AIMC Topic: Spiders
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Unsupervised learning reveals rapid gait adaptation after leg loss and regrowth in spiders.
The Journal of experimental biology
Jun 17, 2025
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...
Individual-Level Prediction of Exposure Therapy Outcome Using Structural and Functional MRI Data in Spider Phobia: A Machine-Learning Study.
Depression and anxiety
Aug 22, 2023
Machine-learning prediction studies have shown potential to inform treatment stratification, but recent efforts to predict psychotherapy outcomes with clinical routine data have only resulted in moderate prediction accuracies. Neuroimaging data showe...
Modeling and design of heterogeneous hierarchical bioinspired spider web structures using deep learning and additive manufacturing.
Proceedings of the National Academy of Sciences of the United States of America
Jul 24, 2023
Spider webs are incredible biological structures, comprising thin but strong silk filament and arranged into complex hierarchical architectures with striking mechanical properties (e.g., lightweight but high strength, achieving diverse mechanical res...
Predicting mechanical properties of silk from its amino acid sequences via machine learning.
Journal of the mechanical behavior of biomedical materials
Feb 22, 2023
The silk fiber is increasingly being sought for its superior mechanical properties, biocompatibility, and eco-friendliness, making it promising as a base material for various applications. One of the characteristics of protein fibers, such as silk, i...
Artificial intelligence and multidisciplinary team meetings; a communication challenge for radiologists' sense of agency and position as spider in a web?
European journal of radiology
Mar 11, 2022
PURPOSE: This paper focuses on how the implementation of artificial intelligence algorithms (AI) challenges and changes the existing communication practice in radiology seen from a psychological communicative and clinical radiologist's perspective.
A Deep Learning Approach with Data Augmentation to Predict Novel Spider Neurotoxic Peptides.
International journal of molecular sciences
Nov 13, 2021
As major components of spider venoms, neurotoxic peptides exhibit structural diversity, target specificity, and have great pharmaceutical potential. Deep learning may be an alternative to the laborious and time-consuming methods for identifying these...
Spider webs inspiring soft robotics.
Journal of the Royal Society, Interface
Nov 11, 2020
In soft robotics, bio-inspiration ranges from hard- to software. Orb web spiders provide excellent examples for both. Adapted sensors on their legs may use morphological computing to fine-tune feedback loops that supervise the handling and accurate p...
Machine learning approaches identify male body size as the most accurate predictor of species richness.
BMC biology
Aug 28, 2020
BACKGROUND: A major challenge in biodiversity science is to understand the factors contributing to the variability of species richness -the number of different species in a community or region - among comparable taxonomic lineages. Multiple biotic an...
On-line anxiety level detection from biosignals: Machine learning based on a randomized controlled trial with spider-fearful individuals.
PloS one
Jun 23, 2020
We present performance results concerning the validation for anxiety level detection based on trained mathematical models using supervised machine learning techniques. The model training is based on biosignals acquired in a randomized controlled tria...
Bio-inspired, Moisture-Powered Hybrid Carbon Nanotube Yarn Muscles.
Scientific reports
Mar 14, 2016
Hygromorph artificial muscles are attractive as self-powered actuators driven by moisture from the ambient environment. Previously reported hygromorph muscles have been largely limited to bending or torsional motions or as tensile actuators with low ...
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