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Plankton

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Main-Chain Sulfonium-Containing Homopolymers with Negligible Hemolytic Toxicity for Eradication of Bacterial and Fungal Biofilms.

ACS macro letters
Antimicrobials against planktonic cells and established biofilms at low doses are in increasing demand to tackle antibiotic-resistant biofilm infections. As a promising alternative to antibiotics, cationic polymers can effectively kill planktonic mic...

A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum.

Science robotics
The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of mi...

Machine Learning for the Study of Plankton and Marine Snow from Images.

Annual review of marine science
Quantitative imaging instruments produce a large number of images of plankton and marine snow, acquired in a controlled manner, from which the visual characteristics of individual objects and their in situ concentrations can be computed. To exploit t...

The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics.

Proceedings of the National Academy of Sciences of the United States of America
Intricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists ...

Hierarchical deep learning model to simulate phytoplankton at phylum/class and genus levels and zooplankton at the genus level.

Water research
Harmful algal blooms (HABs) have become a global issue, affecting public health and water industries in numerous countries. Because funds for monitoring HABs are limited, model development may be an alternative approach for understanding and managing...

EcoTransLearn: an R-package to easily use transfer learning for ecological studies-a plankton case study.

Bioinformatics (Oxford, England)
SUMMARY: In recent years, Deep Learning (DL) has been increasingly used in many fields, in particular in image recognition, due to its ability to solve problems where traditional machine learning algorithms fail. However, building an appropriate DL m...

Deep-Learning-Based Automated Tracking and Counting of Living Plankton in Natural Aquatic Environments.

Environmental science & technology
Plankton are widely distributed in the aquatic environment and serve as an indicator of water quality. Monitoring the spatiotemporal variation in plankton is an efficient approach to forewarning environmental risks. However, conventional microscopy c...

In-domain versus out-of-domain transfer learning in plankton image classification.

Scientific reports
Plankton microorganisms play a huge role in the aquatic food web. Recently, it has been proposed to use plankton as a biosensor, since they can react to even minimal perturbations of the aquatic environment with specific physiological changes, which ...

Predicting thermodynamic adhesion energies of membrane fouling in planktonic anammox MBR via backpropagation neural network model.

Bioresource technology
Predicting thermodynamic adhesion energies was a critical strategy for mitigating membrane fouling. This study utilized a backpropagation (BP) neural network model to predict the thermodynamic adhesion energies associated with membrane fouling in a p...

Intelligent Detection and Recognition of Marine Plankton by Digital Holography and Deep Learning.

Sensors (Basel, Switzerland)
The detection, observation, recognition, and statistics of marine plankton are the basis of marine ecological research. In recent years, digital holography has been widely applied to plankton detection and recognition. However, the recording and reco...