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FIGURE 7 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 7 Enlarged section of the Maximum-likelihood phylogenetic reconstruction of fig. 6, with all COI sequences shown for the sericatus group, i.e., P. thebeatles, P. medius, and P. sericatus. Colours match those in fig. 5.
FIGURE 4 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 4 Dorsal (perpendicular to the surface of the aedeagus between the orifice and the apex) and lateral views of the apices of the aedeagi of members of the Ptomaphagus sericatus complex. a: P. medius from Oegstgeest, the Netherlands, dorsal (a) and lateral (b) views. b: P. sericatus from Les Arnoulats, France, dorsal (c) and lateral (b) views. c: P. thebeatles from Amsterdam, the Netherlands, dorsal (e) and lateral (f) views. (Images derived from topotypical material, not from the holotype itself.).
FIGURE 2 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 2 Neotype of P. sericatus from Kiev, Ukraine: a, habitus; b, aedeagus, dorsal view (angle of view somewhat more rostral than in fig. 4); c, aedeagus, lateral view; d, genital segment; e, labels.
FIGURE 3 Antennomeres 1-7 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 3 Antennomeres 1-7 for members of the Ptomaphagus sericatus complex. a: P. sericatus, female (a) and male (b) from Les Arnoulats, France. b: P. thebeatles, female (c) from Middelburg, the Netherlands, and male (d) from Schiedam, the Netherlands. After Schilthuizen, 1989. c: P. medius, female (e) from Nieuw & St. Joostland, the Netherlands, and male (f) from Oostvoorne, the Netherlands. After Schilthuizen, 1989.
FIGURE 5 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 5 Distribution map of the specimens studied for this paper (the extralimital specimens of P. medius in Canada have not been included). The white arrows point at records that we interpret as recent range expansions.
FIGURE 1 in Coexistence of two newt species in a transition zone of range overlap
FIGURE 1 Land use map of the study area in the western part of the department Pas de Calais in the northwest of France (see insert), after Curado et al. (2011) and Arntzen et al. (2017). The small-bodied newt species Lissotriton helveticus and L. vulgaris are frequently syntopic (for data see table 1), but have different strongholds in and outside the 'Dunes de la Slack' and the bomb crater areas, respectively. The partial spatial separation is illustrated by dotted contour lines where L. vulgaris is at 60% (red dots), 50% (purple dots) or 40% (blue dots) of the Lissotriton total. Note the position of the study pond at the species transition.
FIGURE 6 in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)
FIGURE 6 Maximum-likelihood phylogenetic reconstruction, based on COI sequences, of P. thebeatles, P. medius, P. sericatus, and other members of the subgenus Ptomaphagus s. str., rooted with P. (Adelops) hatchi. Multiple sequences per species have been collapsed. Support values are given only for branches with>80% bootstrap percentage.
FIGURE 2 in Coexistence of two newt species in a transition zone of range overlap
FIGURE 2 Dynamics of the adult newt breeding populations in the study pond, with percentage values over the 1975–2021 period for Ichthyosaura alpestris (black), Lissotroton helveticus (blue) and L. vulgaris (red), with open dots for samples and solid dots for population size estimates (see also tables 2 and 3). Years without observations are marked by open rectangles. The asterisk indicates a hypothetical frequency, on the assumption that the L. helveticus cohort that in March 1986 fell prone to a late freezing event (details see text) would have made it to the breeding population.
Fig. 2 in Distributional range of the South African maritime spider-egg parasitoid wasp, Echthrodesis lamorali (Hymenoptera: Platygastridae: Scelioninae)
Fig. 2. Distribution of Desis formidabilis, Amaurobioides africanus, Heliophanus villosus and Echthrodesis lamorali along the transect spanning Jacobsbaai to Kidds Beach, surveyed during this study in March 2012.
Fig. 3 in Distributional range of the South African maritime spider-egg parasitoid wasp, Echthrodesis lamorali (Hymenoptera: Platygastridae: Scelioninae)
Fig. 3. Distribution of Palpimanus capensis, Desis formidabilis, Amaurobioides africanus, Heliophanus villosus and Echthrodesis lamorali along the coastline surveyed during this study in November 2012 (a – Cape Peninsula; b – Entire survey area).
Fig. 4 in Distributional range of the South African maritime spider-egg parasitoid wasp, Echthrodesis lamorali (Hymenoptera: Platygastridae: Scelioninae)
Fig. 4. Locality in Summerstrand (33°58'47.892"S 25°39'31.0674"E) during (A) March 2012 and (B) November 2012, showing marked visual differences, with a great reduction in invertebrate covering of the intertidal rocks.
Fig. 5 in Distributional range of the South African maritime spider-egg parasitoid wasp, Echthrodesis lamorali (Hymenoptera: Platygastridae: Scelioninae)
Fig. 5. Main biogeographiƇal zones bordering the 6outh AfriƇan Ƈoast ƖBraƇkets: Regions in whiƇh the border between zones Ƈould fall; 6tippled arrows: Current direƇtion and name; Grey Textboxes: Zone name] (After Teske et al. 2011).
Data and R scripts associated with Clark, Moles, Fazlioglu, Brandenburger & Hartley, "Rapid loss of phenotypic plasticity in the introduced range of the beach daisy, Arctotheca populifolia."
<p>Data to accompany article accepted for publication in Journal of Ecology.</p> <p><strong>"Rapid loss of phenotypic plasticity in the introduced range of the beach daisy, <em>Arctotheca populifolia"</em></strong></p> <p>By Charlie D. Clark, Angela T. Moles, Fatih Fazlioglu, Claire R. Brandenburger, & Stephen Hartley</p> <p>1 zip file that contains the following:</p> <p> 2 datasets (xlsx format)</p> <p> 9 R scripts to run the analyses and produce figures</p>
figure 1 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 1 The area surveyed for collection of otter samples (40° 40' N, 39° 37' N). Red spots indicate the location of the collected samples. The blue lines highlight the main rivers (order 1) and their tributaries (order 2, 3 and 4 according to waterway hierarchy). The continuous red lines represent regional boundaries. In the inset, the current otter distribution (inferred from Balestrieri et al., 2016, modified) is reported in orange and the study area is defined by the black bold square.
figure 4 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 4 Principal Component Analysis (pca) performed on microsatellite genotypes (dots). Circles show the well-defined spatial groups. A) pca according to the belonging of genotypes to the six river basins: the Cilento basin (green dots); the Agri basin (pink dots); the Sinni basin (blue dots); the Lao basin (red dots); the Basento basin (orange dots); the Abatemarco basin (violet dots); black dots indicate the samples outside of the main river basins. Dashed line indicates geographically contiguous but genetically different genotypes. B) pca according to clusters inferred by STRUCTURE: genotypes assigned unambiguously to K2 (green dots), to K3 (yellow dots), to K5 (violet dots). Grey dots represent samples with mixed genotypes assignable to K1 and K4.
figure 3 in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 3 Genetic structure and distribution of the Italian otter genotypes in the study area. A) Estimated population structure based on the analysis of 11 microsatellite loci according to STRUCTURE (K = 5). Each bar represents a sample analysed. B) Geographic visualisation of genotypes in the study area performed using QGIS 3.4.1 software with base layers acquired from http://www.pnc.miniambiente. it/. Each circle represents a sample analysed. The colours indicate the percentage of assignment of an individual to each cluster: in blue, K1; in green, K2; in orange, K3; in red, K4; in violet, K5. The bold blue lines highlight the main rivers, while the tiny blue lines show all other waterways.
figure 6 Mantel test for A in Spatial genetic structure in the Eurasian otter (Lutra lutra) meta-population from its core range in Italy
figure 6 Mantel test for A) the correlation between geographic distance (GGDsq) and genetic distance (LinGD) (Rxy = 0.264, P = 0.0001) and for B) the correlation between resistance distance (a measure of ecological distance) (ECO500) and LinGD (Rxy = 0.217, P = 0.0001).
WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32
<p><strong>WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32</strong></p> <p>This repository contains the WiFi CSI human presence detection and activity recognition datasets proposed in [1].</p> <p><strong>Datasets</strong></p> <ul> <li><strong>DP_LOS</strong> - Line-of-sight (LOS) presence detection dataset, comprised of 392 CSI amplitude spectrograms.</li> <li><strong>DP_NLOS </strong>- Non-line-of-sight (NLOS) presence detection dataset, comprised of 384 CSI amplitude spectrograms.</li> <li><strong>DA_LOS</strong> - LOS activity recognition dataset, comprised of 392 CSI amplitude spectrograms.</li> <li><strong>DA_NLOS</strong> - NLOS activity recognition dataset, comprised of 384 CSI amplitude spectrograms.</li> </ul> <p>Table 1: Characteristics of presence detection and activity recognition datasets. </p> <table> <tbody> <tr> <td><strong>Dataset</strong></td> <td><strong>Scenario</strong></td> <td><strong>#Rooms</strong></td> <td><strong>#Persons</strong></td> <td><strong>#Classes</strong></td> <td><strong>Packet Sending Rate</strong></td> <td><strong>Interval </strong></td> <td><strong>#Spectrograms</strong></td> </tr> <tr> <td>DP_LOS</td> <td>LOS</td> <td>1</td> <td>1</td> <td>6</td> <td>100Hz</td> <td>4s (400 packets)</td> <td>392</td> </tr> <tr> <td>DP_NLOS</td> <td>NLOS</td> <td>5</td> <td>1</td> <td>6</td> <td>100Hz</td> <td>4s (400 packets)</td> <td>384</td> </tr> <tr> <td>DA_LOS</td> <td>LOS</td> <td>1</td> <td>1</td> <td>3</td> <td>100Hz</td> <td>4s (400 packets)</td> <td>392</td> </tr> <tr> <td>DA_NLOS</td> <td>NLOS</td> <td>5</td> <td>1</td> <td>3</td> <td>100Hz</td> <td>4s (400 packets)</td> <td>384</td> </tr> </tbody> </table> <p> </p> <p><strong>Data Format</strong></p> <p>Each dataset employs an 8:1:1 training-validation-test split, defined in the provided label files <em>trainLabels.csv</em>, <em>validationLabels.csv</em>, and <em>testLabels.csv</em>. Label files use the sample format [<em>i c</em>], with <em>i</em> corresponding to the spectrogram index (i.png) and <em>c </em>corresponding to the class. For presence detection datasets (DP_LOS <em>, </em>DP_NLOS), c in {0 = "no presence", 1 = "presence in room 1", ..., 5 = "presence in room 5"}. For activity recognition datasets (DA_LOS <em>, </em>DA_NLOS), c in {0="no activity", 1="walking", and 2="walking + arm-waving"}. Furthermore, the mean and standard deviation of a given dataset are provided in <em>meanStd.csv</em>.</p> <p><strong>Download and Use</strong><br>This data may be used for non-commercial research purposes only. If you publish material based on this data, we request that you include a reference to our paper [1].</p> <p>[1] Strohmayer, Julian, and Martin Kampel. "WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32" <em>International Conference on Computer Vision Systems</em>. Cham: Springer Nature Switzerland, 2023. </p> <p>BibTeX citation:</p> <pre>@inproceedings{strohmayer2023wifi, title={WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32}, author={Strohmayer, Julian and Kampel, Martin}, booktitle={International Conference on Computer Vision Systems}, pages={41--50}, year={2023}, organization={Springer} }</pre>
FIGURE 1 in Range sizes of groundwater amphipods (Crustacea) are not smaller than range sizes of surface amphipods: a case study from Iran
FIGURE 1 Distribution map of analyzed gammarid and niphargid species from Iran. Red circles show gammarid distribution records. Black triangles show previous niphargid distributions. Blue triangles show new distribution of Niphargus populations in this study.
FIGURE 4 in Range sizes of groundwater amphipods (Crustacea) are not smaller than range sizes of surface amphipods: a case study from Iran
FIGURE 4 Violin plots, representing maximum linear extent for Gammarus and Niphargus species delimited using ABGD (A) and bPTP (B). The white dot in the middle indicates the median value in the range size, the thick black bar in the center represents the interquartile range and the thin black line shows 95% of all data. The distributions of surface species are not larger than the distributions of subterranean species (Mann-Whitney U test, p = 0.794 (A), p = 0.837 (B)). MOTUs found on a single localities are excluded.
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.