The learning flights and walks of bees, wasps and ants are precisely coordinated movements that enable insects to memorise the visual surroundings of their nest or other significant places such as foraging sites. These movements occur on the first few occasions that an insect leaves its nest. They are of special interest because their discovery in the middle of the 19th century provided perhaps the first evidence that insects can learn and are not solely governed by instinct. Here, we recount the history of research on learning flights from their discovery to the present day. The first studies were conducted by skilled naturalists and then, over the following 50 years, by neuroethologists examining the insects' learning behaviour in the context of experiments on insect navigation and its underlying neural mechanisms. The most important property of these movements is that insects repeatedly fixate their nest and look in other favoured directions, either in a preferred compass direction, such as North, or towards preferred objects close to the nest. Nest facing is accomplished through path integration. Memories of views along a favoured direction can later guide an insect's return to its nest. In some ant species, the favoured direction is adjusted to future foraging needs. These memories can then guide both the outward and homeward legs of a foraging trip. Current studies of central areas of the insect brain indicate what regions implement the behavioural manoeuvres underlying learning flights and the resulting visual memories.
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http://dx.doi.org/10.1242/jeb.245278 | DOI Listing |
PLoS One
January 2025
School of Physical Education, Jinjiang College, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
In athletes' competitions and daily training, in order to further strengthen the athletes' sports level, it is usually necessary to analyze the athletes' sports actions at a specific moment, in which it is especially important to quickly and accurately identify the categories and positions of the athletes, sports equipment, field boundaries and other targets in the sports scene. However, the existing detection methods failed to achieve better detection results, and the analysis found that the reasons for this phenomenon mainly lie in the loss of temporal information, multi-targeting, target overlap, and coupling of regression and classification tasks, which makes it more difficult for these network models to adapt to the detection task in this scenario. Based on this, we propose for the first time a supervised object detection method for scenarios in the field of motion management.
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January 2025
Vocational Training Center, FoShan Open University, FoShan, Guangdong Province, China.
Data classification is an important research direction in machine learning. In order to effectively handle extensive datasets, researchers have introduced diverse classification algorithms. Notably, Kernel Extreme Learning Machine (KELM), as a fast and effective classification method, has received widespread attention.
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January 2025
Logistics service company, Civil Aviation Flight University of China, Guanghan, Sichuan, China.
The risk assessment and prevention in traditional airport safety assurance usually rely on human experience for analysis, and there are problems such as heavy manual workload, excessive subjectivity, and significant limitations. This article proposed a risk assessment and prevention mechanism for airport security assurance that integrated LSTM algorithm. It analyzed the causes of malfunctioning flights by collecting airport flight safety log datasets.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Wake Forest Alzheimer's Disease Research Center, Winston-Salem, NC, USA.
Background: Western and Mediterranean diets differentially affect cerebral cortical gene expression, brain structure, and socioemotional behavior in middle-aged female nonhuman primates (NHP) (Macaca fascicularis). In this study, we investigate the effect of diet on brain molecular composition.
Method: Using a machine learning approach, we quantified the impact of these diets on the presynaptic proteome in the lateral temporal cortex determined by synaptometry by time of flight (SynTOF) mass spectrometry and examined associations between the proteome, transcriptome, and an array of multisystem phenotypes.
Sci Rep
January 2025
Ordos Institute of Liaoning Technical University, Liaoning Technical University, Ordos, 017000, China.
This study focuses on the construction and interpretation of a mine water inrush source identification model to enhance the precision and credibility of the model. For water inrush source identification and feature analysis, a novel method combining XGBoost and SHAP is suggested. The model uses Ca, Mg, K + Na, HCO, Cl, SO, Hardness, and pH as discriminators, and the key parameters in the XGBoost model are optimized by introducing the improved sparrow search algorithm.
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