AIMC Topic: Animals

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Wireless Magnetic Robot for Precise Hierarchical Control of Tissue Deformation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mechanotherapy has emerged as a promising treatment for tissue injury. However, existing robots for mechanotherapy are often designed on intuition, lack remote and wireless control, and have limited motion modes. Herein, through topology optimization...

Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing.

Scientific reports
Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this is often overlooked because existing approaches are labour-intensive, need calibration, and are commonly perceived as inaccurate. Machine-learning pro...

Leveraging camera traps and artificial intelligence to explore thermoregulation behaviour.

The Journal of animal ecology
Behavioural thermoregulation has critical ecological and physiological consequences that profoundly influence individual fitness and species distributions, particularly in the context of climate change. However, field monitoring of this behaviour rem...

Classification of subtask types and skill levels in robot-assisted surgery using EEG, eye-tracking, and machine learning.

Surgical endoscopy
BACKGROUND: Objective and standardized evaluation of surgical skills in robot-assisted surgery (RAS) holds critical importance for both surgical education and patient safety. This study introduces machine learning (ML) techniques using features deriv...

Computational Insights into Reproductive Toxicity: Clustering, Mechanism Analysis, and Predictive Models.

International journal of molecular sciences
Reproductive toxicity poses significant risks to fertility and progeny health, making its identification in pharmaceutical compounds crucial. In this study, we conducted a comprehensive in silico investigation of reproductive toxic molecules, identif...

δ-Conotoxin Structure Prediction and Analysis through Large-Scale Comparative and Deep Learning Modeling Approaches.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The δ-conotoxins, a class of peptides produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage-gated sodium channels causing paralysis and other neurological responses, but difficulties in thei...

Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea.

Food chemistry
Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REI...

A personal view on the history of toxins: From ancient times to artificial intelligence.

Toxicon : official journal of the International Society on Toxinology
Bioactive substances found in plants, microorganisms and animals have fascinated mankind since time immemorial. This review will focus on the progress that has been made over the centuries and our growing insights. The developments relate to both the...

Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles.

Analytical and bioanalytical chemistry
This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15-3 (CA 15-3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learni...

Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

Magnetic resonance in medicine
PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods.