AIMC Topic: Animals

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scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics.

Nature communications
Single-cell omics is the fastest-growing type of genomics data in the literature and public genomics repositories. Leveraging the growing repository of labeled datasets and transferring labels from existing datasets to newly generated datasets will e...

A System Using Artificial Intelligence to Detect and Scare Bird Flocks in the Protection of Ripening Fruit.

Sensors (Basel, Switzerland)
Flocks of birds may cause major damage to fruit crops in the ripening phase. This problem is addressed by various methods for bird scaring; in many cases, however, the birds become accustomed to the distraction, and the applied scaring procedure lose...

Can plants fool artificial intelligence? Using machine learning to compare between bee orchids and bees.

Plant signaling & behavior
Bee orchids have long been an excellent example of how dishonest signal works in plant-animal interaction. Many studies compared the flower structures that resemble female bees, leading toward pseudo-copulation of the male bees on the flower. Using M...

Endoscopic submucosal dissection using a detachable assistant robot: a comparative in vivo feasibility study (with video).

Surgical endoscopy
BACKGROUND: Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic submucosal dissection (ESD). We developed a robotic assistive traction device for flexible endoscopy and...

Drug repurposing: Iron in the fire for older drugs.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Repositioning or "repurposing" of existing therapies for indications of alternative disease is an attractive approach that can generate lower costs and require a shorter approval time than developing a de novo drug. The development of experimental dr...

An Approximate GEMM Unit for Energy-Efficient Object Detection.

Sensors (Basel, Switzerland)
Edge computing brings artificial intelligence algorithms and graphics processing units closer to data sources, making autonomy and energy-efficient processing vital for their design. Approximate computing has emerged as a popular strategy for energy-...

A multi-motion bionic soft hexapod robot driven by self-sensing controlled twisted artificial muscles.

Bioinspiration & biomimetics
Artificial muscles have unique advantages for driving bionic robots because their driving mode is similar to biological muscles. However, there is still a big gap between the existing artificial muscle and biological muscle in performance. The twiste...

Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...

Prediction of drug efficacy from transcriptional profiles with deep learning.

Nature biotechnology
Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning-based efficacy predicti...

Printed miniature robotic actuators with curvature-induced stiffness control inspired by the insect wing.

Bioinspiration & biomimetics
Stimuli-responsive actuating materials offer a promising way to power insect-scale robots, but a vast majority of these material systems are too soft for load bearing in different applications. While strategies for active stiffness control have been ...