بدائل البحث:
significant factor » significant factors (توسيع البحث)
factor decrease » factors increases (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
significant factor » significant factors (توسيع البحث)
factor decrease » factors increases (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
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481
All data points from S1 to S5 Figs as well as the supplementary method table.
منشور في 2025الموضوعات: -
482
Remyelination in adulthood leads to an incomplete restoration of PV interneuron properties.
منشور في 2025الموضوعات: -
483
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484
-
485
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486
-
487
Effect of KV3 modulation on PV interneuron firing frequency and on autaptic release.
منشور في 2025الموضوعات: -
488
-
489
-
490
-
491
Juvenile demyelination impairs the maturation of PV interneurons in the PFC.
منشور في 2025الموضوعات: -
492
-
493
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494
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495
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496
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497
Adult demyelination has no effect on PV interneuron’s firing rate or failures in autaptic responses.
منشور في 2025الموضوعات: -
498
Autapses play a crucial role in PV interneuron’s sustained firing at high frequencies.
منشور في 2025الموضوعات: -
499
-
500
Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas
منشور في 2025"…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…"