referee Comment, Tipping point analysis of ocean acoustic noise

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Acoustic Noise ◽  
Tipping Point ◽  
Point Analysis

scholarly journals Tipping point analysis of ocean acoustic noise

2018 ◽  
Vol 25 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Valerie N. Livina ◽  
Albert Brouwer ◽  
Peter Harris ◽  
Lian Wang ◽  
Kostas Sotirakopoulos ◽  
...  
Keyword(s):  
Dynamical System ◽  
Time Series ◽  
Acoustic Noise ◽  
Tipping Point ◽  
Acoustic Environment ◽  
Scaling Properties ◽  
Acoustic Data ◽  
Acoustic Fluctuations ◽  
Point Analysis ◽  
System States

Abstract. We apply tipping point analysis to a large record of ocean acoustic data to identify the main components of the acoustic dynamical system and study possible bifurcations and transitions of the system. The analysis is based on a statistical physics framework with stochastic modelling, where we represent the observed data as a composition of deterministic and stochastic components estimated from the data using time-series techniques. We analyse long-term and seasonal trends, system states and acoustic fluctuations to reconstruct a one-dimensional stochastic equation to approximate the acoustic dynamical system. We apply potential analysis to acoustic fluctuations and detect several changes in the system states in the past 14 years. These are most likely caused by climatic phenomena. We analyse trends in sound pressure level within different frequency bands and hypothesize a possible anthropogenic impact on the acoustic environment. The tipping point analysis framework provides insight into the structure of the acoustic data and helps identify its dynamic phenomena, correctly reproducing the probability distribution and scaling properties (power-law correlations) of the time series.

scholarly journals Tipping point analysis of ocean acoustic noise

2017 ◽  
Author(s):  
Valerie N. Livina ◽  
Albert Brouwer ◽  
Peter Harris ◽  
Lian Wang ◽  
Kostas Sotirakopoulos ◽  
...  
Keyword(s):  
Dynamical System ◽  
Time Series ◽  
Acoustic Noise ◽  
Tipping Point ◽  
Acoustic Environment ◽  
Scaling Properties ◽  
Acoustic Data ◽  
Acoustic Fluctuations ◽  
Point Analysis ◽  
System States

Abstract. We apply tipping point analysis to a large record of ocean acoustic data to identify the main components of the acoustic dynamical system and study possible bifurcations and transitions of the system. The analysis is based on a statistical physics framework with stochastic modelling, where we represent the observed data as a composition of deterministic and stochastic components estimated from the data using time series techniques. We analyse long-term and seasonal trends, system states and acoustic fluctuations to reconstruct a one-dimensional stochastic equation to approximate the acoustic dynamical system. We apply potential analysis to acoustic fluctuations and detect several changes in the system states in the past 14 years. These are most likely caused by climatic phenomena. We analyse trends in sound pressure level within different frequency bands and hypothesise a possible anthropogenic impact on the acoustic environment. The tipping point analysis framework provides insight into the structure of the acoustic data and helps identify its dynamic phenomena, correctly reproducing the probability distribution and scaling properties (power-law correlations) of the time series.

Tipping point analysis of atmospheric oxygen concentration

2015 ◽  
Vol 25 (3) ◽  
pp. 036403 ◽  
Author(s):  
V. N. Livina ◽  
T. M. Vaz Martins ◽  
A. B. Forbes
Keyword(s):  
Oxygen Concentration ◽  
Atmospheric Oxygen ◽  
Tipping Point ◽  
Point Analysis

A tipping point analysis of service-learning hours and student outcomes

2020 ◽  
Vol 62 (4) ◽  
pp. 413-425
Author(s):  
John Garger ◽  
Veselina P. Vracheva ◽  
Paul Jacques
Keyword(s):  
Service Learning ◽  
Student Satisfaction ◽  
Community Involvement ◽  
Student Outcomes ◽  
Tipping Point ◽  
Job Outcomes ◽  
Learning Context ◽  
Content Type ◽  
Point Analysis ◽  
Curvilinear Relationships

PurposeAlthough extant literature links overstimulation to various job outcomes, most studies do not consider a service-learning context, and they suggest a linear association between stimuli and outcomes. This paper examines the link between the number of service-learning hours students work and three educational outcomes – student satisfaction with the service-learning project, class relevancy to the service-learning project and expected community involvement.Design/methodology/approachApplying activation theory and Yerkes–Dodson law, we test curvilinear relationships between service-learning hours and student outcomes.FindingsResults suggest that students benefit from service learning up to a certain duration of a service-learning project.Originality/valueThis study identifies the tipping point of the number of service-learning hours beyond which students perceive decrements to three outcomes.

scholarly journals Tipping point analysis of cracking in reinforced concrete

2015 ◽  
Vol 25 (1) ◽  
pp. 015027 ◽  
Author(s):  
M Perry ◽  
V Livina ◽  
P Niewczas
Keyword(s):  
Reinforced Concrete ◽  
Tipping Point ◽  
Point Analysis

Dynamics of atmospheric oxygen under anthropogenic stresses

2020 ◽  
Author(s):  
Valerie Livina
Keyword(s):  
Oxygen Concentration ◽  
Carbon Emissions ◽  
Fossil Fuels ◽  
Atmospheric Oxygen ◽  
Tipping Point ◽  
Natural Weathering ◽  
Oxygen Budget ◽  
Point Analysis ◽  
Decline Rate ◽  
The Future

<p>We analyse proxy and observed data of atmospheric oxygen (ten contemporary records over the globe) and demonstrate its nonlinear decline, which is small but of uncertain decline rate. This decline was previously thought to be linear and caused mainly by use of fossil fuels (combustion), but by reviewing anthropogenic interventions we list more than a dozen smaller-scale processes that utilise oxygen in various forms. We have identified and quantified a previously unaccounted sink of atmospheric oxygen that serves multiple industries. This sink grows nonlinearly and has already exceeded the natural weathering deoxygenation. It has also been confirmed by means of comparison of the projection of oxygen decline with carbon emissions in the IPCC scenarios. We discuss the updated oxygen budget, possible solutions for the mitigation of the oxygen sink, and future dynamics of atmospheric oxygen.</p><p>[1] Livina et al, Tipping point analysis of atmospheric oxygen concentration, Chaos 25, 036403 (2015).</p><p>[2] Livina & Vaz Martins, The future of atmospheric oxygen, Springer Nature, in press.</p><p> </p>

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