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Innovative behaviour may allow animals to cope with changes in their environment. Innovative propensities are known to vary widely both between and within species, and a growing body of research has begun to examine the factors that drive individuals to innovate. Evidence suggests that individuals are commonly driven to innovate by necessity; for instance by hunger or because they are physically unable to outcompete others for access to resources. However, it is not known whether the factors that drive individuals to innovate are stable across contexts. We examined contextual variation in the drivers of innovation in rock pool prawns (Palaemon spp), invertebrates that face widely fluctuating environments and may, through the actions of tides and waves, find themselves isolated or in groups. Using two novel foraging tasks, we examined the effects of body size and hunger in prawns tested in solitary and group contexts. When tested alone, small prawns were significantly more likely to succeed in a spatial task, and faster to reach the food in a manipulation task, while hunger state had no effect. In contrast, size had no effect when prawns were tested in groups, but food-deprived individuals were disproportionately likely to innovate in both tasks. We suggest that contextual variation in the drivers of innovation is likely to be common in animals living in variable environments, and may best be understood by considering variation in the perception of relative risks and rewards under different conditions. 相似文献
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NetLogoR is an R package to build and run spatially explicit agent‐based models (SE‐ABMs) using the R language. SE‐ABMs are models that simulate the fate of entities at the individual level within a spatial context and where patterns emerge at the population level. NetLogoR follows the same framework as the NetLogo software (Wilensky 1999). Rather than a call function to use the NetLogo software, NetLogoR is a translation into the R language of the structure and functions of NetLogo. Models built with NetLogoR are written in R language and are run on the R platform; no other software or language has to be involved. NetLogoR provides new R classes to define model agent objects and functions to implement spatially explicit agent‐based models in the R environment. Users of this package benefit from the fast and easy coding provided by the highly developed NetLogo framework, coupled with the versatility, power and massive resources of the R language. 相似文献
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Mocelin Ricieri Marcon Matheus D’ambros Simone Herrmann Ana P. da Rosa Araujo Alex Sander Piato Angelo 《Neurochemical research》2018,43(2):458-464
Neurochemical Research - Alcohol hangover refers to unpleasant symptoms experienced as a direct consequence of a binge drinking episode. The effects observed in this condition are related to the... 相似文献
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Rocha Vanesca Priscila Camargo Gonçalves-Vidigal Maria Celeste Ortiz Alex Henrique Tiene Valentini Giseli Ferreira Rebecca Caroline Ulbricht Gonçalves Tiago Maretti Lacanallo Giselly Figueiredo Vidigal Filho Pedro Soares 《Plant Molecular Biology Reporter》2020,38(1):25-38
Plant Molecular Biology Reporter - Manihot esculenta Crantz is originally from the Amazon region of Brazil, which has the highest genetic diversity. Due to the wide adaptation of cassava to the... 相似文献
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Saleta Sierra J. Nikolai Dybowski Alejandro Pironti Dominik Heider Lisa Güney Alex Thielen Stefan Reuter Stefan Esser Gerd F?tkenheuer Thomas Lengauer Daniel Hoffmann Herbert Pfister Bj?rn Jensen Rolf Kaiser 《PloS one》2015,10(5)
ObjectivesWe analysed the impact of different parameters on genotypic tropism testing related to clinical outcome prediction in 108 patients on maraviroc (MVC) treatment.Methods87 RNA and 60 DNA samples were used. The viral tropism was predicted using the geno2pheno[coreceptor] and T-CUP tools with FPR cut-offs ranging from 1%-20%. Additionally, 27 RNA and 28 DNA samples were analysed in triplicate, 43 samples with the ESTA assay and 45 with next-generation sequencing. The influence of the genotypic susceptibility score (GSS) and 16 MVC-resistance mutations on clinical outcome was also studied.ResultsConcordance between single-amplification testing compared to ESTA and to NGS was in the order of 80%. Concordance with NGS was higher at lower FPR cut-offs. Detection of baseline R5 viruses in RNA and DNA samples by all methods significantly correlated with treatment success, even with FPR cut-offs of 3.75%-7.5%. Triple amplification did not improve the prediction value but reduced the number of patients eligible for MVC. No influence of the GSS or MVC-resistance mutations but adherence to treatment, on the clinical outcome was detected.ConclusionsProviral DNA is valid to select candidates for MVC treatment. FPR cut-offs of 5%-7.5% and single amplification from RNA or DNA would assure a safe administration of MVC without excluding many patients who could benefit from this drug. In addition, the new prediction system T-CUP produced reliable results. 相似文献