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    Dynamical phenomena in complex networks: fundamentals and applications
    (Berlin ; Heidelberg : Springer, 2021) Yanchuk, Serhiy; Roque, Antonio C.; Macau, Elbert E. N.; Kurths, Jürgen
    This special issue presents a series of 33 contributions in the area of dynamical networks and their applications. Part of the contributions is devoted to theoretical and methodological aspects of dynamical networks, such as collective dynamics of excitable systems, spreading processes, coarsening, synchronization, delayed interactions, and others. A particular focus is placed on applications to neuroscience and Earth science, especially functional climate networks. Among the highlights, various methods for dealing with noise and stochastic processes in neuroscience are presented. A method for constructing weighted networks with arbitrary topologies from a single dynamical node with delayed feedback is introduced. Also, a generalization of the concept of geodesic distances, a path-integral formulation of network-based measures is developed, which provides fundamental insights into the dynamics of disease transmission. The contributions from the Earth science application field substantiate predictive power of climate networks to study challenging Earth processes and phenomena.
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    Report on ICDP Deep Dust workshops: probing continental climate of the late Paleozoic icehouse–greenhouse transition and beyond
    (Sapporo : IODP, 2020) Soreghan, Gerilyn S.; Beccaletto, Laurent; Benison, Kathleen C.; Bourquin, Sylvie; Feulner, Georg; Hamamura, Natsuko; Hamilton, Michael; Heavens, Nicholas G.; Hinnov, Linda; Huttenlocker, Adam; Looy, Cindy; Pfeifer, Lily S.; Pochat, Stephane; Sardar Abadi, Mehrdad; Zambito, James
    Chamberlin and Salisbury's assessment of the Permian a century ago captured the essence of the period: it is an interval of extremes yet one sufficiently recent to have affected a biosphere with near-modern complexity. The events of the Permian - the orogenic episodes, massive biospheric turnovers, both icehouse and greenhouse antitheses, and Mars-analog lithofacies - boggle the imagination and present us with great opportunities to explore Earth system behavior. The ICDP-funded workshops dubbed "Deep Dust," held in Oklahoma (USA) in March 2019 (67 participants from nine countries) and Paris (France) in January 2020 (33 participants from eight countries), focused on clarifying the scientific drivers and key sites for coring continuous sections of Permian continental (loess, lacustrine, and associated) strata that preserve high-resolution records. Combined, the two workshops hosted a total of 91 participants representing 14 countries, with broad expertise. Discussions at Deep Dust 1.0 (USA) focused on the primary research questions of paleoclimate, paleoenvironments, and paleoecology of icehouse collapse and the run-up to the Great Dying and both the modern and Permian deep microbial biosphere. Auxiliary science topics included tectonics, induced seismicity, geothermal energy, and planetary science. Deep Dust 1.0 also addressed site selection as well as scientific approaches, logistical challenges, and broader impacts and included a mid-workshop field trip to view the Permian of Oklahoma. Deep Dust 2.0 focused specifically on honing the European target. The Anadarko Basin (Oklahoma) and Paris Basin (France) represent the most promising initial targets to capture complete or near-complete stratigraphic coverage through continental successions that serve as reference points for western and eastern equatorial Pangaea. © 2020 Copernicus GmbH. All rights reserved.
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    Predicting the data structure prior to extreme events from passive observables using echo state network
    (Lausanne : Frontiers Media, 2022) Banerjee, Abhirup; Mishra, Arindam; Dana, Syamal K.; Hens, Chittaranjan; Kapitaniak, Tomasz; Kurths, Jürgen; Marwan, Norbert
    Extreme events are defined as events that largely deviate from the nominal state of the system as observed in a time series. Due to the rarity and uncertainty of their occurrence, predicting extreme events has been challenging. In real life, some variables (passive variables) often encode significant information about the occurrence of extreme events manifested in another variable (active variable). For example, observables such as temperature, pressure, etc., act as passive variables in case of extreme precipitation events. These passive variables do not show any large excursion from the nominal condition yet carry the fingerprint of the extreme events. In this study, we propose a reservoir computation-based framework that can predict the preceding structure or pattern in the time evolution of the active variable that leads to an extreme event using information from the passive variable. An appropriate threshold height of events is a prerequisite for detecting extreme events and improving the skill of their prediction. We demonstrate that the magnitude of extreme events and the appearance of a coherent pattern before the arrival of the extreme event in a time series affect the prediction skill. Quantitatively, we confirm this using a metric describing the mean phase difference between the input time signals, which decreases when the magnitude of the extreme event is relatively higher, thereby increasing the predictability skill.
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    Antarctic ice sheet response to sudden and sustained ice-shelf collapse (ABUMIP)
    (Cambridge : Cambridge University Press, 2020) Sun, Sainan; Pattyn, Frank; Simon, Erika G.; Albrecht, Torsten; Cornford, Stephen; Calov, Reinhard; Dumas, Christophe; Gillet-Chaulet, Fabien; Goelzer, Goelzer; Golledge, Nicholas R.; Greve, Ralf; Hoffman, Matthew J.; Humbert, Angelika; Kazmierczak, Elise; Kleiner, Thomas; Leguy, Gunter R.; Lipscomb, William H.; Martin, Daniel; Morlighem, Mathieu; Nowicki, Sophie; Pollard, David; Price, Stephen; Quiquet, Aurélien; Seroussi, Hélène; Schlemm, Tanja; Sutter, Johannes; van de Wal, Roderik S.W.; Winkelmann, Ricarda; Zhang, Tong
    Antarctica's ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their 'buttressing' effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttressing by investigating the 'end-member' scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1-12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91-5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong function of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments. Copyright © The Author(s) 2020.
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    Ocean warming and acidification may drag down the commercial Arctic cod fishery by 2100
    (San Francisco, California, US : PLOS, 2020) Hänsel, Martin C.; Schmidt, Jörn O.; Stiasny, Martina H.; Stöven, Max T.; Voss, Rudi; Quaas, Martin F.
    The Arctic Ocean is an early warning system for indicators and effects of climate change. We use a novel combination of experimental and time-series data on effects of ocean warming and acidification on the commercially important Northeast Arctic cod (Gadus morhua) to incorporate these physiological processes into the recruitment model of the fish population. By running an ecological-economic optimization model, we investigate how the interaction of ocean warming, acidification and fishing pressure affects the sustainability of the fishery in terms of ecological, economic, social and consumer-related indicators, ranging from present day conditions up to future climate change scenarios. We find that near-term climate change will benefit the fishery, but under likely future warming and acidification this large fishery is at risk of collapse by the end of the century, even with the best adaptation effort in terms of reduced fishing pressure.
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    EEG biomarkers of activation of the lymphatic drainage system of the brain during sleep and opening of the blood-brain barrier
    (Gotenburg : Research Network of Computational and Structural Biotechnology (RNCSB), 2022) Semyachkina-Glushkovskaya, O.V.; Karavaev, A.S.; Prokhorov, M.D.; Runnova, A.E.; Borovkova, E.I.; Ishbulatov, Yu.M.; Hramkov, A.N.; Kulminskiy, D.D.; Semenova, N.I.; Sergeev, K.S.; Slepnev, A.V.; Sitnikova, E.Yu.; Zhuravlev, M.O.; Fedosov, I.V.; Shirokov, A.A.; Blokhina, I.A.; Dubrovski, A.I.; Terskov, A.V.; Khorovodov, A.P.; Ageev, V.B.; Elovenko, D.A.; Evsukova, A.S.; Adushkina, V.V.; Telnova, V.V.; Postnov, D.E.; Penzel, T.U.; Kurths, J.G.
    The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB.
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    A recurrent plot based stochastic nonlinear ray propagation model for underwater signal propagation
    ([London] : IOP, 2020) Haiyang, Yao; Haiyan, Wang; Yong, Xu; Kurths, Juergen
    A stochastic nonlinear ray propagation model is proposed to carry out an exploration of the nonlinear ray theory in underwater signal propagation. The recurrence plot method is proposed to quantify the ray chaos and stochastics to optimize the model. Based on this method, the distribution function of the control parameter d is derived. Experiments and simulations indicate that this stochastic nonlinear ray propagation model provides a good explanation and description on the stochastic frequency shift in underwater signal propagation. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.
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    Maternal mycotoxin exposure and adverse pregnancy outcomes: a systematic review
    (Berlin ; Heidelberg : Springer, 2020) Kyei, Nicholas N.A.; Boakye, Daniel; Gabrysch, Sabine
    Mycotoxin exposure from food occurs globally but is more common in hot humid environments, especially in low-income settings, and might affect pregnancy outcomes. This study aimed to synthesize the evidence from epidemiological studies on the relationship between maternal or fetal exposure to different mycotoxins and the occurrence of adverse pregnancy outcomes. Multiple databases were systematically searched up to December 2018 to identify studies that assessed the association between mycotoxin exposure in pregnant women or fetuses and at least one pregnancy outcome. Studies were appraised and results were synthesized using standard methods for conducting systematic reviews. This review identified and included 17 relevant studies. There is some evidence to suggest that exposure to various Aspergillus mycotoxins (e.g., aflatoxin) during pregnancy may impair intrauterine fetal growth and promote neonatal jaundice. Findings were inconclusive concerning the influence of aflatoxin exposure on perinatal death and preterm birth. Only two studies assessed effects of maternal exposure to Fusarium mycotoxins (e.g., fumonisin) on adverse pregnancy outcomes. These studies found that maternal fumonisin exposure may be associated with hypertensive emergencies in pregnancy and with neural tube defects. Studies using grain farming and weather conditions as a proxy measure for mycotoxin exposure found that such exposure was associated with an increased risk of preterm birth and late-term miscarriage. In conclusion, there is already some evidence to suggest that exposure to mycotoxins during pregnancy may have detrimental effects on pregnancy outcomes. However, given the limited number of studies, especially on effects of Fusarium mycotoxins, more studies are needed for a more comprehensive understanding of the effects of different mycotoxins on maternal and fetal health and to guide public health policies and interventions. © 2020, The Author(s).
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    Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP6 models
    (Göttingen : Copernicus, 2021) Katzenberger, Anja; Schewe, Jacob; Pongratz, Julia; Levermann, Anders
    The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP6 are of interest. Here, we analyze 32 models of the latest CMIP6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with a high agreement between the models independent of the SSP if global warming is the dominant forcing of the monsoon dynamics as it is in the 21st century; the multi-model mean for JJAS projects an increase of 0.33 mm d−1 and 5.3 % per kelvin of global warming. This is significantly higher than in the CMIP5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP6 simulations largely confirm the findings from CMIP5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.
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    Optimal carbon taxation and horizontal equity: A welfare-theoretic approach with application to German household data
    (Amsterdam : Elsevier, 2022) Hänsel, Martin C.; Franks, Max; Kalkuhl, Matthias; Edenhofer, Ottmar
    We develop a model of optimal taxation and redistribution under an ambitious climate target. We take into account vertical income differences, but also explicitly capture horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon and labor taxes, transfers and energy subsidies, we investigate analytically how vertical and horizontal inequality is considered in the welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal and show that redistribution of carbon tax revenues via household-specific transfers is the first-best policy. Under plausible assumptions on inequality aversion, transfers to energy-intensive households should be about five times higher than transfers to energy-efficient households. Equal per-capita transfers do not require to observe households’ efficiency type, but increase equity-weighted mitigation costs by around 5 percent compared to the first-best. Mitigation costs increase by less, if the government can implement a uniform clean energy subsidy or household-specific tax-subsidy schemes on energy consumption and labor income that target heterogeneous energy efficiencies. Horizontal equity concerns may therefore constitute a new second-best rationale for clean energy policies or differentiated energy taxes.