1,720,981 research outputs found
ANOVA table for fledging age.
No full text<p>Reference level for treatment coefficients is prenatal maternal control treatment and matching environment. Brood size and hatching date centred.</p
ANOVA table and estimated coefficients – linear mixed model for nestling morphological traits.
No full text<p>Wing and tarsus models are repeated measures models with Nest of Origin and nestling ID as random factors. Hatching date and brood size are centred for ease of interpretation. <i>F</i> and <i>p</i> values stem from ANOVA table, and for non-significant interactions represent values just before removal (significance level for removal of interaction <i>p</i>>0.1). Reference = 8 days old female nestling from a prenatal maternal control and matching environment group. SE = standard error.</p
Mass growth curves.
No full text<p>Nestling mass on three measurement days (Mixed Effects Model estimations of mean ± SE). The shape of growth curves differed significantly according to the interaction between the treatments. When mothers were exposed to predation risk before or during ovulation, growth depended on offspring environment. When growing with predation risk, i.e. a matching environment, early growth rate increased (steeper slope between days 2–8) compared to mismatching conditions. Under mismatching conditions, the fast mass gain, as well as reaching asymptotic mass, was postponed. C = mothers exposed to control treatment; P = mothers exposed to predator treatment.</p
ANOVA table and estimated coefficients – linear mixed model for nestling mass.
No full text<p>A repeated measurements model with nestling identification nested within Nest of Origin as random factors. Age was taken as an ordered categorical factor. Linear and Quadratic coefficient estimates of age are provided for each treatment group. Hatching date and brood size are centred for ease of interpretation. <i>F</i> and <i>p</i> values originate from the ANOVA table.</p><p>SE = standard error.</p>a<p>For a male compared to a female.</p
Fledging Age.
No full text<p>Fledging age (model estimations of mean ± SE) for offspring of mothers exposed to either control birds (C) or to predatory birds (P) before and during egg-laying, raised either under matching or mismatching conditions. Asterisk represents significant difference (<i>p</i><0.05).</p
Summaries for hatching and fledging probability GLMs.
No full text<p>Coefficients are untransformed and stem from a GLM with binomial (hatching probability) and Poisson (number fledged) errors. Laying and hatching are centered for ease of interpretation. Reference level for all models is a nest from the prenatal control-match treatments. Values for non-significant interactions are just before removal from the model. N2 = number of nestlings on day 2 after first hatch. SE = Standard error.</p
sj-docx-1-wso-10.1177_17474930231181010 – Supplemental material for Association of statin use and lipid levels with cerebral microbleeds and intracranial hemorrhage in patients with atrial fibrillation: A prospective cohort study
No full textSupplemental material, sj-docx-1-wso-10.1177_17474930231181010 for Association of statin use and lipid levels with cerebral microbleeds and intracranial hemorrhage in patients with atrial fibrillation: A prospective cohort study by Elisavet Moutzouri, Matthias Glutz, Nazanin Abolhassani, Martin Feller, Luise Adam, Baris Gencer, Cinzia Del Giovane, Sylvain Bétrisey, Rebecca E Paladini, Elisa Hennings, Stefanie Aeschbacher, Jürg H Beer, Giorgio Moschovitis, David Seiffge, Gian Marco De Marchis, Michael Coslovsky, Tobias Reichlin, Giulio Conte, Tim Sinnecker, Matthias Schwenkglenks, Leo H Bonati, Peter Kastner, Drahomir Aujesky, Michael Kühne, Stefan Osswald, Urs Fischer, David Conen and Nicolas Rodondi in International Journal of Stroke</p
Preparing Offspring for a Dangerous World: Potential Costs of Being Wrong
Full text linkAdaptive maternal responses to stressful environments before young are born can follow two non-exclusive pathways: either the mother reduces current investment in favor of future investment, or influences offspring growth and development in order to fit offspring phenotype to the stressful environment. Inducing such developmental cues, however, may be risky if the environment changes meanwhile, resulting in maladapted offspring. Here we test the effects of a predator-induced maternal effect in a predator-free postnatal environment. We manipulated perceived predation-risk for breeding female great tits by exposing them to stuffed models of either a predatory bird or a non-predatory control. Offspring were raised either in an environment matching the maternal one by exchanging whole broods within a maternal treatment group, or in a mismatching environment by exchanging broods among the maternal treatments. Offspring growth depended on the matching of the two environments. While for offspring originating from control treated mothers environmental mismatch did not significantly change growth, offspring of mothers under increased perceived predation risk grew faster and larger in matching conditions. Offspring of predator treated mothers fledged about one day later when growing under mismatching conditions. This suggests costs paid by the offspring if mothers predict environmental conditions wrongly
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
