The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform

Masatoshi Saitou - One of the best experts on this subject based on the ideXlab platform.

Miklós S.z. Kellermayer - One of the best experts on this subject based on the ideXlab platform.

  • Label-free Multiscale Transport Imaging of the Living Cell.
    Biophysical journal, 2018
    Co-Authors: Szabolcs Osváth, Levente Herényi, Gergely Agócs, Katalin Kis-petik, Miklós S.z. Kellermayer
    Abstract:

    Abstract The living cell is characterized by a myriad of parallel intracellular transport processes. Simultaneously capturing their global features across multiple temporal and spatial scales is a nearly unsurmountable task. Here we present a method that enables the microscopic imaging of the entire spectrum of intracellular transport on a broad time scale without the need for prior labeling. We show that from the time-dependent fluctuation of pixel intensity, in either bright-field or phase-contrast microscopic images, a scaling factor can be derived that reflects the local Hurst Coefficient (H), the value of which reveals the microscopic mechanisms of intracellular motion. The Hurst Coefficient image of the interphase cell displays an unexpected, overwhelming superdiffusion (H > 0.5) in the cytoplasm and subdiffusion (H

  • Transport Imaging of Living Cells
    Biophysical Journal, 2016
    Co-Authors: Szabolcs Osváth, Levente Herényi, Gergely Agócs, Katalin Kis Petik, Miklós S.z. Kellermayer
    Abstract:

    Living cells are out of equilibrium biological systems in which active and passive transports are literally of vital importance. Intracellular motion of a few types of particles has been studied before, but how these motions fit into the broader context of all physiological transports of the cell is still unclear. We used an unselective method - phase contrast imaging - to detect virtually all intracellular movements. Fourier analysis of movies of living HEP2 cells shows that cellular motions lack a well defined characteristic time. Movements observed in the 0.5 s to 655 s range were very information rich, showing self-similar temporal behavior in all locations inside the cell. To grab this information, a transport image of the living cell was constructed by representing the locally observed Hurst Coefficient of the motions as a stand alone image. The cytoplasm of the cells was found to be dominated by superdiffusion driven by active transport. Brownian diffusion and subdiffusion was also observed, mostly inside the nucleus. We believe that the abundance of subdiffusion reports in the literature arises from the fact that the observed test particles or molecules were not integral part of the intracellular physiology. We propose the use of unselective microscopy methods and Hurst Coefficient transport imaging as an effective tool to visualize physiological transport processes of living cells.

Deepak Jhajharia - One of the best experts on this subject based on the ideXlab platform.

  • Streamflow trend analysis by considering autocorrelation structure, long-term persistence, and Hurst Coefficient in a semi-arid region of Iran
    Theoretical and Applied Climatology, 2017
    Co-Authors: Reza Zamani, Rasoul Mirabbasi, Sajjad Abdollahi, Deepak Jhajharia
    Abstract:

    Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst Coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z -statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.

Szabolcs Osváth - One of the best experts on this subject based on the ideXlab platform.

  • Label-free Multiscale Transport Imaging of the Living Cell.
    Biophysical journal, 2018
    Co-Authors: Szabolcs Osváth, Levente Herényi, Gergely Agócs, Katalin Kis-petik, Miklós S.z. Kellermayer
    Abstract:

    Abstract The living cell is characterized by a myriad of parallel intracellular transport processes. Simultaneously capturing their global features across multiple temporal and spatial scales is a nearly unsurmountable task. Here we present a method that enables the microscopic imaging of the entire spectrum of intracellular transport on a broad time scale without the need for prior labeling. We show that from the time-dependent fluctuation of pixel intensity, in either bright-field or phase-contrast microscopic images, a scaling factor can be derived that reflects the local Hurst Coefficient (H), the value of which reveals the microscopic mechanisms of intracellular motion. The Hurst Coefficient image of the interphase cell displays an unexpected, overwhelming superdiffusion (H > 0.5) in the cytoplasm and subdiffusion (H

  • Transport Imaging of Living Cells
    Biophysical Journal, 2016
    Co-Authors: Szabolcs Osváth, Levente Herényi, Gergely Agócs, Katalin Kis Petik, Miklós S.z. Kellermayer
    Abstract:

    Living cells are out of equilibrium biological systems in which active and passive transports are literally of vital importance. Intracellular motion of a few types of particles has been studied before, but how these motions fit into the broader context of all physiological transports of the cell is still unclear. We used an unselective method - phase contrast imaging - to detect virtually all intracellular movements. Fourier analysis of movies of living HEP2 cells shows that cellular motions lack a well defined characteristic time. Movements observed in the 0.5 s to 655 s range were very information rich, showing self-similar temporal behavior in all locations inside the cell. To grab this information, a transport image of the living cell was constructed by representing the locally observed Hurst Coefficient of the motions as a stand alone image. The cytoplasm of the cells was found to be dominated by superdiffusion driven by active transport. Brownian diffusion and subdiffusion was also observed, mostly inside the nucleus. We believe that the abundance of subdiffusion reports in the literature arises from the fact that the observed test particles or molecules were not integral part of the intracellular physiology. We propose the use of unselective microscopy methods and Hurst Coefficient transport imaging as an effective tool to visualize physiological transport processes of living cells.

Demetris Koutsoyiannis - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic similarities between the microscale of turbulence and hydro-meteorological processes
    Hydrological Sciences Journal, 2016
    Co-Authors: Panayiotis Dimitriadis, Demetris Koutsoyiannis, Panos Papanicolaou
    Abstract:

    ABSTRACTTurbulence is considered to generate and drive most geophysical processes. The simplest case is isotropic turbulence. In this paper, the most common three-dimensional power-spectrum-based models of isotropic turbulence are studied in terms of their stochastic properties. Such models often have a high order of complexity, lack stochastic interpretation and violate basic stochastic asymptotic properties, such as the theoretical limits of the Hurst Coefficient, when Hurst-Kolmogorov behaviour is observed. A simpler and robust model (which incorporates self-similarity structures, e.g. fractal dimension and Hurst Coefficient) is proposed using a climacogram-based stochastic framework and tested over high-resolution observational data of laboratory scale as well as hydro-meteorological observations of wind speed and precipitation intensities. Expressions of other stochastic tools such as the autocovariance and power spectrum are also produced from the model and show agreement with data. Finally, uncerta...

  • Stochastic analysis and simulation of hydrometeorological processes for optimizing hybrid renewable energy systems
    2013
    Co-Authors: Georgios Tsekouras, Christos Ioannou, Andreas Efstratiadis, Demetris Koutsoyiannis
    Abstract:

    The drawbacks of conventional energy sources including their negative environmental impacts emphasize the need to integrate renewable energy sources into energy balance. However, the renewable sources strongly depend on time varying and uncertain hydrometeorological processes, including wind speed, sunshine duration and solar radiation. To study the design and management of hybrid energy systems we investigate the stochastic properties of these natural processes, including possible long-term persistence. We use wind speed and sunshine duration time series retrieved from a European database of daily records and we estimate representative values of the Hurst Coefficient for both variables. We conduct simultaneous generation of synthetic time series of wind speed and sunshine duration, on yearly, monthly and daily scale. To this we use the Castalia software system which performs multivariate stochastic simulation. Using these time series as input, we perform stochastic simulation of an autonomous hypothetical hybrid renewable energy system and optimize its performance using genetic algorithms. For the system design we optimize the sizing of the system in order to satisfy the energy demand with high reliability also minimizing the cost. While the simulation scale is the daily, a simple method allows utilizing the subdaily distribution of the produced wind power. Various scenarios are assumed in order to examine the influence of input parameters, such as the Hurst Coefficient, and design parameters such as the photovoltaic panel angle.

  • The Hurst Phenomenon and Monte Carlo Simulation to Forecast Reliability of an Australian Reservoir
    2006
    Co-Authors: Graeme Cox, Crispin Smythe, Demetris Koutsoyiannis
    Abstract:

    The issue of water supply reliability from Australian reservoirs has recently been the subject of increased scientific and media debate. 'Drought Persistence' or prolonged sequences of low inflows has driven reservoirs to seriously low levels. Statistical justification for these persistent droughts is often difficult to find if classical statistics and typical stochastic approaches are used. Therefore persistent droughts may be overlooked in reliability of supply calculations. This can result in dramatically underestimated risk of failure. The Hurst phenomenon offers a consistent basis to remedy this and the Hurst Coefficient can be a simple measure to quantify the amount of persistence in a time series. For this study, the Hurst Coefficient was calculated for the historical flow data of the Boyne River, Queensland. Based on the Coefficient and the probability distribution of the historical inflow data, synthetic reservoir inflow sequences were generated preserving the persistence. Using this data and Monte Carlo simulation, a tool was developed to forecast the reliability of supply into the future from the current storage level. This is used for planning risk reduction strategies by providing valuable information such as the lead-time available to implement contingencies.

  • A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series
    Water Resources Research, 2000
    Co-Authors: Demetris Koutsoyiannis
    Abstract:

    A generalized framework for single-variate and multivariate simulation and forecasting problems in stochastic hydrology is proposed. It is appropriate for short-term or long-term memory processes and preserves the Hurst Coefficient even in multivariate processes with a different Hurst Coefficient in each location. Simultaneously, it explicitly preserves the Coefficients of skewness of the processes. The proposed framework incorporates short-memory (autoregressive moving average) and long-memory (fractional Gaussian noise) models, considering them as special instances of a parametrically defined generalized autocovariance function, more comprehensive than those used in these classes of models. The generalized autocovariance function is then implemented in a generalized moving average generating scheme that yields a new time-symmetric (backward-forward) representation, whose advantages are studied. Fast algorithms for computation of internal parameters of the generating scheme are developed, appropriate for problems including even thousands of such parameters. The proposed generating scheme is also adapted through a generalized methodology to perform in forecast mode, in addition to simulation mode. Finally, a specific form of the model for problems where the autocorrelation function can be defined only for a certain finite number of lags is also studied. Several illustrations are included to clarify the features and the performance of the components of the proposed framework.