AIMC Topic: Animals

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Mammalian piRNA target prediction using a hierarchical attention model.

BMC bioinformatics
BACKGROUND: Piwi-interacting RNAs (piRNAs) are well established for monitoring and protecting the genome from transposons in germline cells. Recently, numerous studies provided evidence that piRNAs also play important roles in regulating mRNA transcr...

Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition.

Scientific reports
The detection and classification of arrhythmia play a vital role in the diagnosis and management of cardiac disorders. Many deep learning techniques are utilized for arrhythmia classification in current research but only based on ECG data, lacking th...

Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis.

Communications biology
Human and animal health rely on balancing cell division and cell death to maintain normal homeostasis. This process is accomplished by regulated cell death (RCD), whose imbalance can lead to disease. Currently, the most frequently used method for ana...

Deliod a lightweight detection model for intestinal organoids based on deep learning.

Scientific reports
Intestinal organoids are indispensable tools for exploring intestinal disorders. Deep learning methodologies are often employed in morphological analysis to evaluate the condition of these organoids. Nonetheless, prevailing analytical techniques face...

RVDLAHA: An RISC-V DLA Hardware Architecture for On-Device Real-Time Seizure Detection and Personalization in Wearable Applications.

IEEE transactions on biomedical circuits and systems
Epilepsy is a globally distributed chronic neurological disorder that may pose a threat to life without warning. Therefore, the use of wearable devices for real-time detection and treatment of epilepsy is crucial. Additionally, personalizing disease ...

Application of 3D point cloud and visual-inertial data fusion in Robot dog autonomous navigation.

PloS one
The study proposes a multi-sensor localization and real-timeble mapping method based on the fusion of 3D LiDAR point clouds and visual-inertial data, which addresses the issue of decreased localization accuracy and mapping in complex environments tha...

Comparing statistical learning methods for complex trait prediction from gene expression.

PloS one
Accurate prediction of complex traits is an important task in quantitative genetics. Genotypes have been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regression methods, dimension reduction me...

Enhanced authentication of organic milk using MALDI-TOF MS with combined lipid-peptide fingerprinting and machine learning integration.

Food chemistry
This study introduces a method for authenticating organic milk and determining its geographic region using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Both lipids and peptides were analyzed, and their ...

Providing concentrate feed outside of the milking robot increases feed intake in dairy cows without reducing motivation to visit the robot.

Animal : an international journal of animal bioscience
Appropriate and adequate feeding is essential to maintaining good health, productivity and welfare of dairy cows. Within automatic milking systems, concentrate feed is offered inside the milking robot, and is thought to play a key role in motivating ...

Importance of dataset design in developing robust U-Net models for label-free cell morphology evaluation.

Journal of bioscience and bioengineering
Advances in regenerative medicine highlighted the need for label-free cell image analysis to replace conventional microscopic observation for non-invasive cell quality evaluation. Image-based evaluation provides an efficient, quantitative, and automa...