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841 results for “fruit flies”
Figure 8 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 8. Bactrocera (Bactrocera) allodistincta Leblanc and Doorenweerd, male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Figure 9 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 9. Bactrocera (Bactrocera) anomala (Drew), male. A) Head. B) Head and scutum. C) Scutellum details (from Drew 1989). D) Abdomen. E) Wing. F) Lateral view.
Figure 2 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 2. Cumulative number of species of Dacini in Oceania through time, starting with the description of Bactrocera longicornis (Macquart) in 1835 (insert).
Figure 4 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 4. Fruit sample processing steps in host fruit surveys. A) Fruit sample weighing. B–C) Fruits placed over juice-collecting inner container inside larger container with moist sawdust for pupation. D) Fruits incubated on petri dishes over moist sawdust. E) Author sifting sawdust to extract fly pupae in French Polynesia. F) Pupae from individual samples placed in ventilated emergence containers with fresh sawdust, with water and sugar provided to maintain emerging adults alive.
Figure 22 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 22. Bactrocera (Bactrocera) dorsalis (Hendel). A) Head. B) Head and scutum. C) Abdomen, female. D) Abdomen, male. E) Wing. F) Lateral view, female. G) Lateral view, male.
Figure 19 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 19. Bactrocera (Bactrocera) curvipennis (Froggatt). A) Head. B) Head and scutum. C) Abdomen, female. D) Abdomen, male. E) Wing. F) Wing, basal costal and costal cells. G) Lateral view, female.
Figure 3. Traps for fruit fly sampling. A–B in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 3. Traps for fruit fly sampling. A–B) Modified Steiner trap. C–H) Fruit fly trap model designed by the author.
Figure 16 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 16. Bactrocera (Bactrocera) caledoniensis Drew, male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Figure 31 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 31. Bactrocera (Bactrocera) froggatti (Bezzi), male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Figure 30 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 30. Bactrocera (Bactrocera) frauenfeldi (Schiner). Intraspecific variation in scutum and abdomen coloration.
Figure 29 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 29. Bactrocera (Bactrocera) frauenfeldi (Schiner). A) Head. B) Head and scutum. C) Abdomen, male. D) Wing. E) Lateral view, female.
Figure 27 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 27. Bactrocera (Bactrocera) epicharis (Hardy), male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Wing, basal costal and costal cells. F) Lateral view.
Figure 26 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 26. Bactrocera (Bactrocera) enochra (Drew), male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Figure 25 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 25. Bactrocera (Bactrocera) ebenea Drew, male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Figure 35 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 35. Bactrocera (Bactrocera) gnetum Drew and Hancock. A) Head. B) Head and scutum. C) Abdomen, female. D) Abdomen, male. E) Wing, female. F) Wing, male. G) Lateral view, male.
Figure 34 in The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 34. Bactrocera (Bactrocera) geminosimulata Leblanc and Doorenweerd, male. A) Head. B) Head and scutum. C) Abdomen. D) Wing. E) Lateral view.
Rapid and transient evolution of local adaptation to seasonal host fruits in an invasive pest fly
<p><span>Both local adaptation and adaptive phenotypic plasticity can influence the match between phenotypic traits and local environmental conditions. Theory predicts that environments stable for multiple generations promote local adaptation, while highly heterogeneous environments favor adaptive phenotypic plasticity. However, when environments have periods of stability mixed with heterogeneity, the relative importance of local adaptation and adaptive phenotypic plasticity is unclear. Here, we used <em>Drosophila suzukii</em> as a model system to evaluate the relative influence of genetic and plastic effects on the match of populations to environments with periods of stability from three to four generations. This invasive pest insect can develop within different fruits, and persists throughout the year in a given location on a succession of distinct host fruits, each one being available for only a few generations. Using reciprocal common environment experiments of natural <em>D. suzukii</em> populations collected from cherry, strawberry and blackberry, we found that both oviposition preference and offspring performance were higher on medium made with the fruit from which the population originated, than on media made with alternative fruits. This pattern, which remained after two generations in the laboratory, was analyzed using a statistical method we developed to quantify the contributions of local adaptation and adaptive plasticity in determining fitness. Altogether, we found that genetic effects (local adaptation) dominate over plastic effects (adaptive phenotypic plasticity). Our study demonstrates that spatially and temporally variable selection does not prevent the rapid evolution of local adaptation in natural populations. The speed and strength of adaptation may be facilitated by several mechanisms including a large effective population size and strong selective pressures imposed by host plants.</span></p>
Figure 135 in Erratum to Leblanc (2022): The dacine fruit flies (Diptera: Tephritidae: Dacini) of Oceania
Figure 135. Mean (±SE) daily captures of Dacus perpusillus (Drew) in cue-lure traps maintained in New Caledonia (Mainland, Lifou) between January 1996 and December 1998, based on 17 trapping sites (n = 612, mean FTD = 0.05).
Co-activation probability between neurons in the largest brain connectome of the fruit fly
<p>This is a data set containing the co-activation probability between neurons in the largest brain connectome of the fruit fly released by the FlyEM project. The co-activation probability is measured based on neural dynamics computation, where a standard leaky integrate-and-fire (LIF) model is applied on the connectome to generate neural dynamics. Please read the paper "Yang Tian, Pei Sun; <strong>Percolation may explain efficiency, robustness, and economy of the brain</strong>. <em><em>Network Neuroscience</em></em> 2022; 6 (3): 765–790. doi: <a href="https://doi.org/10.1162/netn_a_00246">https://doi.org/10.1162/netn_a_00246</a>" for more details.</p> <p><strong>This is the newest version of the data set.</strong></p> <p>The following is a list of variable information:</p> <p>(1) SomaLocation is a 23008*3 matrix that contains the three-dimensional coordinates of neurons;</p> <p>(2) LambdaVector is the vector of a vector of synaptic excitation-inhibition (E/I) balance (see "Percolation may explain efficiency, robustness, and economy of the brain" for detailed explanations).</p> <p>(3) DirectedCoactivationPattern is a cell of co-activation probability matrices generated under each E/I balance condition, which is used in "Percolation may explain efficiency, robustness, and economy of the brain" for computational experiments. The (i,j)-th element in the matrix is the probability for neuron i to activate neuron j under the corresponding E/I balance condition. Note that the (i,j)-th element can be differnt from the (j,i)-th element. </p> <p>(4) SymmetricCoactivationPattern is a cell of symmetric co-activation probability matrices generated under each E/I balance condition. This is a new data that has not been used in "Percolation may explain efficiency, robustness, and economy of the brain" yet. The (i,j)-th element in the matrix is the probability for neurons i and j to be co-activated under the corresponding E/I balance condition. If we define D as the directed co-activation probability matrix and denote S as the symmetric co-activation probability matrix, then we have S(i,j)=S(j,i)=0.5*(D(i,j)+D(j,i)). </p> <p>The earlist version of this data can be seen in https://zenodo.org/record/5497516, which may lack detailed explanations.</p> <p>The second version of this data can be seen in https://zenodo.org/record/7869532, where a small mistake is found while calculating the SymmetricCoactivationPattern. This mistake is resolved in the newest version.</p>
Fig. 21 in The Fruit Flies (Diptera, Tephritidae) In Bhutan: New Faunistic Records And Compendium Of Fauna
Fig. 21. Trypeta indica (a–c —non-type Ơ from Bhutan; d–f — holotype ♀ from Darjeeling): a — left-side lateral view; b — anterior view; c — dorsal view; d — right-side lateral view; e — abdomen, posterior; f — head, dorsal.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.