AIMC Topic: Fresh Water

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Recognizing and counting Dendrocephalus brasiliensis (Crustacea: Anostraca) cysts using deep learning.

PloS one Mar 18, 2021
The Dendrocephalus brasiliensis, a native species from South America, is a freshwater crustacean well explored in conservational and productive activities. Its main characteristics are its rusticity and resistance cysts production, in which the hatch...
Ecological Parameter Monitoring Anostraca Animals Fresh Water South America Deep Learning Image Processing, Computer-Assisted
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Robotic environmental DNA bio-surveillance of freshwater health.

Scientific reports Sep 1, 2020
Autonomous water sampling technologies may help to overcome the human resource challenges of monitoring biological threats to rivers over long time periods and across large geographic areas. The Monterey Bay Aquarium Research Institute has pioneered ...
Humans Rivers Robotics DNA, Environmental Animals Feasibility Studies Fishes Environmental Monitoring Fresh Water
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Manganese (Mn) removal prediction using extreme gradient model.

Ecotoxicology and environmental safety Aug 10, 2020
Exploring the Manganese (Mn) removal prediction with several independent variables is tremendously critical and indispensable to understand the pattern of removal process. Mn is one of the key heavy metals (HMs) stipulated by the WHO for the developm...
Machine Learning Algorithms Forecasting Water Pollutants, Chemical Fresh Water Manganese Ecosystem Models, Theoretical Support Vector Machine
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Microplastics but not natural particles induce multigenerational effects in Daphnia magna.

Environmental pollution (Barking, Essex : 1987) Dec 31, 2019
Several studies have investigated the effects of nano- and microplastics on daphnids as key freshwater species. However, while information is abundant on the acute toxicity of plastic beads, little is known regarding the multigenerational effects of ...
Plastics Microplastics Reproduction Animals Humans Water Pollutants, Chemical Daphnia Female Fresh Water Infant, Newborn
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Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept.

Environmental science and pollution research international May 24, 2018
We present a modelling concept for evaluating the impacts of anthropogenic activities suspected to be from gas flaring on the quality of the atmosphere using domestic roof-harvested rainwater (DRHRW) as indicator. We analysed seven metals (Cu, Cd, Pb...
Environment Atmosphere Oil and Gas Fields Models, Theoretical Environmental Monitoring Water Pollutants, Chemical Air Pollution Water Quality Fuzzy Logic Fresh Water Humans Nigeria Metals
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A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Computational intelligence and neuroscience Nov 9, 2017
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collec...
Weather Water Supply Water Resources Machine Learning Fresh Water Water Algorithms Regression Analysis Time Factors Forecasting Taiwan Environment Design Factor Analysis, Statistical
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Specific chemiluminescent protocol for dual-site recognition of Streptococcus mutans utilizing strong affinity between teicoplanin and Gram-positive bacteria.

Talanta Nov 6, 2017
A novel dual-site recognition protocol was developed for chemiluminescent (CL) detection of Streptococcus mutans (S. mutans) based on a designed antibiotic-affinity strategy. Teicoplanin, a broad-spectrum antibiotic against Gram-positive bacteria, wa...
Luminol Rats Anti-Bacterial Agents Fresh Water Streptococcus mutans Milk Horseradish Peroxidase Limit of Detection Immunoglobulin G Saliva Cell Wall Iodobenzenes Magnetite Nanoparticles Dipeptides Humans Animals Teicoplanin Bacterial Proteins Hydrogen Peroxide Luminescent Measurements Protein Binding
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Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea.

The Science of the total environment Sep 19, 2014
Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vecto...
Artificial Intelligence Republic of Korea Environmental Monitoring Neural Networks, Computer Chlorophyll A Models, Chemical Water Pollutants, Chemical Estuaries Chlorophyll Fresh Water Water Pollution, Chemical
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"UDE DIATOMS in the Wild 2024": a new image dataset of freshwater diatoms for training deep learning models.

GigaScience Jan 2, 2024
BACKGROUND: Diatoms are microalgae with finely ornamented microscopic silica shells. Their taxonomic identification by light microscopy is routinely used as part of community ecological research as well as ecological status assessment of aquatic ecos...
Image Processing, Computer-Assisted Fresh Water Microscopy Diatoms Deep Learning
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A water quality prediction model based on signal decomposition and ensemble deep learning techniques.

Water science and technology : a journal of the International Association on Water Pollution Research Nov 1, 2023
Accurate water quality predictions are critical for water resource protection, and dissolved oxygen (DO) reflects overall river water quality and ecosystem health. This study proposes a hybrid model based on the fusion of signal decomposition and dee...
Deep Learning Fresh Water Oxygen Ecosystem Water Quality Entropy
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