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The importance of evapotranspiration is well-established in different disciplines such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. The objective of this Special Issue is to define and discuss several ET terms, including potential, reference, and actual (crop) ET, and present a wide spectrum of innovative research papers and case studies.

evapotranspiration --- machine learning --- local --- spatial --- subhumid climate --- agricultural drought --- drought characteristics --- evapotranspiration deficit index --- parameter sensitivity --- temporal scale sensitivity --- water stress anomaly --- interception --- linear storage model --- evaporation --- cover crop --- water balance --- faba bean --- GK2A/AMI --- artificial neural network --- Korean Peninsula --- CWSI --- UAV --- remote sensing --- micrometeorological data --- spatial IRT measurements --- crop irrigation scheduling and management --- infrared radiometer sensors --- real-time data analysis --- water reservoir --- regression --- observed data --- ERA5-Land data --- R language --- precipitation --- drought --- Mann–Kendall --- trend analysis --- actual evapotranspiration --- potential evapotranspiration --- reference evapotranspiration --- evaporation paradox --- global dimming --- wind stilling --- forest fires --- groundwater --- stochastic simulation --- marginal structure --- long-range dependence --- Hurst–Kolmogorov dynamics --- RASPOTION --- parametric model --- hydrological calibration --- evapotranspiration estimation --- urban rain gardens --- lysimeters --- evapotranspiration models --- n/a --- Mann-Kendall --- Hurst-Kolmogorov dynamics

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This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him.

Information technology industries --- Computer science --- automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity

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This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him.

Information technology industries --- Computer science --- automata theory --- formal language theory --- bio-informatics --- recursive function theory --- evolutionary processor --- network of evolutionary processors --- network topology --- theory of computation --- computational models --- intrinsic perception --- Hausdorff dimension --- fractal --- computational complexity --- Turing machine --- oracle Turing machine --- shortest computations --- quasiperiod --- formal language --- asymptotic growth --- polynomial --- membrane computing --- computational complexity theory --- P vs. NP problem --- evolutional communication --- symport/antiport --- Kolmogorov complexity --- random strings --- extractors --- finite languages --- deterministic finite cover automata --- multiple entry automata --- automata with “do not care” symbols --- similarity relations --- process calculus --- communication patterns --- control structures --- hypergraph model --- P systems --- cP systems --- NP-complete --- NP-hard --- SAT --- logarithmic time complexity

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Biopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes. The major aim of this effort can be summarized as developing a mechanistic understanding of a wide range of process steps, including the development of technologies to perform online measurements and real-time control and optimization. Furthermore, minimization of the number of empirical experiments and the model-assisted exploration of the process design space are targeted. Even if tremendous progress has been achieved so far, there is still work to be carried out in order to realize the full potential of the process systems engineering toolbox. Within this reprint, an overview of cutting-edge developments of process systems engineering for biopharmaceutical and pharmaceutical manufacturing processes is given, including model-based process design, Digital Twins, computer-aided process understanding, process development and optimization, and monitoring and control of bioprocesses. The biopharmaceutical processes addressed focus on the manufacturing of biopharmaceuticals, mainly by Chinese hamster ovary (CHO) cells, as well as adeno-associated virus production and generation of cell spheroids for cell therapies.

Technology: general issues --- History of engineering & technology --- clonal cell population --- phenotypic diversity --- inoculum train --- uncertainty-based --- cell culture model --- biopharmaceutical manufacturing --- Escherichia coli --- hybrid modeling --- machine learning --- model-assisted DoE --- quality by design --- upstream bioprocessing --- surface plasmon resonance (SPR) --- bioprocess --- monitoring --- biosensor --- quality by design (QbD) --- process analytical technology (PAT) --- biotherapeutics production --- vaccines production --- CHO DP-12 --- computational fluid dynamics --- bioreactor characterization --- hydrodynamic gradients --- process development --- critical shear stress --- Kolmogorov length scale --- operational space --- sensors --- cell culture --- spectroscopy --- PAT --- smart biomanufacturing --- soft-sensor --- Adeno-associated virus --- transfection --- PEI --- continuous --- gene therapy --- microcarriers --- bioreactor --- transient expression --- spheroid strength --- β-cells --- diabetes --- shear stress-guided production --- hydrodynamic stress --- Gaussian processes --- Bayes optimization --- Pareto optimization --- multi-objective --- seed train --- Chinese hamster ovary cells --- cryopreservation --- monoclonal antibodies --- N−1 perfusion --- process intensification --- upstream processing --- n/a

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Biopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes. The major aim of this effort can be summarized as developing a mechanistic understanding of a wide range of process steps, including the development of technologies to perform online measurements and real-time control and optimization. Furthermore, minimization of the number of empirical experiments and the model-assisted exploration of the process design space are targeted. Even if tremendous progress has been achieved so far, there is still work to be carried out in order to realize the full potential of the process systems engineering toolbox. Within this reprint, an overview of cutting-edge developments of process systems engineering for biopharmaceutical and pharmaceutical manufacturing processes is given, including model-based process design, Digital Twins, computer-aided process understanding, process development and optimization, and monitoring and control of bioprocesses. The biopharmaceutical processes addressed focus on the manufacturing of biopharmaceuticals, mainly by Chinese hamster ovary (CHO) cells, as well as adeno-associated virus production and generation of cell spheroids for cell therapies.

Technology: general issues --- History of engineering & technology --- clonal cell population --- phenotypic diversity --- inoculum train --- uncertainty-based --- cell culture model --- biopharmaceutical manufacturing --- Escherichia coli --- hybrid modeling --- machine learning --- model-assisted DoE --- quality by design --- upstream bioprocessing --- surface plasmon resonance (SPR) --- bioprocess --- monitoring --- biosensor --- quality by design (QbD) --- process analytical technology (PAT) --- biotherapeutics production --- vaccines production --- CHO DP-12 --- computational fluid dynamics --- bioreactor characterization --- hydrodynamic gradients --- process development --- critical shear stress --- Kolmogorov length scale --- operational space --- sensors --- cell culture --- spectroscopy --- PAT --- smart biomanufacturing --- soft-sensor --- Adeno-associated virus --- transfection --- PEI --- continuous --- gene therapy --- microcarriers --- bioreactor --- transient expression --- spheroid strength --- β-cells --- diabetes --- shear stress-guided production --- hydrodynamic stress --- Gaussian processes --- Bayes optimization --- Pareto optimization --- multi-objective --- seed train --- Chinese hamster ovary cells --- cryopreservation --- monoclonal antibodies --- N−1 perfusion --- process intensification --- upstream processing