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Invertebrates

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Water quality of Danube Delta systems: ecological status and prediction using machine-learning algorithms.

Water science and technology : a journal of the International Association on Water Pollution Research
Environmental issues have a worldwide impact on water bodies, including the Danube Delta, the largest European wetland. The Water Framework Directive (2000/60/EC) implementation operates toward solving environmental issues from European and national ...

Modelling the presence and identifying the determinant factors of dominant macroinvertebrate taxa in a karst river.

Environmental monitoring and assessment
Modelling the macroinvertebrate community is important for evaluating the status of aquatic ecosystem health. Alternative to physical-based approaches, this study proposed two data-driven methods, support vector machine (SVM) and artificial neural ne...

Using fuzzy logic to determine the vulnerability of marine species to climate change.

Global change biology
Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biolog...

Sensory Feedback and Animal Locomotion: Perspectives from Biology and Biorobotics: An Introduction to the Symposium.

Integrative and comparative biology
The successful completion of many behaviors relies on sensory feedback. This symposium brought together researchers using novel techniques to study how different stimuli are encoded, how and where multimodal feedback is integrated, and how feedback m...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...

Automatic identification and morphological comparison of bivalve and brachiopod fossils based on deep learning.

PeerJ
Fossil identification is an essential and fundamental task for conducting palaeontological research. Because the manual identification of fossils requires extensive experience and is time-consuming, automatic identification methods are proposed. Howe...

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research.

Bioinspiration & biomimetics
Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevan...

Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.

Environment international
Practical, legal, and ethical reasons necessitate the development of methods to replace animal experiments. Computational techniques to acquire information that traditionally relied on animal testing are considered a crucial pillar among these so-cal...

Moving in an Uncertain World: Robust and Adaptive Control of Locomotion from Organisms to Machine Intelligence.

Integrative and comparative biology
Whether walking, running, slithering, or flying, organisms display a remarkable ability to move through complex and uncertain environments. In particular, animals have evolved to cope with a host of uncertainties-both of internal and external origin-...

Ethics of biohybrid robotics and invertebrate research: biohybrid robotic jellyfish as a case study.

Bioinspiration & biomimetics
Invertebrate research ethics has largely been ignored compared to the consideration of higher order animals, but more recent focus has questioned this trend. Using the robotic control ofas a case study, we examine ethical considerations in invertebra...