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Genomics and Effectomics of the Crop Killer Xanthomonas

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199020 Year: Pages: 158 DOI: 10.3389/978-2-88919-902-0 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Botany
Added to DOAB on : 2016-01-19 14:05:46
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Phytopathogenic bacteria of the Xanthomonas genus cause severe diseases on hundreds of host plants, including economically important crops, such as bean, cabbage, cassava, citrus, hemp, pepper, rice, sugarcane, tomato or wheat. Diseases occurring in nature comprise bacterial blight, canker, necrosis, rot, scald, spot, streak or wilt. Xanthomonas spp. are distributed worldwide and pathogenic and nonpathogenic strains are essentially found in association to plants. Some phytopathogenic strains are emergent or re-emergent and, consequently, dramatically impact agriculture, economy and food safety. During the last decades, massive efforts were undertaken to decipher Xanthomonas biology. So far, more than one hundred complete or draft genomes from diverse Xanthomonas species have been sequenced (http://www.xanthomonas.org), thus providing powerful tools to study genetic determinants triggering pathogenicity and adaptation to plant habitats. Xanthomonas spp. employ an arsenal of virulence factors to invade its host, including extracellular polysaccharides, plant cell wall-degrading enzymes, adhesins and secreted effectors. In most xanthomonads, type III secretion (T3S) system and secreted effectors (T3Es) are essential to bacterial pathogenicity through the inhibition of plant immunity or the induction of plant susceptibility (S) genes, as reported for Transcription Activation-Like (TAL) effectors. Yet, toxins can also be major virulence determinants in some xanthomonads while nonpathogenic Xanthomonas species do live in sympatry with plant without any T3S systems nor T3Es. In a context of ever increasing international commercial exchanges and modifications of the climate, monitoring and regulating pathogens spread is of crucial importance for food security. A deep knowledge of the genomic diversity of Xanthomonas spp. is required for scientists to properly identify strains, to help preventing future disease outbreaks and to achieve knowledge-informed sustainable disease resistance in crops. This Research Topic published in the ‘Plant Biotic Interactions’ section of Frontiers in Plant Science and Frontiers in Microbiology aims at illustrating several of the recent achievements of the Xanthomonas community. We collected twelve manuscripts dealing with comparative genomics or T3E repertoires, including five focusing on TAL effectors which we hope will contribute to advance research on plant pathogenic bacteria.

Plant cell wall in pathogenesis, parasitism and symbiosis

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889194421 Year: Pages: 150 DOI: 10.3389/978-2-88919-442-1 Language: English
Publisher: Frontiers Media SA
Subject: Botany --- Science (General)
Added to DOAB on : 2016-02-05 17:24:33
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The cell wall is a complex structure mainly composed of cellulose microfibrils embedded in a cohesive hemicellulose and pectin matrix. Cell wall structural proteins, enzymes and their inhibitors are also essential components of plant cell walls. They are involved in the cross-link of cell wall polysaccharides, wall structure, and the perception and signaling of defense-related elicitors at the cell surface. In the outer part of the epidermal cells, the polysaccharides are coated by the cuticle, consisting of hydrophobic cutin, suberin and wax layers. Lignin, a macromolecule composed of highly cross-linked phenolic molecules, is a major component of the secondary cell wall. The cell wall is the first cell structure on which interactions between plants and a wide range of other organisms, including insects, nematodes, pathogenic or symbiotic micro-organisms take place. It not only represents a barrier that limits access to the cellular contents that provide a rich nutrient source for pathogens but serves as a source of elicitors of plant defense responses released upon partial enzymatic degradation of wall polysaccharides during infection. Modification of the plant cell wall can also occur at the level of plasmodesmata during virus infection as well as during abiotic stresses. The fine structure and composition of the plant cell wall as well as the regulation of its biosynthesis can thus strongly influence resistance and susceptibility to pathogens. This Research Topic provides novel insights and detailed overviews on the dynamics of the plant cell wall in plant defence, parasitism and symbiosis and describes experimental approaches to study plant cell wall modifications occurring during interaction of plants with different organisms.

Biotic and Abiotic Stress Responses in Crop Plants

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ISBN: 9783038974635 9783038974642 Year: Pages: 252 DOI: 10.3390/books978-3-03897-464-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Plant Sciences --- Genetics --- Biology
Added to DOAB on : 2019-01-16 10:24:11
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While the demand for crop products continues to increase strongly, agricultural productivity is threatened by various stress factors, often associated with global warming. To sustain and improve yield, it is necessary to understand how plants respond to various stresses, and to use the generated knowledge in modern breeding programs. Most knowledge regarding the molecular mechanisms associated with stress responses has been obtained from investigations using the model plant Arabidopsis thaliana. Stress hormones, such as abscisic acid, jasmonic acid, and salicylic acid, have been shown to play key roles in defense responses against abiotic and biotic stresses. More recently, evidence that growth-regulating plant hormones are also involved in stress responses has been accumulating. Epigenetic regulation at the DNA and histone level, and gene regulation by small non-coding RNAs appear to be important as well. Many approaches have used mutant screens and next generation sequencing approaches to identify key players and mechanisms how plants respond to their environment. However, it is often unclear to which extent the elucidated mechanisms also operate in crops.This Special Issue Book, therefore, aims to close this gap and contains a number of contributions from labs that work both, on Arabidopsis and crops. The book includes contributions reporting how crop plant species respond to various abiotic stresses, such as drought, heat, cold, flooding, and salinity, as well as biotic stimuli during microbial infections. It contains reviews, opinions, perspectives, and original articles, and its focus is on our molecular understanding of biotic and abiotic stress responses in crops, highlighting, among other aspects, the role of stress hormones, secondary metabolites, signaling mechanisms, and changes in gene expression patterns and their regulation. Approaches and ideas to achieve stress tolerance and to maintain yield stability of agricultural crops during stress periods can be found in most chapters. These include also perspectives on how knowledge from model plants can be utilized to facilitate crop-plant breeding and biotechnology.

A Themed Issue of Functional Molecule-based Magnets: Dedicated to Professor Masahiro Yamashita on the Occasion of his 65th Birthday

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ISBN: 9783039289011 / 9783039289028 Year: Pages: 134 DOI: 10.3390/books978-3-03928-902-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Chemistry (General)
Added to DOAB on : 2020-06-09 16:38:57
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Research on molecule-based magnetic materials was systematized in the 1980s and expanded rapidly. A Special Issue focusing on molecule-based magnetic substances was published in Magnetochemistry. However, the functionalities of the substances increase daily; therefore, the researchers’ quest is not yet in decline. Research on molecule-based magnetism developed across many fields, including chemistry, physics, material chemistry, and applied physics, and the use of the various functionalities of these molecule-based magnetic substances has greatly influenced research on spin-based devices. In honor of Professor Masahiro Yamashita, who contributed greatly to this field, I have put together a Special Issue that highlights ten groundbreaking articles. The issue is entitled, “A Themed Issue of Functional Molecule-Based Magnets: Dedicated to Professor Masahiro Yamashita on the Occasion of his 65th Birthday”. I wish to thank the authors for their dedicated work, and the referees and editorial staff for the time they invested commenting on the articles.

Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

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ISBN: 9783039212156 9783039212163 Year: Pages: 438 DOI: 10.3390/books978-3-03921-216-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Mechanical Engineering
Added to DOAB on : 2019-12-09 11:49:15
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.

Keywords

landslide --- bagging ensemble --- Logistic Model Trees --- GIS --- Vietnam --- colorization --- random forest regression --- grayscale aerial image --- change detection --- gully erosion --- environmental variables --- data mining techniques --- SCAI --- GIS --- mapping --- single-class data descriptors --- materia medica resource --- Panax notoginseng --- one-class classifiers --- geoherb --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- remote sensing image segmentation --- convolutional neural networks --- Gaofen-2 --- hybrid structure convolutional neural networks --- winter wheat spatial distribution --- classification-based learning --- real-time precise point positioning --- convergence time --- ionospheric delay constraints --- precise weighting --- landslide --- weights of evidence --- logistic regression --- random forest --- hybrid model --- traffic CO --- traffic CO prediction --- neural networks --- GIS --- land use/land cover (LULC) --- unmanned aerial vehicle --- texture --- gray-level co-occurrence matrix --- machine learning --- crop --- landslide susceptibility --- random forest --- boosted regression tree --- information gain --- landslide susceptibility map --- ALS point cloud --- multi-scale --- classification --- large scene --- coarse particle --- particulate matter 10 (PM10) --- landsat image --- machine learning --- support vector machine --- high-resolution --- optical remote sensing --- object detection --- deep learning --- transfer learning --- land subsidence --- Bayes net --- naïve Bayes --- logistic --- multilayer perceptron --- logit boost --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- leaf area index (LAI) --- machine learning --- Sentinel-2 --- sensitivity analysis --- training sample size --- spectral bands --- spatial sparse recovery --- constrained spatial smoothing --- spatial spline regression --- alternating direction method of multipliers --- landslide prediction --- machine learning --- neural networks --- model switching --- spatial predictive models --- predictive accuracy --- model assessment --- variable selection --- feature selection --- model validation --- spatial predictions --- reproducible research --- Qaidam Basin --- remote sensing --- TRMM --- artificial neural network --- n/a

Safety, Quality and Processing of Fruits and Vegetables

Authors: --- --- ---
ISBN: 9783039288298 / 9783039288304 Year: Pages: 216 DOI: 10.3390/books978-3-03928-830-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Nutrition and Food Sciences
Added to DOAB on : 2020-06-09 16:38:57
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Nowadays, one of the main objectives of the fruit and vegetable industry is to develop innovative novel products with high quality, safety, and optimal nutritional characteristics in order to respond, with efficiency, to increasing consumer expectations. Various unconventional technologies (e.g., pulsed electric field, pulsed light, ultrasound, high pressure, and microwave drying) have emerged and enable the processing of fruits and vegetables in a way that increases their stability while preserving their thermolabile nutrients, flavour, texture, and overall quality. Some of these technologies can also be used for waste and byproduct valorisation. The application of fast noninvasive methods for process control is of great importance for the fruit and vegetable industry. The following Special Issue “Safety, Quality, and Processing of Fruits and Vegetables” consists of 11 papers which represent a high-value contribution to the existing knowledge on safety aspects, quality evaluation, and emerging processing technologies for fruits and vegetables.

Family Iridoviridae Molecular and Ecological Studies of a Family Infecting Invertebrates and Ectothermic Vertebrates

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ISBN: 9783039215164 9783039215171 Year: Pages: 234 DOI: 10.3390/books978-3-03921-517-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
Added to DOAB on : 2019-12-09 11:49:15
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Ranaviruses and other viruses within the family Iridoviridae, infect a wide range of ecologically and commercially important ectothermic vertebrates, i.e., bony fish, amphibians, and reptiles, and invertebrates, including agricultural and medical pests and cultured shrimp and crayfish, and are responsible for considerable morbidity and mortality. Understanding the impact of these various agents on diverse host species requires the combined efforts of ecologists, veterinarians, pathologists, comparative immunologists and molecular virologists. Unfortunately, investigators involved in these studies often work in discipline-specific silos that preclude interaction with others whose insights and approaches are required to comprehensively address problems related to ranavirus/iridovirus disease. Our intent here is to breakdown these silos and provide a forum where diverse researchers with a common interest in ranavirus/iridovirus biology can profitably interact. As a colleague once quipped, “Three people make a genius.” We are hoping to do something along those lines by presenting a collection of research articles dealing with issues of anti-viral immunity, identification of a potentially novel viral genus exemplified by erythrocytic necrosis virus, viral inhibition of innate immunity, identification of novel hosts for lymphocystivirus and invertebrate iridoviruses, and modelling studies of ranavirus transmission. Collectively these and others will exemplify the breadth of ongoing studies focused on this virus family.

Keywords

amphibians --- histopathology --- immunohistochemistry --- Mexico --- outbreak --- ranavirus --- risk assessment --- Iridoviridae --- frog virus 3 --- FV3 --- ranavirus --- immunofluorescence --- intracellular localization --- iridovirus --- ranavirus --- epidemiology --- antibody --- ELISA --- virus isolation --- prevalence --- native-fish conservation --- biosecurity --- endemic disease --- Unconventional T cell --- nonclassical MHC --- antiviral immunity --- interferon --- DIV1 --- SHIV --- CQIV --- Macrobrachium rosenbergii --- Macrobrachium nipponense --- Procambarus clarkii --- white head --- susceptible species --- viral load --- erythrocytic necrosis virus (ENV) --- viral erythrocytic necrosis (VEN) --- Pacific salmon --- Pacific herring --- British Columbia --- SHIV --- DIV1 --- Decapodiridovirus --- Exopalaemon carinicauda --- susceptibility --- host --- ISDL --- amphibian --- Ranavirus --- frog virus 3 --- mathematical models --- Bayesian inference --- viral immune evasion --- immunomodulators --- NF-?B --- Imd --- DNA virus --- host-pathogen interactions --- IIV-6 --- Rana grylio virus (RGV) --- iridovirus core proteins --- protein interaction --- aquatic animals --- cross-species transmission --- yeast two-hybrid (Y2H) --- co-immunoprecipitation (Co-IP) --- megalocytivirus --- iridovirus --- European chub --- Lymphocystis disease virus --- Artemia spp. --- viral infection --- Sparus aurata --- viral transmission --- eDNA --- Ranavirus --- Common frog --- Rana temporaria --- early detection --- virus surveillance --- n/a --- transmission modelling --- susceptible-infected (SI) models --- emerging infection --- ranavirosis --- Iridoviridae --- disease dynamics --- ranavirus --- virus binding --- heparan sulfate --- Andrias davidianus ranavirus --- Rana grylio virus --- envelope protein --- lizard --- bearded dragon --- Pogona vitticeps --- cricket --- Gryllus bimaculatus

Synthesis and Applications of New Spin Crossover Compounds

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ISBN: 9783039213610 9783039213627 Year: Pages: 254 DOI: 10.3390/books978-3-03921-362-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-12-09 11:49:15
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The crystal chemistry of spin crossover (SCO) behavior in coordination compounds can potentially be in association with smart materials—promising materials for applications as components of memory devices, displays, sensors and mechanical devices and, especially, actuators, such as artificial muscles. This Special Issue is devoted to various aspects of SCO and related research, comprising 18 interesting original papers on valuable and important SCO topics. Significant and fundamental scientific attention has been focused on the SCO phenomena in a wide research range of fields of fundamental chemical and physical and related sciences, containing the interdisciplinary regions of chemical and physical sciences related to the SCO phenomena. Coordination materials with bistable systems between the LS and the HS states are usually triggered by external stimuli, such as temperature, light, pressure, guest molecule inclusion, soft X-ray, and nuclear decay. Since the first Hofmann-like spin crossover (SCO) behavior in {Fe(py)2[Ni(CN)4]}n (py = pyridine) was demonstrated, this crystal chemistry motif has been frequently used to design Fe(II) SCO materials to enable determination of the correlations between structural features and magnetic properties.

Keywords

spin crossover --- spin transition --- cobalt(II) ion --- paramagnetic ligand --- aminoxyl --- switch --- mosaicity --- spin crossover --- X-ray diffraction --- fatigability --- single crystal --- phase transition --- structural disorder --- spin-crossover --- dinuclear triple helicate --- Fe(II) --- solvent effects --- metal dithiolene complexes --- [Au(dmit)2]?, [Au(dddt)2]? --- ion-pair crystals --- [Fe(III)(3-OMesal2-trien)]+ --- coordination complexes --- crystal structure --- magnetic properties --- magnetic susceptibility --- magnetization --- spin-crossover transition --- Fe(II) complex --- dipyridyl-N-alkylamine ligands --- high spin (HS) --- low spin (LS) --- spin cross-over (SCO) --- magnetic transition --- cobalt oxide --- spin polaron --- impurity effect --- spin-state crossover --- coordination polymer --- supramolecular isomerism --- spin crossover --- crystal engineering --- spin crossover --- X-ray absorption spectroscopy --- soft X-ray induced excited spin state trapping --- high spin --- spin-crossover --- LIESST effect --- hydrogen bonding --- ?-? interactions --- charge-transfer phase transition --- iron mixed-valence complex --- hetero metal complex --- dithiooxalato ligand --- substitution of 3d transition metal ion --- ferromagnetism --- dielectric response --- 57Fe Mössbauer spectroscopy --- Fe(III) coordination complexes --- hexadentate ligand --- Schiff base --- spin crossover --- UV-Vis spectroscopy --- SQUID --- EPR spectroscopy --- spin-crossover --- optical microscopy --- reaction diffusion --- spin crossover --- Fe(III) complex --- qsal ligand --- thermal hysteresis --- structure phase transition --- counter-anion --- solvate --- lattice energy --- optical conductivity spectrum --- spiral structure --- 1,2-bis(4-pyridyl)ethane --- supramolecular coordination polymer --- chiral propeller structure --- atropisomerism --- spin crossover --- iron(II) complexes --- C–H···? interactions --- magnetic properties --- thermochromism --- spin crossover --- linear pentadentate ligand --- iron(II) --- mononuclear --- 1,2,3-triazole --- crystal structure --- magnetic properties --- DFT calculation --- intermolecular interactions --- amorphous --- spin crossover --- Cu(II) complexes --- nitroxides --- phase transitions --- magnetostructural correlations --- iron (II), spin crossover --- X-ray diffraction --- coordination polymers --- n/a

Protection Strategy against Spruce Budworm

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ISBN: 9783039280964 9783039280971 Year: Pages: 220 DOI: 10.3390/books978-3-03928-097-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Forestry --- Biology --- Science (General)
Added to DOAB on : 2020-01-30 16:39:46
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Spruce budworm (Choristoneura fumiferana (Clem.)) outbreaks are a dominant natural disturbance in the forests of Canada and northeastern USA. Widespread, severe defoliation by this native insect results in large-scale mortality and growth reductions of spruce (Picea sp.) and balsam fir (Abies balsamea (L.) Mill.) forests, and largely determines future age–class structure and productivity. The last major spruce budworm outbreak defoliated over 58 million hectares in the 1970s–1980s, and caused 32–43 million m3/year of timber volume losses from 1978 to 1987, in Canada. Management to deal with spruce budworm outbreaks has emphasized forest protection, spraying registered insecticides to prevent defoliation and keep trees alive. Other tactics can include salvage harvesting, altering harvest schedules to remove the most susceptible stands, or reducing future susceptibility by planting or thinning. Chemical insecticides are no longer used, and protection strategies use biological insecticides Bacillus thuringiensis (B.t.) or tebufenozide, a specific insect growth regulator. Over the last five years, a $30 million research project has tested another possible management tactic, termed an ‘early intervention strategy’, aimed at area-wide management of spruce budworm populations. This includes intensive monitoring to detect ‘hot spots’ of rising budworm populations before defoliation occurs, targeted insecticide treatment to prevent spread, and detailed research into target and non-target insect effects. The objective of this Special Issue is to compile the most recent research on protection strategies against spruce budworm. A series of papers will describe results and prospects for the use of an early intervention strategy in spruce budworm and other insect management.

Keywords

forest pests --- defoliation --- spruce budworm --- multi-spectral remote sensing --- Acadian region --- Maine --- Quebec --- Choristoneura fumiferana --- Abies balsamea --- hardwood content --- defoliation prediction --- Choristoneura fumiferana --- annual defoliation --- spatial autocorrelation --- spatial-temporal patterns --- mixed effect models --- intertree variance --- insect population management --- spruce budworm --- early intervention --- defoliation --- economic losses --- decision support system --- optimized treatment design --- insect population management --- spruce budworm --- early intervention --- defoliation --- economic losses --- decision support system --- computable general equilibrium model --- Pinaceae --- endophytic fungi --- plant tolerance --- Phialocephala scopiformis --- Picea glauca --- spruce budworm --- phenology --- insect susceptibility --- spruce budworm --- forest protection --- early intervention strategy --- egg recruitment --- apparent fecundity --- growth rate --- spruce budworm --- Choristoneura fumiferana --- forest protection --- early intervention strategy --- survival --- apparent fecundity --- immigration --- growth rate --- treatment threshold --- insecticides --- spruce budworm --- moth --- tortricidae --- Choristoneura fumiferana (Clemens) --- forest protection --- early intervention strategy --- pheromone mating disruption --- migration --- dispersal --- spruce budworm --- Choristoneura fumiferana --- moth --- Lepidoptera --- forest protection --- early intervention strategy --- migration --- simulation --- aerobiology --- moths --- migration --- forest protection --- spruce budworm --- Choristoneura fumiferana (Clem.) --- early intervention strategy --- modelling --- circadian rhythm --- foliage protection --- population control --- monitoring --- area-wide management --- science communication --- economic and ecological cost: benefit analyses --- early intervention strategy --- foliage protection --- defoliation --- monitoring --- insecticide application

Flood Forecasting Using Machine Learning Methods

Authors: --- ---
ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

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