AIMC Topic: Animals

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Machine learning-based optimal design of fibrillar adhesives.

Journal of the Royal Society, Interface
Fibrillar adhesion, observed in animals like beetles, spiders and geckos, relies on nanoscopic or microscopic fibrils to enhance surface adhesion via 'contact splitting'. This concept has inspired engineering applications across robotics, transportat...

A machine learning approach fusing multisource spectral data for prediction of floral origins and taste components of Apis cerana honey.

Food research international (Ottawa, Ont.)
This study explores the use of near-infrared (NIR), mid-infrared (MIR), and Raman spectral fusion for the rapid prediction of floral origins and main taste components in Apis cerana (A. cerana) honey. Feature-level fusion with the partial least squar...

Microfluidics with Machine Learning for Biophysical Characterization of Cells.

Annual review of analytical chemistry (Palo Alto, Calif.)
Understanding the biophysical properties of cells is essential for biological research, diagnostics, and therapeutics. Microfluidics enhances biophysical cell characterization by enabling precise manipulation and real-time measurement at the microsca...

Intelligent larval zebrafish phenotype recognition via attention mechanism for high-throughput screening.

Computers in biology and medicine
BACKGROUND: Larval zebrafish phenotypes serve as critical research indicators in fields such as ecotoxicology and safety assessment since phenotypic defects are closely related to alterations of underlying pathway. However, identifying these defects ...

Current methods in explainable artificial intelligence and future prospects for integrative physiology.

Pflugers Archiv : European journal of physiology
Explainable artificial intelligence (XAI) is gaining importance in physiological research, where artificial intelligence is now used as an analytical and predictive tool for many medical research questions. The primary goal of XAI is to make AI model...

Discrimination of inherent characteristics of susceptible and resistant strains of Anopheles gambiae by explainable artificial intelligence analysis of flight trajectories.

Scientific reports
Understanding mosquito behaviours is vital for the development of insecticide-treated nets (ITNs), which have been successfully deployed in sub-Saharan Africa to reduce disease transmission, particularly malaria. However, rising insecticide resistanc...

Bio-inspired interlocking metasurfaces.

Bioinspiration & biomimetics
Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, ...

Beyond human perception: challenges in AI interpretability of orangutan artwork.

Primates; journal of primatology
Drawings serve as a profound medium of expression for both humans and apes, offering unique insights into the cognitive and emotional landscapes of the artists, regardless of their species. This study employs artificial intelligence (AI), specificall...

Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.

ACS sensors
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...

Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets.

Renal failure
OBJECTIVES: Diabetic kidney disease (DKD) is driven by mitochondrial dysfunction and immune dysregulation, yet the mechanistic interplay remains poorly defined. This study aimed to identify key molecular networks linking mitochondrial and immune path...