Long term very low frequency ambient noise: A window to the ocean and atmosphere

2021 ◽  
Vol 149 (4) ◽  
pp. A90-A90
Author(s):  
Anthony I. Eller ◽  
Kevin D. Heaney ◽  
James J. Murray ◽  
David L. Bradley
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

scholarly journals Pre-Emption of Affliction Severity Using HRV Measurements from a Smart Wearable; Case-Study on SARS-Cov-2 Symptoms

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7068
Author(s):  
Gatha Tanwar ◽  
Ritu Chauhan ◽  
Madhusudan Singh ◽  
Dhananjay Singh
Keyword(s):  
High Frequency ◽  
Viterbi Algorithm ◽  
Low Frequency ◽  
Very Low Frequency ◽  
Internal States ◽  
Hidden States ◽  
Complications And Mortality ◽  
Smart Wearable

Smart wristbands and watches have become an important accessory to fitness, but their application to healthcare is still in a fledgling state. Their long-term wear facilitates extensive data collection and evolving sensitivity of smart wristbands allows them to read various body vitals. In this paper, we hypothesized the use of heart rate variability (HRV) measurements to drive an algorithm that can pre-empt the onset or worsening of an affliction. Due to its significance during the time of the study, SARS-Cov-2 was taken as the case study, and a hidden Markov model (HMM) was trained over its observed symptoms. The data used for the analysis was the outcome of a study hosted by Welltory. It involved the collection of SAR-Cov-2 symptoms and reading of body vitals using Apple Watch, Fitbit, and Garmin smart bands. The internal states of the HMM were made up of the absence and presence of a consistent decline in standard deviation of NN intervals (SSDN), the root mean square of the successive differences (rMSSD) in R-R intervals, and low frequency (LF), high frequency (HF), and very low frequency (VLF) components of the HRV measurements. The emission probabilities of the trained HMM instance confirmed that the onset or worsening of the symptoms had a higher probability if the HRV components displayed a consistent decline state. The results were further confirmed through the generation of probable hidden states sequences using the Viterbi algorithm. The ability to pre-empt the exigent state of an affliction would not only lower the chances of complications and mortality but may also help in curbing its spread through intelligence-backed decisions.

Dictionary-unsanctioned Anglicisms

2017 ◽  
Author(s):  
Valérie Saugera
Keyword(s):  
Life Cycle ◽  
Low Frequency ◽  
Short Life ◽  
Global English ◽  
Very Low Frequency ◽  
Short And Long Term

This core chapter reports on the findings from the investigation of the Libération corpus. Systematic tracking of dictionary-unattested Anglicisms occurring over a year of press language reveals that contact with global English has resulted in new patterns of borrowing and processes for extending the French lexicon, for the short and long term. A major finding is that the database includes many types of Anglicisms with very few tokens: global English is a robust supplier of transient words (nonce borrowings and very low-frequency items) which complement the more durable lexicon. Diachronic comparisons show that these Anglicisms typically have a short life cycle in the French lexicon, though some Anglicisms from the corpus entered subsequent editions of the dictionary. The data also reveal the less common borrowing of items from closed classes, including pronoun himself, stressed article the, and the preposition-like series starring/featuring/including.

A review of DREA's very low‐frequency ambient noise program

1978 ◽  
Vol 64 (S1) ◽  
pp. S45-S45
Author(s):  
I. A. Fraser ◽  
H. M. Merklinger ◽  
J. H. Stockhausen
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

Multiyear variability of very-low-frequency ambient noise

2019 ◽  
Vol 146 (4) ◽  
pp. 2849-2849
Author(s):  
Anthony I. Eller ◽  
David L. Bradley ◽  
Kevin D. Heaney
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

Global examination of the wind-dependence of very low frequency underwater ambient noise

2016 ◽  
Vol 139 (3) ◽  
pp. 1110-1123 ◽  
Author(s):  
Stephen M. Nichols ◽  
David L. Bradley
Keyword(s):  
Ambient Noise ◽  
Low Frequency ◽  
Very Low Frequency

The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

2009 ◽  
Vol 23 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Suzannah K. Helps ◽  
Samantha J. Broyd ◽  
Christopher J. James ◽  
Anke Karl ◽  
Edmund J. S. Sonuga-Barke
Keyword(s):  
Brain Activity ◽  
Sampling Rate ◽  
Low Frequency ◽  
Future Research ◽  
Adhd Symptoms ◽  
Default Mode ◽  
Very Low Frequency ◽  
Wide Range ◽  
Interference Hypothesis ◽  
Mode Interference

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.

Sign in / Sign up

Export Citation Format

Share Document