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Figure 5 in Bacterial diversity in high Andean grassland soils disturbed with Lepidium meyenii crops evaluated by metagenomics
Figure 5. Non-metric MSD and cluster analysis of sampling sectors divided by use pressure and sampling period factors.
Figure 2 in Evaluation of some nutritional quality criteria of seventeen Moroccan dates varieties and clones, fruits of date palm (Phoenix dactylifera L.)
Figure 2. Representation of dates varieties and clones according to their quality characteristics. (a) Representation of variables according to PCA. (b) Segregation of 17 dates varieties and clones according to their quality attributes.
Data from: Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
<p>Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ash (<em>Fraxinus pennsylvanica</em>) using 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross-validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic-genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially-explicit model. Approximate Bayesian Computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross-validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.</p>
SLF Evaluation Dataset
<p>This dataset was constructed from the test set split of the VoxCeleb 2 dataset (<a href="https://www.robots.ox.ac.uk/~vgg/data/voxceleb/vox2.html">VoxCeleb</a>). The VoxCeleb 2 test set contains 118 speakers each in several different videos. To develop this dataset, only one video per speaker was selected. A face image was also extracted from the video, as well as, a low resolution face image (8x8). Age, gender and ethnicity of the person in the face image were determined using the “DeepFace” library, a face recognition and facial attribute analysis library.</p> <p>This dataset can be used to evaluate speech2face, speech conditioned face generation and speech conditioned face super-resolution systems.</p>
Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
<p>Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets–with many taxa and/or many sites in the sequence alignment–or complex substitution models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time. To address this bottleneck, we incorporated the high-performance phylogenetic library BEAGLE into RevBayes, which enables multi-threading on multi-core CPUs and GPUs, as well as hardware-specific vectorized instructions for faster likelihood calculations. Our new implementation of RevBayes+BEAGLE retains the flexibility and dynamic nature that users expect from vanilla RevBayes. Additionally, we implemented a native parallelization within RevBayes without an external library using the message passing interface (MPI); RevBayes+MPI. We evaluated our new implementation of RevBayes+BEAGLE using multi-threading on CPUs and a powerful NVidia Titan V GPU against our native implementation of RevBayes+MPI. We found good improvements in speedup when multiple cores were used with up to 20-fold speedup when using multiple CPUs and over 90-fold speedup when using multiple GPU cores. The improvement depended on the data type used, DNA or amino acids, and the size of the alignment, but less on the size of the tree. We additionally investigated the cost of rescaling partial likelihoods to avoid numerical underflow and showed that unnecessarily frequent rescaling can increase runtimes 2.5 to 3-fold. Finally, we presented and compared a new approach to store partial likelihoods on branches instead of nodes which can speed up computations but comes at twice the memory requirements.</p> <p>Availability: The software described in the paper is available at https://github.com/revbayes/revbayes with documentation and tutorials found at https://revbayes.github.io.</p>
Evaluation of the Impact of the Educational Revolution in Peru and the Gender Wage Gap, 2017-2021
<p><strong><span>Background:</span></strong><strong><span> </span></strong><span>Women's educational attainment and their generation of value through education has increased the prospects for achieving economic equality between men and women. However, women continue to earn lower wages than men, reflecting growing inequality in several countries. Therefore, the objective of the study is to estimate the impact of education on the gender wage gap in Peru over the period 2017-2021.</span></p> <p><strong><span>Methods:</span></strong><span> Quantitative, explanatory study aimed at identifying the impact of education on the gender wage gap in Peru during the period 2017-2021. The research design is non-experimental and uses a time series that analyses the influence of the latent variable of education on the gender wage gap. This is a continuous variable to estimate the Tobit model.</span></p> <p><strong><span>Results:</span></strong><strong><span> </span></strong><span>The results show that the gender gap in Peru exhibited a decreasing trend between men and women during the period 2017-2020, with an average reduction of 10% until 2020 due to the health crisis. The highest average salary was achieved by men in 2019, reaching S/2289.97 soles, while women reached an average salary of S/1368.85 soles. In the post-pandemic scenario for 2021, the gender gap increased by 3%, with men earning an average salary of S/1999.63 soles and women earning an average salary of S/1281.16 soles. The analysis from 2017-2021 shows that years of education had a positive impact on the gender wage gap in Peru based on the Tobit model estimation.</span></p> <p><strong><span>Conclusions:</span></strong><strong><span> </span></strong><span>During the analysis period of 2017-2021, years of education had a positive impact on the gender wage gap in Peru, with the greatest impact occurring during the health crisis. The probability of women's incomes improving with an increase in years of education was 2.35%, while for men, the highest impact was in 2018, with a probability of income improvement of 2.16% in terms of marginal effect.</span></p>
Fig. 4 in Greenhouse evaluation of neonate and adult applications of Coleomegilla maculata (Coleoptera: Coccinellidae) to control twospotted spider mite infestations
Fig. 4. Spider mite infestation levels in each treatment 20 d afer treatment application. Data represent the non-transformed mean number of mites, at specified developmental stage, per square cm of leaf surface (abaxial) ± SEM (n = 4). Different letters above bars indicate significant difference (P <0.05, Holm-Sidak multiple comparisons).
Fig. 2 in Greenhouse evaluation of neonate and adult applications of Coleomegilla maculata (Coleoptera: Coccinellidae) to control twospotted spider mite infestations
Fig. 2. Temperature fluctuations (only daily high temperatures are charted) during the course of the experiment.
Fig. 3. Representative samples from initial experiment interrupted and lef untended for 17 d in Greenhouse evaluation of neonate and adult applications of Coleomegilla maculata (Coleoptera: Coccinellidae) to control twospotted spider mite infestations
Fig. 3. Representative samples from initial experiment interrupted and lef untended for 17 d. Plants treated with lady beetles recovered from extreme stress; infested and untreated plants could not grow new leaves (no recovery).
Figs. 7–10 in Morphology of the 1st gonapophysis in the genus Neoplea (Hemiptera: Heteroptera: Pleidae), including an evaluation of its taxonomic importance
Figs. 7–10. Outer lateral surface of the right 1st gonapophysis of species of Neoplea. Neoplea gauchita (7), re-drawn from Bachmann (1968); Neoplea harnedi (8); Neoplea lingula (9), re-drawn from Roback & Nieser (1974); Neoplea maculosa (10); op: spur on opposing face of 1st gonapophysis.
Fig. 11–14 in Morphology of the 1st gonapophysis in the genus Neoplea (Hemiptera: Heteroptera: Pleidae), including an evaluation of its taxonomic importance
Fig. 11–14. Outer lateral surface of the right 1st gonapophysis of species of Neoplea. Neoplea notana (11); Neoplea punctifer (12); Neoplea striola (13); Neoplea tenuistyla (14), re-drawn from Roback & Nieser (1974).
Figs. 3–6 in Morphology of the 1st gonapophysis in the genus Neoplea (Hemiptera: Heteroptera: Pleidae), including an evaluation of its taxonomic importance
Figs. 3–6. Outer lateral surface of the right 1st gonapophysis of species of Neoplea. Neoplea absona (3); Neoplea apopkana (4); Neoplea argentina (5); Neoplea borellii (6).
Fig. 1 in Morphology of the 1st gonapophysis in the genus Neoplea (Hemiptera: Heteroptera: Pleidae), including an evaluation of its taxonomic importance
Fig. 1. General external female genital morphology in Neoplea, showing abdominal segments VIII and IX; T8 and T9 are tergal sclerites of abdominal segments VIII and IX, respectively; 1Gx and 2Gx are the 1st and 2nd lef gonocoxae; 1Gpo and 2Gpo are the 1st and 2nd lef gonapophyses; 2Gpl is the gonoplac, which is located on segment IX. Orientation of these structures is skewed to allow for viewing of all structures, but they overlap and tilt when attached to the abdomen.
Fig. 2. General 1 in Morphology of the 1st gonapophysis in the genus Neoplea (Hemiptera: Heteroptera: Pleidae), including an evaluation of its taxonomic importance
Fig. 2. General 1st gonapophysis morphology in Neoplea. Outer lateral surface of the right 1st gonapophysis with apex to the lef and dorsal edge at the top of the figure. All following figures are oriented to match Fig. 2. A1: 1st spur of apical row; P1: 1st spur of primary row; S1: 1st spur of secondary row; T1: 1st spur of tertiary row; L1: 1st spur of lateral row; U: accessory spurs; dd: dorsal depression; dl: dorsal lobe; vr: ventral ridge; vt: ventral tooth.
Fig. 2 in Evaluation of field dispersal and survival capacity of the genetic sexing strain Tapachula-7 of Anastrepha ludens (Diptera: Tephritidae)
Fig. 2. General displacement of Anastrepha ludens SMR strain (solid line) and Tap-7 strain (broken line) in a Cartesian plane.
Fig. 1 in Evaluation of field dispersal and survival capacity of the genetic sexing strain Tapachula-7 of Anastrepha ludens (Diptera: Tephritidae)
Fig. 1. Contours of displacement of the SMR strain (lef) and Tap-7 strain (right) of Anastrepha ludens inside the field plot. The density of the flies at each contour is indicated by the number.
Figure 2 in Molecular evaluation of Conogethes punctiferalis (Guenée, 1854): Species status and intraspecific divergence
Figure 2. Median-joining network of mitochondrial haplotypes of refined Conogethes punctiferalis. Each node represents a unique haplotype identified from 420 mtCOI sequences. Node size is proportional to the frequency of relevant haplotypes, and branch length is proportional to the mutations that occurred between haplotypes. Color depicts the geographic origins of the harboring mtCOI sequences.
Figure 1 in Molecular evaluation of Conogethes punctiferalis (Guenée, 1854): Species status and intraspecific divergence
Figure 1. Species delimitation and phylogenetic relationship of Conogethes mitochondrial haplotypes. The ultrametric phylogenetic tree was inferred using BEAST with a strict molecular clock model and a speciation prior of Yule process. Strongly supported nodes with posteriors ≥ 0.95 and maximum likelihood bootstrapping support values ≥ 70 were indicated by black dots. The bars on the right depict the putative species delimited by different methods. Species names identified following Shashank et al. (2018).
Fig. 3 in Appraisal of sperm dynamics as a crucial trait of radio- sterilized Spodoptera litura (Lepidoptera: Noctuidae) and its F progeny for evaluation of the 'inherited sterility technique' for pest suppression
Fig. 3. Effect of gamma irradiation on (a) the percentage of active apyrene sperm, and (b) the intensity of active sperm (no. of undulations/s) in virgin irradiated parental (P) male Spodoptera litura.
Fig. 2b in Appraisal of sperm dynamics as a crucial trait of radio- sterilized Spodoptera litura (Lepidoptera: Noctuidae) and its F progeny for evaluation of the 'inherited sterility technique' for pest suppression
Fig. 2b. Eupyrene sperm bundles descent from the testes to the reproductive tract (upper vasa deferentia (UVD), seminal vesicles (SV) and the duplex) of irradiated male Spodoptera litura and their F1 progeny during the photophase (white bars)and the scotophase (black bars). Means ± SE followed by the same capital letter within white bars, or within black bars within each treatment regimen of sperm descent in the UVD, SV and duplex are not significantly different at P ≤ 0.05 (ANOVA followed by LSD post-test). Means ± SE followed by a different small letter between white bar and black bar, within each age group within a regimen are significantly different at P ≤ 0.05 (ANOVA followed by LSD posttest).
ScienceDex guides
Understand access before you commit
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.