AIMC Topic: Water

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Robot-assisted magnetic capsule endoscopy; navigating colorectal inclinations.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy Feb 3, 2022
To investigate the interaction of a robot assisted magnetically driven wireless capsule endoscope (WCE) with colonic tissue, as it traverses the colorectal bends in the dorsal and ventral directions, relying only on the feedback from a 3D accelerome...
Animals Swine Capsule Endoscopy Capsule Endoscopes Colorectal Neoplasms Water Robotics
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Ultrafast water-fat separation using deep learning-based single-shot MRI.

Magnetic resonance in medicine Jan 31, 2022
PURPOSE: To present a deep learning-based reconstruction method for spatiotemporally encoded single-shot MRI to simultaneously obtain water and fat images.
Algorithms Rats Animals Artifacts Deep Learning Magnetic Resonance Imaging Water Image Processing, Computer-Assisted
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Improving the leak detection efficiency in water distribution networks using noise loggers.

The Science of the total environment Jan 29, 2022
Leak detection techniques are effective ways of controlling water leakage in real water distribution networks (WDNs). Nevertheless, developing detection techniques for real WDNs has received little attention compared to the detection models developed...
Support Vector Machine Wavelet Analysis Water Supply Algorithms Water Neural Networks, Computer
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Rapid detection of ionic contents in water through sensor fusion and convolutional neural network.

Chemosphere Jan 25, 2022
Salt contents in soil or groundwater are one of the primary indicators to evaluate contamination levels. Electrical conductivity (EC) or salinity information from the conventional laboratory analysis is typically inefficient in delineating contaminat...
Ions Spectrum Analysis Soil Water Neural Networks, Computer
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Predicting the evolution of number of native contacts of a small protein by using deep learning approach.

Computational biology and chemistry Jan 12, 2022
Native contacts (NCs) are one of the most vital parameters in order to define the resemblance of a protein conformation with its native state. Prediction of number of native contacts in a protein is useful in protein folding mechanism. In this work, ...
Deep Learning Water Neural Networks, Computer Forecasting
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Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Using a LSTM Neural Network Model from Environmental Data.

Toxins Jan 12, 2022
Paralytic shellfish toxins (PSTs) are produced mainly by (formerly ). Since 2000, the National Institute of Fisheries Science (NIFS) has been providing information on PST outbreaks in Korean coastal waters at one- or two-week intervals. However, a d...
Models, Theoretical Environmental Monitoring Water Time Factors Mytilus Tidal Waves Marine Toxins Salinity Neural Networks, Computer Republic of Korea Temperature Animals
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Application of NIRs coupled with PLS and ANN modelling to predict average droplet size in oil-in-water emulsions prepared with different microfluidic devices.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 6, 2022
In this study, the potential of microfluidic systems with different microchannel geometries (microchannel with teardrop micromixers and microchannel with swirl micromixers) for the preparation of oil-in-water (O/W) emulsions using two different emuls...
Lab-On-A-Chip Devices Neural Networks, Computer Least-Squares Analysis Water Emulsions
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An Ambidextrous STarfish-Inspired Exploration and Reconnaissance Robot (The ASTER-bot).

Soft robotics Dec 31, 2021
As more roboticists are turning to Nature for design inspiration, it is becoming increasingly apparent that multisystem-level investigations of biological processes can frequently lead to unexpected advances in the development of experimental researc...
Locomotion Starfish Robotics Motion Animals Water
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Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Environmental science & technology Dec 30, 2021
Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimenta...
Membranes, Artificial Bayes Theorem Permeability Machine Learning Water
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Localizing Perturbations in Pressurized Water Reactors Using One-Dimensional Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland) Dec 24, 2021
This work outlines an approach for localizing anomalies in nuclear reactor cores during their steady state operation, employing deep, one-dimensional, convolutional neural networks. Anomalies are characterized by the application of perturbation diagn...
Neutrons Software Neural Networks, Computer Nuclear Reactors Water
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