You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Assessment of groundwater vulnerability in the Daule aquifer, Ecuador, using the susceptibility index method The Guayas region in Ecuador is economically very important, producing 68% of the national crops. The main agricultural activities threaten the groundwater therein with nitrate contamination given the large fertiliser and water needs. The present work tests the applicability of the susceptibility index assessment method in evaluating the impact of agricultural activities on groundwater quality, using as a case study an aquifer of the Guayas river basin in Ecuador. The index adapts four parameters of the DRASTIC method and incorporated a new land use parameter. Results show that the areas highly vulnerable to contamination are located in irrigation perimeters of dominant paddy fields associated with the high recharge rates in the alluvial deposits. Respectively, moderately vulnerable and low - vulnerability areas correspond to aquatic environments and forests, semi-natural zones and water bodies. One of the main contributions of the Daule aquifer vulnerability is likely its wide, flat topography. A great part of the aquifer is at high risk of contamination by nitrates if a code of good agricultural practices is not applied. Therefore the implementation of a monitoring network to control the nitrates concentrations is the first step to assure groundwater quality for drinking purposes.
{"AnatomicalStructure": [], "Bacterium": [], "BiologicFunction": [], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["nitrate", "nitrates", "alluvial deposits", "fertiliser", "water"], "ClinicalAttribute": [], "Eukaryote": ["national crops"], "Finding": ["monitoring network to control"], "Food": [], "HealthCareActivity": ["DRASTIC method", "susceptibility index assessment method", "susceptibility index method"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": [], "SpatialConcept": ["river basin", "Guayas", "semi-natural zones", "flat topography", "perimeters", "areas", "Ecuador", "wide", "Guayas region", "paddy fields", "groundwater"], "Virus": []}