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  • 2020-2023  (4)
  • 1985-1989  (2)
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  • 1
    Publication Date: 2022-03-24
    Description: Volcanic ash (VA) from explosive eruptions contributes to aerosol loadings in the atmosphere. Aside from the negative impact of VA on air quality and aviation, these particles can alter the optical and microphysical properties of clouds by triggering ice formation, thereby influencing precipitation and climate. Depending on the volcano and eruption style, VA displays a wide range of different physical, chemical, and mineralogical properties. Here, we present a unique data set on the ice nucleation activity of 15 VA samples obtained from different volcanoes worldwide. The ice nucleation activities of these samples were studied in the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud simulation chamber as well as with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). All VA particles nucleated ice in the immersion freezing mode from 263 to 238K with ice nucleation active site (INAS) densities ranging from ∼105 to 1011 m−2, respectively. The variabilities observed among the VA samples, at any given temperature, range over 3.5 orders of magnitude. The ice‐nucleating abilities of VA samples correlate to varying degrees with their bulk pyroxene and plagioclase contents as a function of temperature. We combined our new data set with existing literature data to develop an improved ice nucleation parameterization for natural VA in the immersion freezing mode. This should be useful for modeling the impact of VA on clouds.
    Description: Plain Language Summary: Volcanic ash particles, which are generated during volcanic eruptions, can initiate ice formation in clouds. The clouds formed by these volcanic ash particles can influence precipitation, and in turn, weather and climate. In our study, we investigated the ability with which volcanic ash particles form ice in clouds. We performed our study in a state‐of‐the‐art aerosol and cloud simulation chamber and on a cold‐stage instrument. The findings show that volcanic ash particles can form ice as effectively as mineral dust particles or their components. These results will help scientists to have a better understanding of the impact of volcanic ash particles on clouds.
    Description: Key Points: The ice‐nucleating ability of natural volcanic ash particles in the immersion freezing mode can vary by 3.5 orders of magnitude. Ice‐nucleating properties of volcanic ash particles correlate to varying degrees with their pyroxene and plagioclase contents. The temperature‐dependent immersion freezing ability of volcanic ash is approximated with an exponential fit line.
    Description: Alexander von Humboldt‐Stiftung (Humboldt‐Stiftung) http://dx.doi.org/10.13039/100005156
    Description: Marie Skłodowska‐Curie Actions
    Description: ERC 2018 ADG
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Description: Helmholtz Association of German Research Centres
    Description: EUROCHAMP 2020 Infrastructure Activity
    Keywords: ddc:551.38 ; ddc:549 ; ddc:552.23
    Language: English
    Type: doc-type:article
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  • 2
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    In:  Geophys. J. Int., Jena, Physica-Verlag, vol. 96, no. 2, pp. 253-258, pp. 2096, (ISSN: 1340-4202)
    Publication Date: 1989
    Keywords: Wave propagation ; Waves ; GJI
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  • 3
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    In:  Geophys. J. Int., Hannover, Bundesanstalt für Geowissenschaften und Rohstoffe, vol. 99, no. 8, pp. 415-420, pp. L08305
    Publication Date: 1989
    Keywords: Seismics (controlled source seismology) ; Wave propagation ; GJI
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  • 4
    Publication Date: 2022-03-21
    Description: The heart rate in humans is regulated by the autonomic nervous system, which modulates the frequency of heart contractions, resulting in heart rate variability (HRV). Therefore, to assess the activity of the autonomic nervous system, which contains important information for medical diagnostics, methods based on the analysis of interbeat interval variability are often used. This approach does not require the use of invasive methods for measuring the signals of the autonomic nervous system, but its accuracy is an open question. Using mathematical modeling, we investigate the possibility of extracting the signal of frequency modulation of the heartbeats from the electrocardiogram (ECG) signal and conduct a detailed comparison of the extracted signal with the real modulating signal. Since the quality of extraction of the signal of frequency modulation from the ECG depends on the method of demodulation, we compare two different approaches. One is based on the detection of the main oscillation rhythm and its bandpass filtering, and the other on the heterodyning technique. It is shown that low-frequency (LF) and high-frequency (HF) oscillations in HRV associated, respectively, with sympathetic and parasympathetic modulation by the autonomic nervous system, in the general case, significantly differ from the signals of frequency modulation of the heart rate in shape, but have close similarity with them in the frequency domain. We find that in model systems, the similarity of the LF component of HRV with sympathetic modulation of the heart rate is higher than the similarity of the HF component of HRV with parasympathetic modulation.
    Type: info:eu-repo/semantics/article
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  • 5
    Publication Date: 2022-03-21
    Description: We propose a mathematical model of the human cardiovascular system. The model allows one to simulate the main heart rate, its variability under the influence of the autonomic nervous system, breathing process, and oscillations of blood pressure. For the first time, the model takes into account the activity of the cerebral cortex structures that modulate the autonomic control loops of blood circulation in the awake state and in various stages of sleep. The adequacy of the model is demonstrated by comparing its time series with experimental records of healthy subjects in the SIESTA database. The proposed model can become a useful tool for studying the characteristics of the cardiovascular system dynamics during sleep.
    Type: info:eu-repo/semantics/article
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  • 6
    Publication Date: 2022-03-21
    Description: We present a study of quantitative characteristics of a test subject attention associated with analysis of EEG-records in test subjects. Twelve overall healthy subjects 20–35 years old (5/7 male/female) with complaints about daytime sleepiness were included. Multichannel electroencephalography was conducted during the monotonous sound perception test. The processing of the EEG signals was based on the adapted method for assessing spatial patterns using the Karhunen–Loève transformation. We used descriptive statistics to summarize our findings. All experimental time was classified into active stages with reaction to sound stimuli and passive stages, in which subjects demonstrated drowsiness without reaction to presented stimuli. An analysis of EEG activity in conjunction with assessment of the patient response enabled us to identify a characteristic scenario of adaptation to the task of maintaining attention to sound stimuli in this group. Active stages with a minimum reaction time of response to the signal and maximum duration were preceded by an increase in the spatial activity complexity on the EEG of the left hemisphere during the passive stage without responses. The passive stage of drowsiness without response to stimuli was actively involved in the process of adaptation to prolonged monotonic activity in patients with increased daytime sleepiness.
    Type: info:eu-repo/semantics/article
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