AIMC Topic: Animals

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AI-Enabled Mosquito Surveillance and Population Mapping Using Dragonfly Robot.

Sensors (Basel, Switzerland)
Mosquito-borne diseases can pose serious risks to human health. Therefore, mosquito surveillance and control programs are essential for the wellbeing of the community. Further, human-assisted mosquito surveillance and population mapping methods are t...

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load.

eLife
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of...

Automated identification of chicken distress vocalizations using deep learning models.

Journal of the Royal Society, Interface
The annual global production of chickens exceeds 25 billion birds, which are often housed in very large groups, numbering thousands. Distress calling triggered by various sources of stress has been suggested as an 'iceberg indicator' of chicken welfa...

HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images.

Computational intelligence and neuroscience
The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish re...

Exploring Deep Learning of Quantum Chemical Properties for Absorption, Distribution, Metabolism, and Excretion Predictions.

Journal of chemical information and modeling
Quantum mechanical (QM) descriptors of small molecules have wide applicability in understanding organic reactivity and molecular properties, but the substantial compute cost required for QM calculations limits their broad usage. Here, we investigate...

The signature-testing approach to mapping biological and artificial intelligences.

Trends in cognitive sciences
Making inferences from behaviour to cognition is problematic due to a many-to-one mapping problem, in which any one behaviour can be generated by multiple possible cognitive processes. Attempts to cross this inferential gap when comparing human intel...

Development and Application of Two Inducible Expression Systems for Streptococcus suis.

Microbiology spectrum
Streptococcus suis is an important zoonotic bacterial pathogen posing a threat to the pig industry as well as public health, for which the mechanisms of growth and cell division remain largely unknown. Developing convenient genetic tools that can ach...

SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction.

BMC genomics
BACKGROUND: Protein-protein interactions (PPIs) dominate intracellular molecules to perform a series of tasks such as transcriptional regulation, information transduction, and drug signalling. The traditional wet experiment method to obtain PPIs info...

Harris Hawk Optimization: A Survey onVariants and Applications.

Computational intelligence and neuroscience
In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along with an updated set of applications in well-established works. For th...

In silico prediction of chemical aquatic toxicity by multiple machine learning and deep learning approaches.

Journal of applied toxicology : JAT
Fish is one of the model animals used to evaluate the adverse effects of a chemical exposed to the ecosystem. However, its low throughput and relevantly high expense make it impossible to test all new chemicals in manufacture. Hence, using in silico ...