AIMC Topic: Larva

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Acoustic Denoising Using Artificial Intelligence for Wood-Boring Pests Larvae Early Monitoring.

Sensors (Basel, Switzerland)
Acoustic detection technology is a new method for early monitoring of wood-boring pests, and the effective denoising methods are the premise of acoustic detection in forests. This paper used sensors to record larval feeding sounds and various enviro...

Decoupling and Reprogramming the Wiggling Motion of Midge Larvae Using a Soft Robotic Platform.

Advanced materials (Deerfield Beach, Fla.)
The efficient motility of invertebrates helps them survive under evolutionary pressures. Reconstructing the locomotion of invertebrates and decoupling the influence of individual basic motion are crucial for understanding their underlying mechanisms,...

In-Field Detection of American Foulbrood (AFB) by Electric Nose Using Classical Classification Techniques and Sequential Neural Networks.

Sensors (Basel, Switzerland)
American foulbrood is a dangerous bee disease that attacks the sealed brood. It quickly leads to the death of bee colonies. Efficient diagnosis of this disease is essential. As specific odours are produced when larvae rot, it was investigated whether...

Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens.

Lab on a chip
Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that throug...

Exposure to polydopamine nanoparticles induces neurotoxicity in the developing zebrafish.

NanoImpact
Currently, the potential applications of polydopamine (PDA) nanoparticles in the biomedical field are being extensively studied, such as cell internalization, biocompatible surface modification, biological imaging, nano-drug delivery, cancer diagnosi...

Development of a deep learning model from breeding substrate images: a novel method for estimating the abundance of house fly (Musca domestica L.) larvae.

Pest management science
BACKGROUND: The application of computer vision and deep learning to pest monitoring has recently received much attention. Although several studies have demonstrated the application of object detection to the number of pests on a substrate, for house ...

The CPGs for Limbed Locomotion-Facts and Fiction.

International journal of molecular sciences
The neuronal networks that generate locomotion are well understood in swimming animals such as the lamprey, zebrafish and tadpole. The networks controlling locomotion in tetrapods remain, however, still enigmatic with an intricate motor pattern requi...

Deep learning-enhanced light-field imaging with continuous validation.

Nature methods
Visualizing dynamic processes over large, three-dimensional fields of view at high speed is essential for many applications in the life sciences. Light-field microscopy (LFM) has emerged as a tool for fast volumetric image acquisition, but its effect...

Towards Detecting Red Palm Weevil Using Machine Learning and Fiber Optic Distributed Acoustic Sensing.

Sensors (Basel, Switzerland)
Red palm weevil (RPW) is a detrimental pest, which has wiped out many palm tree farms worldwide. Early detection of RPW is challenging, especially in large-scale farms. Here, we introduce the combination of machine learning and fiber optic distribute...

Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network.

Scientific reports
Closed-cycle aquaculture using hatchery produced seed stocks is vital to the sustainability of endangered species such as Pacific bluefin tuna (Thunnus orientalis) because this aquaculture system does not depend on aquaculture seeds collected from th...