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19,493 results for “Populism”
Fig. 5 in Morphological characters and SNP markers suggest hybridization and introgression in sympatric populations of the pleurocarpous mosses Homalothecium lutescens and H. sericeum
Fig. 5 Principal component analysis of 14 leaf characters from 240 specimens representing allopatric and sympatric populations of Homalothecium lutescens and H. sericeum. The first two axes (PC1 and PC2) representing together 36% of variation are shown. The colours and shapes of data points correspond to the population of the specimens. Leaf
Fig. 2 in Morphological characters and SNP markers suggest hybridization and introgression in sympatric populations of the pleurocarpous mosses Homalothecium lutescens and H. sericeum
Fig. 2 (a) Measurement of capsule orientation in relation to the seta in Homalothecium as the angle (in degrees) between the seta and spore capsule at the basis of the spore capsule. (b) Capsule inclinations of individuals from the allopatric populations fell into the black ranges of variation; in the sympatric populations individuals occurred with capsule inclinations ranging outside typical capsule inclinations of the pure species (red zone: 150°- 164°), indicating hybrid origin
Fig. 2 Micromorphological differences between Drepanocladus longifolius and D in Do Antarctic populations represent local or widespread phylogenetic and ecological lineages? Complicated fate of bipolar moss concepts with Drepanocladus longifolius as a case study
Fig. 2 Micromorphological differences between Drepanocladus longifolius and D. capillifolius. Alar cells of D. longifolius a, b—from Lyall 47, Falkland Islands. Alar cells of D. capillifolius c―from Nelson 4262, USA, Wyoming (KRAM), d―from isolectotype of Hypnum capillifolium var. fallax Renauld, Canada, Quebec. Scale bar 100 μm
Fig. 1 in Do Antarctic populations represent local or widespread phylogenetic and ecological lineages? Complicated fate of bipolar moss concepts with Drepanocladus longifolius as a case study
Fig. 1 Geographical distribution of the studied accessions and detected genetic lineages corresponding to Drepanocladus longifolius (blue dots) and D. capillifolius (green triangles) according to present circumscription.
Fig. 2 in Genetic diversity and population structure of endangered Neofinetia falcata (Orchidaceae) in South Korea based on microsatellite analysis
Fig. 2. Structure analyses for putative genetic clusters of N. falcata. A: Graphs of ΔK values to determine the ideal number of groups present in the accessions of N. falcata. B: Estimated genetic structure of the 3 populations of brinjal based on STRUCTURE analysis K = 2 and K = 3.
Fig. 6 in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 6. Phylogenetic relationships of Microstomum Schmidt, 1848 inferred from ML analysis of partial COI gene. Outgroups were selected based on the phylogenetic hypothesis presented in Janssen et al. (2015). Numbers at nodes represent bootstrap support. Genbank accession numbers are listed after each taxon name.
Fig. 2 in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 2. Microstomum edmondi sp. nov. A. Entire body. B. Anterior end with focus on glands around mouth. C. Posterior end with focus on adhesive papillae. D. Anterior end of male specimen. E. Anterior end of female specimen. Abbreviations: a = auricles (ciliary pits); ap = adhesive papillae; b = brain; eg = egg; i = intestine; m = mouth; o = ovary; ph = pharynx; r = rhabdite bundle; st = male stylet; t = testis; vs = vesicula seminalis.
Fig. 1 in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 1. Microstomum laurae sp. nov. A. Composite image of whole body. B. Anterior end. C. Posterior end. Abbreviations: a = auricles (ciliary pits); ap = adhesive papillae; b = brain; e = eyespots; i = intestine; m = mouth; n = nematocyst; ph = pharynx; r = rhabdite. Arrowheads indicate orange lipid droplets.
Fig. 5. Microstomum rubromaculatum von Graff, 1882, composite sketches. A in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 5. Microstomum rubromaculatum von Graff, 1882, composite sketches. A. Ventral view of entire body. B. Lateral view of posterior end. C. Lateral view of stylet. D. Ventral view of stylet. Abbreviations: a = auricles (ciliary pits); am = antrum masculinum; ap = adhesive papillae; b = brain; eg = egg; fp = female pore; i = intestine; m = mouth; mp = male pore; o = ovary; ph = pharynx; s = sperm; st = male stylet; t = testis; vs = vesicula seminalis.
Fig. 4. Microstomum rubromaculatum von Graff, 1882. A. Entire body. B in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 4. Microstomum rubromaculatum von Graff, 1882. A. Entire body. B. Anterior end with focus on glands around mouth. C. Nematocysts. D. Posterior end with focus on reproductive anatomy. E. Male stylet. Abbreviations: a = auricles (ciliary pits); am = antrum masculinum; b = brain; gl = glands; i = intestine; m = mouth; o = ovary; ph = pharynx; s = sperm; st = male stylet; t = testis; vs = vesicula seminalis. Arrowheads indicate orange lipid droplets.
Fig. 3 in Microstomum (Platyhelminthes, Macrostomorpha, Microstomidae) from the Swedish west coast: two new species and a population description
Fig. 3. Microstomum edmondi sp. nov., composite sketches. A. Entire body of male specimen. B. Posterior end of female specimen. C. Stylet. Abbreviations: a = auricles (ciliary pits); ap = adhesive papillae; b = brain; eg = egg; i = intestine; m = mouth; n = nematocysts; o = ovary; ph = pharynx; r = rhabdites; st = male stylet; t = testis; vs = vesicula seminalis.
Figure 2.(a)Results of the Monte-Carlo simulations describing a population of elderly patients after a single oral dose of propranolol.-The Brain and Propranolol Pharmacokinetics in the Elderly
<p>In effort to identify the recommended Propranolol dosage for elderly patients, we identified<br> the patient package inserts from the Food and Drug Administration (FDA) Inderal label, who<br> manufacture propranolol. Based from FDA Wyeth Propranolol label, for dosing in the geriatric<br> population,the label states that there were not sufficient numbers of clinical study participants who<br> were 65-years and older to properly determine the difference in response young and elderly<br> patients.</p>
Figure 4. Simulation (Monte-Carlo, n=200) results elderly patients taking a 10mg oral dose resulting in similar Cmax, maximum plasma concentration, to the young patients taking a 40mg oral dose. The dotted lines illustrate the 10th and 90th percentiles of plasma levels of the elderly population with a 10mg oral administration of propranolol.-The Brain and Propranolol Pharmacokinetics in the Elderly
<p>Thus, the package insert (see 1) recommends clinicians start at the lower end of the dosing<br> range, without further details.<br> Similarly, Pfizer manufactures Inderal® LA (Propranolol HCI), which is the long-acting<br> form of propranolol and their package insert (see 2) states, “There is no information available for<br> elderly patients.” Though the kinetics for the long-acting formdiffers from the standard form,<br> manufactured by Wyeth, we would suspect a 10mg dose for the elderly would achieve a similar<br> maximum plasma concentration (Cmax) to that of the younger patient cohort.This 10mg, which is<br> 25% of the original 40mg, dosing schedule is based on our simulations at 10mg in the geriatric<br> population.</p>
A Genetic Algorithm Approach to Regenerate Image from a Reduce Scaled Image Using Bit Data Count-Figure 11. Initial population
<p>In figure 11 it is the initial population showed and figure 12 the population started to change and figure 13 we reached a convergence.</p>
The Optimal Species Richness Environments for Human Populations
<p>This supporting document should allow one to recreate the analysis performed as part of “The optimal species richness environments for human populations, ” By Freeman et al. 2018 Submitted to PNAS July 2018. The annotated scripts in this directory (RichnessSIScripts.pdf) contain code to replicate the analysis, as well as code for additional analyses not included in the main paper or supplemental information. To replicate the analysis, one can either analyze the data files provided or build their own data set. As discussed in the main body of the text, we built three data sets following the procedures outlined by Tallavaara et al. (2017) for linking species richness values, net primary productivity and pathogen stress to each ethnographic case. We do not replicate the scripts provided by Tallavaara et al.(2017) as these are available, clear and should be cited when used.To replicate our analysis, one needs to set their working directory in R to the file location that contains the data files. There are 11 files that follow the naming convention “name.csv.” The 11 files are “MainFinal.csv”. “AGPOP3Eco.csv”, “HGFEM4R.csv”, “AGPOPClass.csv”, “CountryMeansEco2.csv”, “AGPOP3EcoH.csv”, “AGPOP3EcoL.csv”, “HiHG.csv”, “LowHG,csv”, “CountryMeansEco2H.csv”, and “CountryMeansEco2L.csv”. The first five files are the main files, the second six files are divided into high and low species richness environments by economy type for convenience. In each file, the variables are defined as follows:</p> <p>1. Group/Country–name of the ethnographic society of country</p> <p>2. Latitude–the latitude at the geographic center of a group’s territory or a country’s territory.</p> <p>3. Longitude–the longitude at the geographic center of a group’s territory or a country’s territory.</p> <p>4. Class–an ordinal ranking of wealth and status differentiation among the hunter-gatherer and agriculturalists societies (see main text for more details)</p> <p>5. Class2–an binary ranking of wealth and status differentiation among the hunter-gatherer and agriculturalists societies (see main text for more details).</p> <p>6. ECI–The average economic complexity index since 1973 as measured among modern countries.</p> <p>7. DENSITY–Population density in people per square kilometer. This is a point in time estimatefor hunter-gatherer and agricultural groups and an average density since 1973 among nation states.</p> <p>8. LnDENSITY–The natural log of population density</p> <p>9. npp–net primary productivity estimated at the center of each group’s territory</p> <p>10. npp2-Net primary productivity squared</p> <p>11. biodiv–Standardized estimate of species richness at the center of each group’s range.</p> <p>12. biodiv2–Species richness *100 ad squared.</p> <p>13. pathos–Index of pathogen stress at the center of a group’s territory.</p> <p>14. DivDiff–The absolute value of species richness-the species richness value of peak population density (values identified in Fig. 2 of the main manuscript).1</p> <p>5. ID–A nominal variable that denotes economy type. HG=hunter-gatherer, AG=subsistence agriculturalist, IND=modern nation state</p> <p> </p> <p>Tallavaara, M., J. T. Eronen, and M. Luoto2017. Supporting data and script for ”productivity, biodiversity, and pathogens influence the global hunter-gatherer population density” (Tallavaara et al. pnas 2018).<a href="https://doi.org/10.5281/zenodo.1167852">https://doi.org/10.5281/zenodo.1167852</a></p>
Comparison and Assessment of Family- and Population-based Genotype Imputation Methods in Large Pedigrees Dataset
<p>Here is the data corresponding to the paper "Comparison and Assessment of Family- and Population-based Genotype Imputation Methods in Large Pedigrees" submitted to Genome Research. The data includes the following:<br> <br> Simulated data for 1200 African and European subjects in pedigrees.<br> Lists of subjects selected by each of the 4 subject selection methods examined; Primus, GIGI-Pick, Exome-Picks, and Random selection. <br> <br> The positions of sparse markers for gl_auto for African and European data.<br> <br> The lists of GWAS SNPs for AFR and EUR. </p> <p>Please see the paper for further details of the data generation, this metadata will be updated following publication. </p>
The Accretion History of AGN I: Supermassive Black Hole Population Synthesis Model
<p>The X-ray Luminosity Function attached to this paper: https://ui.adsabs.harvard.edu/#abs/arXiv:1810.02298</p> <p>The python script contains instructions on how to calculate space densities using the numpy array.</p>
Interspecific competition affects the expression of personality-traits in natural populations
<p>Interspecific competition can cause niche partitioning among species in a community and shape an individual’s phenotype, including its behaviour. However, little is known about how interspecific competition affects the expression of animal personality. We investigated whether the occurrence of competing alien grey squirrels (<em>Sciurus carolinensis</em>) altered personality traits in native Eurasian red squirrels (<em>Sciurus vulgaris</em>). We compared personality traits of red squirrels in red-only (no interspecific competition) and red-grey (with interspecific competition) sites, using arena tests. Open Field Test returned repeatable estimates of activity and shyness, Mirror Image Stimulation test of sociability and avoidance of a conspecific. Red squirrels competing with the alien species had higher sociability and slightly lower avoidance than in red-only sites. Moreover, an individual’s probability to survive was not affected by any of the personality traits, but more active females were more likely to wean a litter than shy ones. This relationship was not affected by the presence or absence of the alien competitor. Our findings suggest that the occurrence of certain personality traits in red squirrels was affected by interspecific competition not as a consequence of short-term selection, but more likely as a result of context-related advantages of sociability or avoidance.</p>
Populations_over_years
<p>Populations of hares, carrots and lynces over several years. </p>
SNP call data for: The current epidemic of the barley pathogen Ramularia collo-cygni derives from a recent population expansion and shows global admixture
<p>Ramularia Leaf Spot is becoming an ever increasing problem in main barley growing regions since the 1980s, causing up to 70% yield loss in extreme cases. Yet, the causal agent <em>Ramularia collo-cygni</em>, remains poorly studied. The diversity of the pathogen in the field thus far remains unknown. Furthermore, it is unknown to which extend the pathogen has a sexual reproductive cycle. To date, the teleomorph of <em>R. collo-cygni</em> has not been observed.</p> <p>To study the genetic diversity of <em>R. collo-cygni </em>and to get more insights into its biology, we sequenced the genomes of 19 <em>R. collo-cygn</em>i isolates from multiple geographic locations and diverse hosts. Here we share the SNP call data as well as the reference genome.</p> <p>The reference genome files and assembly can be found on ENI: GCA_900074925.1</p> <p>https://www.ebi.ac.uk/ena/data/view/GCA_900074925.1</p> <p>The raw sequence data is also available through ENI: ERX2296228</p> <p>https://www.ebi.ac.uk/ena/data/view/ERX2296228</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.