Tipping point analysis of atmospheric oxygen concentration

Quantifying resilience and the risk of regime shifts under strong correlated noise

Early warning indicators often suffer from the shortness and coarse-graining of real-world time series. Furthermore, the typically strong and correlated noise contributions in real applications are severe drawbacks for statistical measures. Even under favourable simulation conditions the measures are of limited capacity due to their qualitative nature and sometimes ambiguous trend-to-noise ratio. In order to solve these shortcomings, we analyze the stability of the system via the slope of the deterministic term of a Langevin equation, which is hypothesized to underlie the system dynamics close to the fixed point. The open-source available method is applied to a previously studied seasonal ecological model under noise levels and correlation scenarios commonly observed in real world data. We compare the results to autocorrelation, standard deviation, skewness, and kurtosis as leading indicator candidates by a Bayesian model comparison with a linear and a constant model. We show that the slope of the deterministic term is a promising alternative due to its quantitative nature and high robustness against noise levels and types. The commonly computed indicators apart from the autocorrelation with deseasonalization fail to provide reliable insights into the stability of the system in contrast to a previously performed study in which the standard deviation was found to perform best. In addition, we discuss the significant influence of the seasonal nature of the data to the robust computation of the various indicators, before we determine approximately the minimal amount of data per time window that leads to significant trends for the drift slope estimations.

Digital society social interactions and trust analysis model

During unprecedented events such as COVID-19, the fabric of society comes under stress and all stakeholders want to increase the predictability of the future and reduce the ongoing uncertainties. In this research, an attempt has been made to model the situation in which the sentiment "trust" is computed so as to map the behaviour of society. However, technically, the purpose of this research is not to determine the "degree of trust in society" as a consequence of some specific emotions or sentiments that the community is experiencing at any particular time. This project is concerned with the construction of a computational model that can assist in improving our understanding of the dynamics of digital societies, particularly when it comes to the attitude referred to as "trust." The digital society trust analysis (D.S.T.A.) model that has been provided is simple to configure and simple to implement. It includes many previous models, such as standing models, Schelling's model of segregation, and tipping points, in order to construct models for understanding the dynamics of a society reeling under the effects of a COVID-19 pandemic, misinformation, fake news, and other sentiments that impact the behaviour of the different groups.

Impacts of Changes in Atmospheric O2 on Human Physiology. Is There a Basis for Concern?

Concern is often voiced over the ongoing loss of atmospheric O₂. This loss, which is caused by fossil-fuel burning but also influenced by other processes, is likely to continue at least for the next few centuries. We argue that this loss is quite well understood, and the eventual decrease is bounded by the fossil-fuel resource base. Because the atmospheric O₂ reservoir is so large, the predicted relative drop in O₂ is very small even for extreme scenarios of future fossil-fuel usage which produce increases in atmospheric CO₂ sufficient to cause catastrophic climate changes. At sea level, the ultimate drop in oxygen partial pressure will be less than 2.5 mm Hg out of a baseline of 159 mmHg. The drop by year 2300 is likely to be between 0.5 and 1.3 mmHg. The implications for normal human health is negligible because respiratory O₂ consumption in healthy individuals is only weakly dependent on ambient partial pressure, especially at sea level. The impacts on top athlete performance, on disease, on reproduction, and on cognition, will also be very small. For people living at higher elevations, the implications of this loss will be even smaller, because of a counteracting increase in barometric pressure at higher elevations due to global warming.

Oxygen, evolution and redox signalling in the human brain; quantum in the quotidian

Rising atmospheric oxygen (O₂ ) levels provided a selective pressure for the evolution of O₂ -dependent micro-organisms that began with the autotrophic eukaryotes. Since these primordial times, the respiring mammalian cell has become entirely dependent on the constancy of electron flow, with molecular O₂ serving as the terminal electron acceptor in mitochondrial oxidative phosphorylation. Indeed, the ability to 'sense' O₂ and maintain homeostasis is considered one of the most important roles of the central nervous system (CNS) and probably represented a major driving force in the evolution of the human brain. Today, modern humans have evolved with an oversized brain committed to a continually active state and, as a consequence, paradoxically vulnerable to failure if the O₂ supply is interrupted. However, our pre-occupation with O₂ , the elixir of life, obscures the fact that it is a gas with a Janus face, capable of sustaining life in physiologically controlled amounts yet paradoxically deadly to the CNS when in excess. A closer look at its quantum structure reveals precisely why; the triplet ground state diatomic O₂ molecule is paramagnetic and exists in air as a free radical, constrained from reacting aggressively with the brain's organic molecules due to its 'spin restriction', a thermodynamic quirk of evolutionary fate. By further exploring O₂ 's free radical 'quantum quirkiness', including emergent (quantum) physiological phenomena, our understanding of precisely how the human brain senses O₂ deprivation (hypoxia) and the elaborate redox-signalling defence mechanisms that defend O₂ homeostasis has the potential to offer unique insights into the pathophysiology and treatment of human brain disease.

RETRACTED ARTICLE: The quantum physiology of oxygen; from electrons to the evolution of redox signaling in the human brain

Rising atmospheric oxygen (O₂) levels provided a selective pressure for the evolution of O₂-dependent micro-organisms that began with the autotrophic eukaryotes. Since these primordial times, the respiring mammalian cell has become entirely dependent on the constancy of electron flow with molecular O₂ serving as the terminal electron acceptor in mitochondrial oxidative phosphorylation. Indeed, the ability to “sense” O₂ and maintain homeostasis is considered one of the most important roles of the central nervous system (CNS) and likely represented a major driving force in the evolution of the human brain. Today, modern humans have evolved with an oversized brain committed to a continually active state and as a consequence, paradoxically vulnerable to failure if the O₂ supply is interrupted. However, our pre-occupation with O₂, the elixir of life, obscures the fact that it is a gas with a Janus Face, capable of sustaining life in physiologically controlled amounts yet paradoxically deadly to the CNS when in excess. A closer look at its quantum structure reveals precisely why; the triplet ground state diatomic O₂ molecule is paramagnetic and exists in air as a free radical, constrained from reacting aggressively with the brain’s organic molecules due to its “spin restriction”, a thermodynamic quirk of evolutionary fate. By further exploring O₂’s free radical “quantum quirkiness” including emergent quantum physiological phenomena, our understanding of precisely how the human brain senses O₂ deprivation (hypoxia) and the elaborate redox-signaling defense mechanisms that defend O₂ homeostasis has the potential to offer unique insights into the pathophysiology and treatment of human brain disease.

The human physiological impact of global deoxygenation

There has been a clear decline in the volume of oxygen in Earth’s atmosphere over the past 20 years. Although the magnitude of this decrease appears small compared to the amount of oxygen in the atmosphere, it is difficult to predict how this process may evolve, due to the brevity of the collected records. A recently proposed model predicts a non-linear decay, which would result in an increasingly rapid fall-off in atmospheric oxygen concentration, with potentially devastating consequences for human health. We discuss the impact that global deoxygenation, over hundreds of generations, might have on human physiology. Exploring the changes between different native high-altitude populations provides a paradigm of how humans might tolerate worsening hypoxia over time. Using this model of atmospheric change, we predict that humans may continue to survive in an unprotected atmosphere for ~3600 years. Accordingly, without dramatic changes to the way in which we interact with our planet, humans may lose their dominance on Earth during the next few millennia.

Early warning signals for critical transitions in a thermoacoustic system

Dynamical systems can undergo critical transitions where the system suddenly shifts from one stable state to another at a critical threshold called the tipping point. The decrease in recovery rate to equilibrium (critical slowing down) as the system approaches the tipping point can be used to identify the proximity to a critical transition. Several measures have been adopted to provide early indications of critical transitions that happen in a variety of complex systems. In this study, we use early warning indicators to predict subcritical Hopf bifurcation occurring in a thermoacoustic system by analyzing the observables from experiments and from a theoretical model. We find that the early warning measures perform as robust indicators in the presence and absence of external noise. Thus, we illustrate the applicability of these indicators in an engineering system depicting critical transitions.