Results 241 to 250 of about 147,191 (322)

Insights into garlic (Allium Sativum)'s nutrigenomics-associated fly-repellent potency in cattle. [PDF]

Trop Anim Health Prod
Mudau F, Durunna O, Mapiye C, Semwogerere F, Hagg F, Raffrenato E, Molotsi A.   +6 more
europepmc   +1 more source

Revision of the American parasitic flies belonging to the genus Winthemia

, 1931
H. J. Reinhard
openalex   +2 more sources

Flies and Campylobacter. [PDF]

American Journal of Public Health, 1986
openaire   +3 more sources

AInsectID Version 1.1: An Insect Species Identification Software Based on the Transfer Learning of Deep Convolutional Neural Networks

Advanced Intelligent Discovery, EarlyView.
This paper describes the basis for AInsectID Version 1, a GUI‐operable open‐source insect species identification, color processing, and image analysis software. This paper discusses our methods of algorithmic development, coupled to rigorous machine training used to enable high levels of validation accuracy.
Haleema Sadia, Parvez Alam
wiley   +1 more source

Developmental mitochondrial complex I activity determines lifespan. [PDF]

EMBO Rep
Stefanatos R, Robertson F, Castejon-Vega B, Yu Y, Uribe AH, Myers K, Kataura T, Korolchuk VI, Maddocks ODK, Martins LM, Sanz A.   +10 more
europepmc   +1 more source

The chrysotoxine syrphid-flies

, 1926
R. C. Shannon
openalex   +2 more sources

Microbial solutions to dietary stress: experimental evolution reveals host-microbiome interplay in <i>Drosophila melanogaster</i>. [PDF]

Proc Biol Sci
Henry L, Fernandez M, Webb A, Ayroles J.
europepmc   +1 more source

Redescription of types of American muscoid flies in the collection of the Vienna Natural History Museum, with incidental notes

, 1927
John Merton Aldrich
openalex   +2 more sources

Neuroecology of alcohol risk and reward: Methanol boosts pheromones and courtship success in <i>Drosophila melanogaster</i>. [PDF]

Sci Adv
Keesey IW, Doll G, Chakraborty SD, Baschwitz A, Lemoine M, Kaltenpoth M, Svatoš A, Sachse S, Knaden M, Hansson BS.   +9 more
europepmc   +1 more source

Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions

Advanced Intelligent Systems, EarlyView.
This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen, Hao Li, Guanwei Yan, Haojie Peng, Qian Zhang   +4 more
wiley   +1 more source