AIMC Topic: Water

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Semi-Automated Data Processing and Semi-Supervised Machine Learning for the Detection and Classification of Water-Column Fish Schools and Gas Seeps with a Multibeam Echosounder.

Sensors (Basel, Switzerland)
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and ...

Early Coaching to Increase Water Intake in CKD.

Annals of nutrition & metabolism
INTRODUCTION: In observational studies, increased water intake improves kidney function but not in adults with CKD stage 3 and more. CKD WIT trial has shown a nonsignificant gradual decline in kidney function after 1 year of coaching to increase wate...

Effects of a 14-Day Hydration Intervention on Individuals with Habitually Low Fluid Intake.

Annals of nutrition & metabolism
BACKGROUND: Debate continues over whether or not individuals with low total water intake (TWI) are in a chronic fluid deficit (i.e., low total body water) [1]. When women with habitually low TWI (1.6 ± 0.5 L/da...

The Influence of Fluid Intake Behavior on Cognition and Mood among College Students in Baoding, China.

Annals of nutrition & metabolism
INTRODUCTION: Water is a critical nutrient, and it is important for the maintenance of the physiological function of the human body [1-3]. In addition to fluid amounts, f...

Tuning the reversibility of hair artificial muscles by disulfide cross-linking for sensors, switches, and soft robotics.

Materials horizons
Tensile and torsional artificial muscles from biocompatible and biodegradable materials are highly desired for soft robotics, sensors, and controllers in bio-related applications. Twisted fibers can be used to prepare tensile and torsional artificial...

On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks.

Food chemistry
In this paper, we present an analysis of the performance of Raman spectroscopy, combined with feed-forward neural networks (FFNN), for the estimation of concentration percentages of glucose, sucrose, and fructose in water solutions. Indeed, we analys...

Cerebral blood flow measurements with O-water PET using a non-invasive machine-learning-derived arterial input function.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of O-labeled water by using tracer kinetic modelling. However, for quantification of regional CBF, an arterial input function (AIF), obtained from arterial bloo...

New methods based on back propagation (BP) and radial basis function (RBF) artificial neural networks (ANNs) for predicting the occurrence of haloketones in tap water.

The Science of the total environment
Haloketones (HKs) is one class of disinfection by-products (DBPs) which is genetically toxic and mutagenic. Monitoring HKs in drinking water is important for drinking water safety, yet it is a time-consuming and laborious job. Developing predictive m...

A cumulative-risk assessment method based on an artificial neural network model for the water environment.

Environmental science and pollution research international
To analyze the cumulative risks to the water environment, the backpropagation artificial neural network (BP-ANN), a self-adapting algorithm, was proposed in this study. A new comprehensive indicator of cumulative risks was formed by combining the wat...

Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia.

Environmental science and pollution research international
Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at...