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Nowadays, more and more people realize the importance of global sustainability. Also, there has been an increasing number of quantitative studies investigating the connection between climate change and human societies in academia. Given this background, the Atmosphere Special Issue “Climate Change, Climatic Extremes, and Human Societies in the Past” aimed to highlight the major aspects of the climate-society nexus in ancient and recent human history. There are eight papers based on quantitative approaches to illustrate different forms of climate-society nexus in ancient, historical, and contemporary periods. Regarding ancient periods, the interconnection among climate, agriculture, and human societies is focused. Regarding historical periods, the non-linear and complex relationship between climate change and the positive checks (wars, famines, and epidemics) in historical China and pre-industrial Europe is revealed. Regarding contemporary periods, the papers focus on weather-related phenomena that significantly affect human societies. The complexity of those phenomena is also highlighted. The associated findings can help human societies to mitigate the adverse impacts of weather extremes better. This special issue contributes to the field of quantitative analysis of the climate-society nexus, both theoretically and methodologically, which could facilitate a more fruitful discussion about the climate-society nexus.
Research & information: general --- soil moisture-temperature coupling --- heatwaves --- multiple time scales --- correlation dimension method --- Geogdetector method --- interaction effect --- multi-scale --- climate change --- war --- imperial China --- Global Moran's I --- Emerging Hot Spot Analysis --- plague --- direct and indirect effects --- Structural Equation Modelling --- drought --- regional interaction --- North China Famine of 1876-1879 --- human diet --- hierarchy --- bronze age --- carbon and nitrogen stable isotope ratios --- decision tree --- random forest --- precipitation prediction --- machine learning --- Yangtze River valley --- Yellow River valley --- rice cultivation --- millet cultivation --- precipitation --- Neolithic China --- soil moisture-temperature coupling --- heatwaves --- multiple time scales --- correlation dimension method --- Geogdetector method --- interaction effect --- multi-scale --- climate change --- war --- imperial China --- Global Moran's I --- Emerging Hot Spot Analysis --- plague --- direct and indirect effects --- Structural Equation Modelling --- drought --- regional interaction --- North China Famine of 1876-1879 --- human diet --- hierarchy --- bronze age --- carbon and nitrogen stable isotope ratios --- decision tree --- random forest --- precipitation prediction --- machine learning --- Yangtze River valley --- Yellow River valley --- rice cultivation --- millet cultivation --- precipitation --- Neolithic China
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Nowadays, more and more people realize the importance of global sustainability. Also, there has been an increasing number of quantitative studies investigating the connection between climate change and human societies in academia. Given this background, the Atmosphere Special Issue “Climate Change, Climatic Extremes, and Human Societies in the Past” aimed to highlight the major aspects of the climate-society nexus in ancient and recent human history. There are eight papers based on quantitative approaches to illustrate different forms of climate-society nexus in ancient, historical, and contemporary periods. Regarding ancient periods, the interconnection among climate, agriculture, and human societies is focused. Regarding historical periods, the non-linear and complex relationship between climate change and the positive checks (wars, famines, and epidemics) in historical China and pre-industrial Europe is revealed. Regarding contemporary periods, the papers focus on weather-related phenomena that significantly affect human societies. The complexity of those phenomena is also highlighted. The associated findings can help human societies to mitigate the adverse impacts of weather extremes better. This special issue contributes to the field of quantitative analysis of the climate-society nexus, both theoretically and methodologically, which could facilitate a more fruitful discussion about the climate-society nexus.
Research & information: general --- soil moisture–temperature coupling --- heatwaves --- multiple time scales --- correlation dimension method --- Geogdetector method --- interaction effect --- multi-scale --- climate change --- war --- imperial China --- Global Moran’s I --- Emerging Hot Spot Analysis --- plague --- direct and indirect effects --- Structural Equation Modelling --- drought --- regional interaction --- North China Famine of 1876–1879 --- human diet --- hierarchy --- bronze age --- carbon and nitrogen stable isotope ratios --- decision tree --- random forest --- precipitation prediction --- machine learning --- Yangtze River valley --- Yellow River valley --- rice cultivation --- millet cultivation --- precipitation --- Neolithic China --- n/a --- soil moisture-temperature coupling --- Global Moran's I --- North China Famine of 1876-1879
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Nowadays, more and more people realize the importance of global sustainability. Also, there has been an increasing number of quantitative studies investigating the connection between climate change and human societies in academia. Given this background, the Atmosphere Special Issue “Climate Change, Climatic Extremes, and Human Societies in the Past” aimed to highlight the major aspects of the climate-society nexus in ancient and recent human history. There are eight papers based on quantitative approaches to illustrate different forms of climate-society nexus in ancient, historical, and contemporary periods. Regarding ancient periods, the interconnection among climate, agriculture, and human societies is focused. Regarding historical periods, the non-linear and complex relationship between climate change and the positive checks (wars, famines, and epidemics) in historical China and pre-industrial Europe is revealed. Regarding contemporary periods, the papers focus on weather-related phenomena that significantly affect human societies. The complexity of those phenomena is also highlighted. The associated findings can help human societies to mitigate the adverse impacts of weather extremes better. This special issue contributes to the field of quantitative analysis of the climate-society nexus, both theoretically and methodologically, which could facilitate a more fruitful discussion about the climate-society nexus.
soil moisture–temperature coupling --- heatwaves --- multiple time scales --- correlation dimension method --- Geogdetector method --- interaction effect --- multi-scale --- climate change --- war --- imperial China --- Global Moran’s I --- Emerging Hot Spot Analysis --- plague --- direct and indirect effects --- Structural Equation Modelling --- drought --- regional interaction --- North China Famine of 1876–1879 --- human diet --- hierarchy --- bronze age --- carbon and nitrogen stable isotope ratios --- decision tree --- random forest --- precipitation prediction --- machine learning --- Yangtze River valley --- Yellow River valley --- rice cultivation --- millet cultivation --- precipitation --- Neolithic China --- n/a --- soil moisture-temperature coupling --- Global Moran's I --- North China Famine of 1876-1879
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Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.
Research & information: general --- Mathematics & science --- autonomic nervous function --- heart rate variability (HRV) --- baroreflex sensitivity (BRS) --- photo-plethysmo-graphy (PPG) --- digital volume pulse (DVP) --- percussion entropy index (PEI) --- heart rate variability --- posture --- entropy --- complexity --- cognitive task --- sample entropy --- brain functional networks --- dynamic functional connectivity --- static functional connectivity --- K-means clustering algorithm --- fragmentation --- aging in human population --- factor analysis --- support vector machines classification --- Sampen --- cross-entropy --- autonomic nervous system --- heart rate --- blood pressure --- hypobaric hypoxia --- rehabilitation medicine --- labor --- fetal heart rate --- data compression --- complexity analysis --- nonlinear analysis --- preterm --- Alzheimer’s disease --- brain signals --- single-channel analysis --- biomarker --- refined composite multiscale entropy --- central autonomic network --- interconnectivity --- ECG --- ectopic beat --- baroreflex --- self-organized criticality --- vasovagal syncope --- Zipf’s law --- multifractality --- multiscale complexity --- detrended fluctuation analysis --- self-similarity --- sEMG --- approximate entropy --- fuzzy entropy --- fractal dimension --- recurrence quantification analysis --- correlation dimension --- largest Lyapunov exponent --- time series analysis --- relative consistency --- event-related de/synchronization --- motor imagery --- vector quantization --- information dynamics --- partial information decomposition --- conditional transfer entropy --- network physiology --- multivariate time series analysis --- State–space models --- vector autoregressive model --- penalized regression techniques --- linear prediction --- fNIRS --- brain dynamics --- mental arithmetics --- multiscale --- cardiovascular system --- brain --- information flow --- autonomic nervous function --- heart rate variability (HRV) --- baroreflex sensitivity (BRS) --- photo-plethysmo-graphy (PPG) --- digital volume pulse (DVP) --- percussion entropy index (PEI) --- heart rate variability --- posture --- entropy --- complexity --- cognitive task --- sample entropy --- brain functional networks --- dynamic functional connectivity --- static functional connectivity --- K-means clustering algorithm --- fragmentation --- aging in human population --- factor analysis --- support vector machines classification --- Sampen --- cross-entropy --- autonomic nervous system --- heart rate --- blood pressure --- hypobaric hypoxia --- rehabilitation medicine --- labor --- fetal heart rate --- data compression --- complexity analysis --- nonlinear analysis --- preterm --- Alzheimer’s disease --- brain signals --- single-channel analysis --- biomarker --- refined composite multiscale entropy --- central autonomic network --- interconnectivity --- ECG --- ectopic beat --- baroreflex --- self-organized criticality --- vasovagal syncope --- Zipf’s law --- multifractality --- multiscale complexity --- detrended fluctuation analysis --- self-similarity --- sEMG --- approximate entropy --- fuzzy entropy --- fractal dimension --- recurrence quantification analysis --- correlation dimension --- largest Lyapunov exponent --- time series analysis --- relative consistency --- event-related de/synchronization --- motor imagery --- vector quantization --- information dynamics --- partial information decomposition --- conditional transfer entropy --- network physiology --- multivariate time series analysis --- State–space models --- vector autoregressive model --- penalized regression techniques --- linear prediction --- fNIRS --- brain dynamics --- mental arithmetics --- multiscale --- cardiovascular system --- brain --- information flow
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Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.
autonomic nervous function --- heart rate variability (HRV) --- baroreflex sensitivity (BRS) --- photo-plethysmo-graphy (PPG) --- digital volume pulse (DVP) --- percussion entropy index (PEI) --- heart rate variability --- posture --- entropy --- complexity --- cognitive task --- sample entropy --- brain functional networks --- dynamic functional connectivity --- static functional connectivity --- K-means clustering algorithm --- fragmentation --- aging in human population --- factor analysis --- support vector machines classification --- Sampen --- cross-entropy --- autonomic nervous system --- heart rate --- blood pressure --- hypobaric hypoxia --- rehabilitation medicine --- labor --- fetal heart rate --- data compression --- complexity analysis --- nonlinear analysis --- preterm --- Alzheimer’s disease --- brain signals --- single-channel analysis --- biomarker --- refined composite multiscale entropy --- central autonomic network --- interconnectivity --- ECG --- ectopic beat --- baroreflex --- self-organized criticality --- vasovagal syncope --- Zipf’s law --- multifractality --- multiscale complexity --- detrended fluctuation analysis --- self-similarity --- sEMG --- approximate entropy --- fuzzy entropy --- fractal dimension --- recurrence quantification analysis --- correlation dimension --- largest Lyapunov exponent --- time series analysis --- relative consistency --- event-related de/synchronization --- motor imagery --- vector quantization --- information dynamics --- partial information decomposition --- conditional transfer entropy --- network physiology --- multivariate time series analysis --- State–space models --- vector autoregressive model --- penalized regression techniques --- linear prediction --- fNIRS --- brain dynamics --- mental arithmetics --- multiscale --- cardiovascular system --- brain --- information flow
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There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
Information technology industries --- volatility clustering --- Baidu Index --- information demand --- generalized autoregressive conditional heteroscedasticity model (GARCH) --- mixture of distribution hypothesis --- speculation --- land acquisition --- motivation --- real estate --- development --- Ethiopia --- systemic risk --- macroprudential policy --- agent-based modelling --- inequality --- central-banking --- information transfer --- transfer entropy --- stock markets --- econophysics --- complexity science --- information theory --- economic complexity --- evolutionary dynamics --- network theory --- leveraged trading --- stock price crash risk --- threshold effect --- complexity in stock market --- entropy economics --- non-extensive cross-entropy econometrics --- non-ergodic ill-behaved inverse problems --- general system theory --- non-linear dynamics --- complex adaptive systems --- homo oeconomicus --- edge of chaos --- complexity economics --- pricing constraint --- IPO timing --- dynamic game model --- real option --- complexity of IPOs --- financial institution --- complex network --- jump volatility --- entropy weight TOPSIS --- structural entropy --- stock market --- EMD --- cluster-entropy --- Shannon-entropy --- financial markets --- time series --- dynamics --- Tsallis entropy --- copula functions --- cross-shareholding network --- finance --- cryptocurrencies --- multivariate transfer entropy --- complex networks --- liquidity proxy --- liquidity benchmark --- volatility estimate --- correlation coefficient --- partial determination --- mutual information --- forecasting market risk --- value at risk --- extreme returns --- peaks over threshold --- self-exciting point process --- discrete-time models --- generalized Pareto distribution --- dynamical complexity --- universal complexity measure --- irreversible processes --- entropies --- entropic susceptibilities --- complex systems --- multifractal analysis --- detrended cross-correlations --- minimal spanning tree --- wealth condensation --- agent-based computational economics --- bargaining --- gain function --- macroeconomics --- innovative activity --- manufacturing industry --- conjunctural movements --- cybernetics --- feedback loops --- correspondence analysis --- Polish Green Island effect --- Red Queen effect --- Kondratieff waves --- power law --- Zipf law --- gender productivity gap --- fake news --- rumor spreading --- Nash equilibrium --- evolutionarily stable strategies --- evolutionary information search dynamics --- nonlinear dynamics --- chaos --- time series analysis --- stock exchange market --- Lyapunov --- recurrence plots --- BDS --- correlation dimension --- GARCH model --- measure of economic development --- websites --- public administration sector --- municipality --- four-colour theorem --- prosumption --- platforms for participation --- location quotient --- dual graph --- Euler characteristic --- volatility clustering --- Baidu Index --- information demand --- generalized autoregressive conditional heteroscedasticity model (GARCH) --- mixture of distribution hypothesis --- speculation --- land acquisition --- motivation --- real estate --- development --- Ethiopia --- systemic risk --- macroprudential policy --- agent-based modelling --- inequality --- central-banking --- information transfer --- transfer entropy --- stock markets --- econophysics --- complexity science --- information theory --- economic complexity --- evolutionary dynamics --- network theory --- leveraged trading --- stock price crash risk --- threshold effect --- complexity in stock market --- entropy economics --- non-extensive cross-entropy econometrics --- non-ergodic ill-behaved inverse problems --- general system theory --- non-linear dynamics --- complex adaptive systems --- homo oeconomicus --- edge of chaos --- complexity economics --- pricing constraint --- IPO timing --- dynamic game model --- real option --- complexity of IPOs --- financial institution --- complex network --- jump volatility --- entropy weight TOPSIS --- structural entropy --- stock market --- EMD --- cluster-entropy --- Shannon-entropy --- financial markets --- time series --- dynamics --- Tsallis entropy --- copula functions --- cross-shareholding network --- finance --- cryptocurrencies --- multivariate transfer entropy --- complex networks --- liquidity proxy --- liquidity benchmark --- volatility estimate --- correlation coefficient --- partial determination --- mutual information --- forecasting market risk --- value at risk --- extreme returns --- peaks over threshold --- self-exciting point process --- discrete-time models --- generalized Pareto distribution --- dynamical complexity --- universal complexity measure --- irreversible processes --- entropies --- entropic susceptibilities --- complex systems --- multifractal analysis --- detrended cross-correlations --- minimal spanning tree --- wealth condensation --- agent-based computational economics --- bargaining --- gain function --- macroeconomics --- innovative activity --- manufacturing industry --- conjunctural movements --- cybernetics --- feedback loops --- correspondence analysis --- Polish Green Island effect --- Red Queen effect --- Kondratieff waves --- power law --- Zipf law --- gender productivity gap --- fake news --- rumor spreading --- Nash equilibrium --- evolutionarily stable strategies --- evolutionary information search dynamics --- nonlinear dynamics --- chaos --- time series analysis --- stock exchange market --- Lyapunov --- recurrence plots --- BDS --- correlation dimension --- GARCH model --- measure of economic development --- websites --- public administration sector --- municipality --- four-colour theorem --- prosumption --- platforms for participation --- location quotient --- dual graph --- Euler characteristic
Choose an application
There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
volatility clustering --- Baidu Index --- information demand --- generalized autoregressive conditional heteroscedasticity model (GARCH) --- mixture of distribution hypothesis --- speculation --- land acquisition --- motivation --- real estate --- development --- Ethiopia --- systemic risk --- macroprudential policy --- agent-based modelling --- inequality --- central-banking --- information transfer --- transfer entropy --- stock markets --- econophysics --- complexity science --- information theory --- economic complexity --- evolutionary dynamics --- network theory --- leveraged trading --- stock price crash risk --- threshold effect --- complexity in stock market --- entropy economics --- non-extensive cross-entropy econometrics --- non-ergodic ill-behaved inverse problems --- general system theory --- non-linear dynamics --- complex adaptive systems --- homo oeconomicus --- edge of chaos --- complexity economics --- pricing constraint --- IPO timing --- dynamic game model --- real option --- complexity of IPOs --- financial institution --- complex network --- jump volatility --- entropy weight TOPSIS --- structural entropy --- stock market --- EMD --- cluster-entropy --- Shannon-entropy --- financial markets --- time series --- dynamics --- Tsallis entropy --- copula functions --- cross-shareholding network --- finance --- cryptocurrencies --- multivariate transfer entropy --- complex networks --- liquidity proxy --- liquidity benchmark --- volatility estimate --- correlation coefficient --- partial determination --- mutual information --- forecasting market risk --- value at risk --- extreme returns --- peaks over threshold --- self-exciting point process --- discrete-time models --- generalized Pareto distribution --- dynamical complexity --- universal complexity measure --- irreversible processes --- entropies --- entropic susceptibilities --- complex systems --- multifractal analysis --- detrended cross-correlations --- minimal spanning tree --- wealth condensation --- agent-based computational economics --- bargaining --- gain function --- macroeconomics --- innovative activity --- manufacturing industry --- conjunctural movements --- cybernetics --- feedback loops --- correspondence analysis --- Polish Green Island effect --- Red Queen effect --- Kondratieff waves --- power law --- Zipf law --- gender productivity gap --- fake news --- rumor spreading --- Nash equilibrium --- evolutionarily stable strategies --- evolutionary information search dynamics --- nonlinear dynamics --- chaos --- time series analysis --- stock exchange market --- Lyapunov --- recurrence plots --- BDS --- correlation dimension --- GARCH model --- measure of economic development --- websites --- public administration sector --- municipality --- four-colour theorem --- prosumption --- platforms for participation --- location quotient --- dual graph --- Euler characteristic --- n/a
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