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Blockchain and cryptocurrencies have recently captured the interest of academics and those in industry. Cryptocurrencies are essentially digital currencies that use blockchain technology and cryptography to facilitate secure and anonymous transactions. The cryptocurrency market is currently worth over $500 billion. Many institutions and countries are starting to understand and implement the idea of cryptocurrencies in their business models. This Special Issue will provide a collection of papers from leading experts in the area of blockchain and cryptocurrencies. The topics covered in this Special Issue will include but are not limited to the following: academic research on blockchain and cryptocurrencies; industrial applications of blockchain and cryptocurrencies; applications of fintech in academia and industry; the economics of blockchain technology, and the financial analysis and risk management with cryptocurrencies.

cryptocurrencies --- connectedness --- spill overs --- spectral analysis --- time-frequency-dynamic --- Bitcoin --- cryptocurrency --- spillover risks --- Copulas --- Student’s-t --- survey --- bitcoin --- efficient market hypothesis --- ARIMA --- artificial neural network --- static forecast --- contagion effect --- detrended cross-correlation analysis --- liquidity --- Ethereum --- market liquidity --- Hurst exponent --- high frequency --- fraud --- algorithms --- correlations --- impact --- risks --- regulation --- blockchain --- autoregression --- time-series analysis --- simulation --- predictive modes --- endogenous --- exogenous variables --- Blockchain --- Cryptocurrencies --- Digital Currencies --- Risk management --- Financial analysis

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Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.

artificial neural network --- downscaling --- innovative methods --- reservoir inflow forecasting --- simulation --- extreme events --- climate variability --- sparse monitoring network --- weighted mean analogue --- sampling errors --- precipitation --- drought indices --- discrete wavelet --- SWSI --- hyetograph --- trends --- climate change --- SIAP --- Kabul river basin --- Hurst exponent --- extreme rainfall --- evolutionary strategy --- the Cauca River --- hydrological drought --- global warming --- least square support vector regression --- polynomial normal transform --- TRMM --- satellite data --- Fiji --- heavy storm --- flood regime --- compound events --- random forest --- uncertainty --- seasonal climate forecast --- INDC pledge --- Pakistan --- wavelet artificial neural network --- HBV model --- temperature --- APCC Multi-Model Ensemble --- meteorological drought --- flow regime --- high resolution --- rainfall --- clausius-clapeyron scaling --- statistical downscaling --- ENSO --- forecasting --- variation analogue --- machine learning --- extreme rainfall analysis --- hydrological extremes --- multivariate modeling --- monsoon --- non-stationary --- support vector machine --- ANN model --- stretched Gaussian distribution --- drought prediction --- non-normality --- statistical analysis --- extreme precipitation exposure --- drought analysis --- extreme value theory --- streamflow --- flood management

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In geodesy and geoinformation science, as well as in many other technical disciplines, it is often not possible to directly determine the desired target quantities. Therefore, the unknown parameters must be linked with the measured values by a mathematical model which consists of the functional and the stochastic models. The functional model describes the geometrical–physical relationship between the measurements and the unknown parameters. This relationship is sufficiently well known for most applications. With regard to the stochastic model, two problem domains of fundamental importance arise: 1. How can stochastic models be set up as realistically as possible for the various geodetic observation methods and sensor systems? 2. How can the stochastic information be adequately considered in appropriate least squares adjustment models? Further questions include the interpretation of the stochastic properties of the computed target values with regard to precision and reliability and the use of the results for the detection of outliers in the input data (measurements). In this Special Issue, current research results on these general questions are presented in ten peer-reviewed articles. The basic findings can be applied to all technical scientific fields where measurements are used for the determination of parameters to describe geometric or physical phenomena.

EM-algorithm --- multi-GNSS --- PPP --- process noise --- observation covariance matrix --- extended Kalman filter --- machine learning --- GNSS phase bias --- sequential quasi-Monte Carlo --- variance reduction --- autoregressive processes --- ARMA-process --- colored noise --- continuous process --- covariance function --- stochastic modeling --- time series --- elementary error model --- terrestrial laser scanning --- variance-covariance matrix --- terrestrial laser scanner --- stochastic model --- B-spline approximation --- Hurst exponent --- fractional Gaussian noise --- generalized Hurst estimator --- very long baseline interferometry --- sensitivity --- internal reliability --- robustness --- CONT14 --- Errors-In-Variables Model --- Total Least-Squares --- prior information --- collocation vs. adjustment --- mean shift model --- variance inflation model --- outlierdetection --- likelihood ratio test --- Monte Carlo integration --- data snooping --- GUM analysis --- geodetic network adjustment --- stochastic properties --- random number generator --- Monte Carlo simulation --- 3D straight line fitting --- total least squares (TLS) --- weighted total least squares (WTLS) --- nonlinear least squares adjustment --- direct solution --- singular dispersion matrix --- laser scanning data

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Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trapped—the current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be built—only on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era.

energy --- economic growth --- output elasticities --- entropy production --- emissions --- optimization --- speculative attacks --- currency crisis --- neural networks --- deep learning --- Quantum-Inspired Neural Network --- traveling salesman problem --- simulated annealing technique --- kinetic exchange model --- Gini index --- Kolkata index --- minority game --- Kolkata Paise Restaurant problem --- time series analysis --- cross-correlations --- power law classification scheme --- network analysis --- globalisation --- entropy --- portfolio optimization --- regularization --- renormalization --- econophysics --- highway freight transportation --- radiation model --- transportation network --- network diversity --- power law --- economic development --- decision-making --- bounded rationality --- complexity economics --- information-theory --- maximum entropy principle --- quantal response statistical equilibrium --- correlation coefficient --- detrended cross-correlation analysis --- COVID-19 --- mobility indices --- random geometry --- risk measurement --- disordered systems --- replica theory --- return distributions --- power-law tails --- stretched exponentials --- q-Gaussians --- financial markets --- financial complexity --- collective intelligence --- emergent property --- stock correlation --- lexical evolution of econophysics --- text as data --- correspondence analysis --- long-range memory --- 1/f noise --- absolute value estimator --- anomalous diffusion --- ARFIMA --- first-passage times --- fractional Lèvy stable motion --- Higuchi’s method --- mean squared displacement --- multiplicative point process --- correlation filtering --- minimal spanning tree --- planar maximally filtered graph --- topological data analysis --- SGX --- TAIEX --- complex systems --- ecological economics --- urban–regional economics --- income distribution --- financial market dynamics --- income tax --- tax deduction --- income redistribution --- government transfer --- government dependency --- poverty line --- basic income guarantee --- effective tax rate --- balanced budget --- elastic tax --- Cantor set --- fractals --- homeomorphism --- detrended fluctuation analysis --- Hurst exponent --- continuous time random walk --- intertrade times --- volatility clustering --- local transfer entropy --- long-short-term-memory --- Bitcoin --- cryptocurrencies --- multiscale analysis --- detrended cross-correlations --- covariance matrices --- copulas --- high-frequency trading --- market stability --- agent-based models --- structural entropy --- Economic Freedom of the World index --- Index of Economic Freedom --- rank-size law technique --- power law behaviour --- exponential behaviour --- multiscale partition function --- multifractal analysis --- company market --- export readiness --- internationalization --- options pricing --- mortality --- companies --- start-up --- FTSE100 --- Gompertz --- MinMax --- survival probability distribution --- high-frequency trader --- multivariate Hawkes process --- forex market --- wealth distribution --- kinetic models --- wealth inequalities --- compartmental epidemic modelling --- vaccination campaign --- flash crash --- systemic risk --- financial networks --- high frequency trading --- market microstructure --- phase transition --- criticality --- dynamics of complex networks --- cascading failure --- network science --- economic complexity --- relatedness --- products and services --- planar graph --- partial correlation --- discounting --- bond pricing --- real interest rates --- calendar anomalies --- day-of-the-week effect --- market indices --- multifractal detrended fluctuation analysis --- n/a --- fractional Lèvy stable motion --- Higuchi's method --- urban-regional economics