AIMC Topic: Animals

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Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach.

PLoS neglected tropical diseases
BACKGROUND: Leptospirosis is a neglected zoonotic disease prevalent worldwide, particularly in tropical regions experiencing frequent rainfall and severe cyclones, which are further aggravated by climate change. This bacterial zoonosis, caused by the...

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis.

PloS one
The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research ...

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis.

Developmental cell
The 5' UTRs of mRNAs are critical for translation regulation during development, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massivel...

Decoding the blueprint of receptor binding by filoviruses through large-scale binding assays and machine learning.

Cell host & microbe
Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) is an essential entry receptor, with amino acid variations influencing viral susceptibility and spec...

Neural mechanisms of relational learning and fast knowledge reassembly in plastic neural networks.

Nature neuroscience
Humans and animals have a striking ability to learn relationships between items in experience (such as stimuli, objects and events), enabling structured generalization and rapid assimilation of new information. A fundamental type of such relational l...

Acrobatics at the insect scale: A durable, precise, and agile micro-aerial robot.

Science robotics
Aerial insects are exceptionally agile and precise owing to their small size and fast neuromotor control. They perform impressive acrobatic maneuvers when evading predators, recovering from wind gust, or landing on moving objects. Flapping-wing propu...

A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications.

PloS one
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge ...

Dorsoventral comparison of intraspecific variation in the butterfly wing pattern using a convolutional neural network.

Biology letters
Butterfly wing patterns exhibit notable differences between the dorsal and ventral surfaces, and morphological analyses of them have provided insights into the ecological and behavioural characteristics of wing patterns. Conventional methods for dors...

Optimizing automated photo identification for population assessments.

Conservation biology : the journal of the Society for Conservation Biology
Several legal acts mandate that management agencies regularly assess biological populations. For species with distinct markings, these assessments can be conducted noninvasively via capture-recapture and photographic identification (photo-ID), which ...

Swarm-initialized adaptive controller with beetle antenna searching of wearable lower limb exoskeleton for sit-to-stand and walking motions.

ISA transactions
In recent years, exoskeleton robots have attracted great interest from researchers in the area of robotics due to their ability to assist human functionality improvement. A wearable lower limb exoskeleton is aimed at supporting the limb functionality...