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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.

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

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The Special Issue “Refrigeration Systems and Applications” aims to encourage researchers to address the concerns associated with climate change and the sustainability of artificial cold production systems, and to further the transition to the more sustainable technologies and methodologies of tomorrow through theoretical, experimental, and review research on the different applications of refrigeration and associated topics.

energy consumption --- thermal load --- domestic refrigeration system --- two-phase ejector --- CO2 --- transcritical system --- exergy analysis --- irreversibility --- transiting exergy --- magnetic refrigeration --- magnetocaloric effect --- LaFe13 ? x ? yCoxSiy --- gadolinium --- artificial neural network --- modelling --- twin-screw refrigeration compressor --- CFD --- thermodynamic performance --- P-? indicator diagram --- chiller energy consumption --- artificial neural network (ANN) --- HVAC --- nanofluids --- caloric cooling --- barocaloric --- solid-state cooling --- acetoxy silicone rubber --- Cu nanofluids --- ethylene-glycol nanofluids --- heat transfer --- absorption refrigeration system --- thermodynamic analysis --- calculation model --- LiCl-H2O --- LiBr-H2O --- off-design behaviors --- phase change material --- thermal energy storage --- vapor compression system --- HVAC --- energy efficiency --- distillation --- heat pump --- hydraulic turbine --- refrigerant reclamation --- R-410A --- superheating --- r1234yf --- r1234ze(e) --- HFO --- ejector refrigeration technology --- magnetic refrigeration --- magneto-caloric effect --- coefficient of performance --- eddy currents --- experimental --- parasitic heat load --- modelling

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Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators.

demand response --- genetic algorithm --- renewable energy --- unit commitment --- uncertainty --- artificial neural network --- day-ahead forecast --- ensemble methods --- harmony search meta-heuristic algorithm --- solar radiation --- photovoltaic --- tilt angle --- orientation --- smart photovoltaic system blind --- prototype model --- photovoltaic panel --- tracking system --- monitoring system --- photovoltaic --- battery --- integrated storage --- PV cell temperature --- thermal model --- thermal image --- single-diode photovoltaic model --- online diagnosis --- genetic algorithm --- embedded systems --- photovoltaics --- power forecasting --- artificial neural networks --- solar cell --- metaheuristic algorithm --- electrical parameters --- analytical methods --- firefly algorithm --- statistical errors --- photovoltaics --- MPPT algorithm --- evolutionary algorithms --- particle swarm optimization --- solar photovoltaic --- parameter extraction --- symbiotic organisms search --- metaheuristic --- computational intelligence --- day-ahead forecast --- photovoltaics

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This Special Issue presents the work of 30 scientists from 11 countries. It confirms that the impacts of global change, resulting from both climate change and increasing anthropogenic pressure, are huge on worldwide coastal areas (and critically so on some islands in the Pacific Ocean), with highly negative effects on coastal groundwater resources, which are widely affected by seawater intrusion. Some improved research methods are proposed in the contributions: using innovative hydrogeological, geophysical, and geochemical monitoring; assessing impacts of the changing environment on the coastal groundwater resources in terms of quantity and quality; and using modelling, especially to improve management approaches. The scientific research needed to face these challenges must continue to be deployed by different approaches based on the monitoring, modelling and management of groundwater resources. Novel and more efficient methods must be developed to keep up with the accelerating pace of global change.

artificial neural network --- support vector machine --- time series model --- freshwater-saltwater interface --- direct prediction --- recursive prediction --- geophysics --- groundwater --- hydrogeology --- aquifer --- atoll --- freshwater lens --- sea-level rise --- flooding --- groundwater --- tide --- submarine groundwater discharge --- atoll island --- groundwater storage --- freshwater resilience --- MODFLOW/SEAWAT --- saltwater intrusion --- water resources management --- seawater intrusion --- coastal aquifer --- arid and semi-arid regions --- cation exchange --- Tripoli --- Libya --- seawater intrusion --- multi-layered coastal aquifer --- offshore geophysics --- numerical model --- tidal signal --- sea–aquifer relations --- fish ponds --- sharp interface numerical modeling --- freshwater lens --- saltwater intrusion --- well salinization --- small islands --- Tongatapu --- saltwater intrusion --- sea level rise --- Nile Delta aquifer --- fresh groundwater volume --- extraction --- Nile Delta governorates --- SGD --- SGD model --- Radon --- coastal aquifer --- nutrient discharge --- Gaza Strip --- saltwater intrusion --- groundwater resources --- coastal aquifer --- climate change --- modelling --- monitoring --- salinization --- water resources management

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Climate change, urban air quality, and dependency on crude oil are important societal challenges. In the transportation sector especially, clean and energy efficient technologies must be developed. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) have gained a growing interest in the vehicle industry. Nowadays, the commercialization of EVs and PHEVs has been possible in different applications (i.e., light duty, medium duty, and heavy duty vehicles) thanks to the advances in energy storage systems, power electronics converters (including DC/DC converters, DC/AC inverters, and battery charging systems), electric machines, and energy efficient power flow control strategies. This book is based on the Special Issue of the journal Applied Sciences on “Plug-In Hybrid Electric Vehicles (PHEVs)”. This collection of research articles includes topics such as novel propulsion systems, emerging power electronics and their control algorithms, emerging electric machines and control techniques, energy storage systems, including BMS, and efficient energy management strategies for hybrid propulsion, vehicle-to-grid (V2G), vehicle-to-home (V2H), grid-to-vehicle (G2V) technologies, and wireless power transfer (WPT) systems.

battery power --- convex optimization --- dynamic programming --- engine-on power --- plug-in hybrid electric vehicle --- simulated annealing --- electric vehicle --- open-end winding --- dual inverter --- voltage vector distribution --- power sharing --- energy management --- range-extender --- CO2 --- air quality --- mobility needs --- LCA --- Paris Agreement --- hybrid energy storage system --- lithium-ion battery --- lithium-ion capacitor --- lifetime model --- power distribution --- state of health estimation --- adaptive neuron-fuzzy inference system (ANFIS) --- group method of data handling (GMDH) --- artificial neural network (ANN) --- electric vehicles (EVs) --- capacity degradation --- lithium-ion battery --- time-delay input --- interleaved multiport converte --- multi-objective genetic algorithm --- hybrid electric vehicles --- losses model --- wide bandgap (WBG) technologies --- Energy Storage systems --- LCA --- Well-to-Wheel --- electric vehicle --- plug-in hybrid --- electricity mix --- consequential --- attributional --- marginal --- system modelling --- energy system --- meta-analysis --- parallel hybrid electric vehicle --- regenerative braking --- fuel consumption characteristics --- energy efficiency --- state of charge --- lithium polymer battery --- electric vehicle --- Plugin Hybrid electric vehicle --- Li-ion battery --- modelling --- measurements --- state of charge --- strong track filter --- modified one-state hysteresis model --- Li(Ni1/3Co1/3Mn1/3)O2 battery --- energy management strategy --- Markov decision process (MDP) --- plug-in hybrid electric vehicles (PHEVs) --- Q-learning (QL) --- reinforcement learning (RL) --- novel propulsion systems --- emerging power electronics --- including wide bandgap (WBG) technology --- emerging electric machines --- efficient energy management strategies for hybrid propulsion systems --- energy storage systems --- life-cycle assessment (LCA)