at low frequencies, and there were significant effects of HUT on gain only at high frequencies and of Pco 2 on phase only at low frequencies. BP → CVRi had coherence >0.5 from very low to low frequencies. There was a significant reduction of gain with increased Pco 2 in the very low and low frequencies and with HUT at the low frequency. Phase was affected by Pco 2 in the very low frequencies. Transfer function analysis of BP → CVRi provides direct evidence of altered cerebrovascular autoregulation under HUT and higher levels of Pco 2.

scholarly journals Regional distribution of non-human H7N9 avian influenza virus detections in China and construction of a predictive model

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zeying Huang ◽  
Haijun Li ◽  
BeiXun Huang
Keyword(s):  
Influenza Virus ◽  
Avian Influenza ◽  
Avian Influenza Virus ◽  
High Frequency ◽  
Regional Distribution ◽  
Low Frequency ◽  
Early Summer ◽  
Late Spring ◽  
Combined Model ◽  
Model Based

Abstract Introduction H7N9 avian influenza has broken out in Chinese poultry 10 times since 2013 and impacted the industry severely. Although the epidemic is currently under control, there is still a latent threat. Material and Methods Epidemiological surveillance data for non-human H7N9 avian influenza from April 2013 to April 2020 were used to analyse the regional distribution and spatial correlations of positivity rates in different months and years and before and after comprehensive immunisation. In addition, positivity rate monitoring data were disaggregated into a low-frequency and a high-frequency trend sequence by wavelet packet decomposition (WPD). The particle swarm optimisation algorithm was adopted to optimise the least squares support-vector machine (LS-SVM) model parameters to predict the low-frequency trend sequence, and the autoregressive integrated moving average (ARIMA) model was used to predict the high-frequency one. Ultimately, an LS-SVM-ARIMA combined model based on WPD was constructed. Results The virus positivity rate was the highest in late spring and early summer, and overall it fell significantly after comprehensive immunisation. Except for the year 2015 and the single month of December from 2013 to 2020, there was no significant spatiotemporal clustering in cumulative non-human H7N9 avian influenza virus detections. Compared with the ARIMA and LS-SVM models, the LS-SVM-ARIMA combined model based on WPD had the highest prediction accuracy. The mean absolute and root mean square errors were 2.4% and 2.0%, respectively. Conclusion Low error measures prove the validity of this new prediction method and the combined model could be used for inference of future H7N9 avian influenza virus cases. Live poultry markets should be closed in late spring and early summer, and comprehensive H7N9 immunisation continued.

scholarly journals Model-Based Energy Path Analysis of Tip-In Event in a 2WD Vehicle with Range-Extender Electric Powertrain Architecture

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5696
Author(s):  
Raja Mazuir Raja Ahsan Shah ◽  
Richard Peter Jones ◽  
Caizhen Cheng ◽  
Alessandro Picarelli ◽  
Abd Rashid Abd Abd Aziz ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Low Frequency ◽  
High Fidelity ◽  
Centre Of Gravity ◽  
Model Based ◽  
Dominant Component ◽  
Range Extender ◽  
Multibody Dynamic ◽  
Vehicle Systems ◽  
Dynamic Components

Vehicle driveability is one of the important attributes in range-extender electric vehicles due to the electric motor torque characteristics at low-speed events. Physical vehicle prototypes are typically used to validate and rectify vehicle driveability attributes. However, this can be expensive and require several design iterations. In this paper, a model-based energy method to assess vehicle driveability is presented based on high-fidelity 49 degree-of-freedom powertrain and vehicle systems. Multibody dynamic components were built according to their true centre of gravity relative to the vehicle datum to provide an accurate system interaction. The work covered a frequency of less than 20 Hz. The results consist of the components’ frequency domination, which was structured and examined to identify the low-frequency resonances sensitivity based on different operating parameters such as road surface coefficients. An energy path method was also implemented on the dominant component by decoupling its compliances to study the effect on the vehicle driveability and low-frequency resonances. The outcomes of the research provided a good understanding of the interaction across the sub-systems levels. The powertrain rubber mounts were the dominant component that controlled the low-frequency resonances (<15.33 Hz) and can change the vehicle driveability quality.

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