AIMC Topic: Fishes

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Machine learning models to predict the bioaccessibility of parent and substituted polycyclic aromatic hydrocarbons (PAHs) in food: Impact on accurate health risk assessment.

Journal of hazardous materials Oct 9, 2024
Food intake is the primary pathway for polycyclic aromatic hydrocarbons (PAHs) to enter the human body. Once ingested, PAHs tend to accumulate, posing health risks. To accurately assess the risk of PAHs from food, concentrations of 10 parent PAHs (PP...
Humans Machine Learning Animals Seafood Risk Assessment Polycyclic Aromatic Hydrocarbons Food Contamination Shellfish Fishes
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Machine learning-enabled attapulgite/polyimide nanofiber composite aerogels-based colorimetric sensor array for real-time monitoring of balsa fish freshness.

Food chemistry Sep 20, 2024
This paper presents the development and application of attapulgite/polyimide nanofiber composite aerogels (ATP/PI NFAs) integrated with a range of acid-base indicators, fabricated using electrospinning and freeze-drying technologies. A detailed chara...
Machine Learning Animals Colorimetry Fishes Seafood Silicon Compounds Gels Nanofibers Magnesium Compounds
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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

Scientific reports Sep 8, 2024
This paper presents the design and development of a coastal fisheries monitoring system that harnesses artificial intelligence technologies. Application of the system across the Pacific region promises to revolutionize coastal fisheries management. T...
Pacific Ocean Fisheries Deep Learning Fishes Conservation of Natural Resources Artificial Intelligence Animals Ecosystem
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Computer-Simulated Virtual Image Datasets to Train Machine Learning Models for Non-Invasive Fish Detection in Recirculating Aquaculture.

Sensors (Basel, Switzerland) Sep 7, 2024
Artificial Intelligence (AI) and Machine Learning (ML) can assist producers to better manage recirculating aquaculture systems (RASs). ML is a data-intensive process, and model performance primarily depends on the quality of training data. Relatively...
Computer Simulation Animals Image Processing, Computer-Assisted Aquaculture Fishes Artificial Intelligence Machine Learning
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Towards reliable data: Validation of a machine learning-based approach for microplastics analysis in marine organisms using Nile red staining.

Marine pollution bulletin Sep 5, 2024
Microplastic (MP) research faces challenges due to costly, time-consuming, and error-prone analysis techniques. Additionally, the variability in data quality across studies limits their comparability. This study addresses the critical need for reliab...
Machine Learning Plastics Oxazines Aquatic Organisms Animals Environmental Monitoring Water Pollutants, Chemical Mytilus edulis Microplastics Fishes Gastrointestinal Tract
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Machine learning-based q-RASAR predictions of the bioconcentration factor of organic molecules estimated following the organisation for economic co-operation and development guideline 305.

Journal of hazardous materials Sep 3, 2024
In this study, we utilized an innovative quantitative read-across (RA) structure-activity relationship (q-RASAR) approach to predict the bioconcentration factor (BCF) values of a diverse range of organic compounds, based on a dataset of 575 compounds...
Bioaccumulation Organisation for Economic Co-Operation and Development Water Pollutants, Chemical Fishes Quantitative Structure-Activity Relationship Algorithms Animals Organic Chemicals Machine Learning
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Fish-inspired tracking of underwater turbulent plumes.

Bioinspiration & biomimetics Sep 3, 2024
Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of...
Hydrodynamics Water Movements Animals Oceans and Seas Robotics Algorithms Equipment Design Fishes Computer Simulation Biomimetics Swimming
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Hydrodynamic pressure sensing for a biomimetic robotic fish caudal fin integrated with a resistive pressure sensor.

Bioinspiration & biomimetics Aug 22, 2024
Micro-sensors, such as pressure and flow sensors, are usually adopted to attain actual fluid information around swimming biomimetic robotic fish for hydrodynamic analysis and control. However, most of the reported micro-sensors are mounted discretely...
Animal Fins Equipment Failure Analysis Transducers Transducers, Pressure Biomimetic Materials Hydrodynamics Animals Biomimetics Robotics Swimming Equipment Design Pressure Fishes
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Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea.

Food chemistry Jul 20, 2024
Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REI...
Seafood Lasers China Machine Learning Geography Animals Mass Spectrometry Fishes
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Measuring activity-rest rhythms under different acclimation periods in a marine fish using automatic deep learning-based video tracking.

Chronobiology international Jul 8, 2024
Most organisms synchronize to an approximately 24-hour (circadian) rhythm. This study introduces a novel deep learning-powered video tracking method to assess the stability, fragmentation, robustness and synchronization of activity rhythms in . Exper...
Animals Deep Learning Circadian Rhythm Acclimatization Fishes Photoperiod Video Recording Behavior, Animal
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