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Figure 4 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 4. Drawing of the skull of Cymbospondylus nichollsi sp. nov. (FMNH PR2251) in lateral view. See Appendix for explanation of abbreviations. Scale bar = 10 cm.
Figure 3 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 3. Drawing of the skull of Cymbospondylus nichollsi sp. nov. (FMNH PR2251) in dorsal view. See Appendix for explanation of abbreviations. Scale bar = 10 cm.
Figure 2 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 2. Right temporal opening of specimen FMNH PR2251 with the arrow indicating the bite marks on the parietal plateau. See Appendix for explanation of abbreviations.
Figure 7 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 7. Close-up view of the occipital–cervical complex of specimen FMNH PR2251 in posteroventral view. Vertebrae are observed in ventrolateral view. See Appendix for explanation of abbreviations.
Figure 11 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 11. Comparison of the lateral views of the postrostral skull regions of Cymbospondylus. A, Cymbospondylus nichollsi sp. nov., based on the holotype FMNH PR2251. B, C. petrinus, based on UCMP 9950. C, C. buchseri, based on PIMUZ 4351, modified after Sander (1989b). B and C are based on left sides of the skulls and have been inverted.
Figure 9 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 9. Drawings of ribs of specimen FMNH PR2251. A, double-headed first cervical rib. B, anterior dorsal rib. C, middle dorsal rib. Scale bar = 2 cm.
Figure 12 in A new species of Cymbospondylus (Diapsida, Ichthyosauria) from the Middle Triassic of Nevada and a re-evaluation of the skull osteology of the genus
Figure 12. Strict consensus of three most parsimonious trees reflecting the hypothesized phylogenetic relationships of Cymbospondylus nichollsi sp. nov. to a selection of mainly Triassic ichthyosaurs. Based on the data matrix of Nicholls & Manabe (2001). After inclusion of C. nichollsi, 15 taxa and 44 characters were considered in the analysis.
Evaluating the efficacy of drone-based thermal images for measuring wildlife abundance and physiology
<p>Monitoring the population dynamics and behaviors of wildlife is crucial for effective conservation. Although drones can provide a promising alternative to traditional monitoring methods, validation studies must be done to quantify the accuracy of drone-based abundance and distribution estimates in various biological systems. Here, we investigate the use of drones equipped with high-resolution Red-Green-Blue (RGB) and thermal cameras, along with machine learning techniques, for assessments of abundance and physiology in northern elephant seals (<em>Mirounga</em> <em>angustirostris</em>). Aerial images of N=3,415 northern elephant seals were collected at Año Nuevo Reserve during N=24 drone flights, along with ambient air temperatures, wind speed, and time-of-day data. The two-dimensional footprints and surface temperatures of seals were measured from the images. Machine learning algorithms were applied to detect seals in the imagery, and model performance was evaluated. Our findings indicate that seal detection was more accurate using RGB images compared to Thermal images, but that Thermal images could be used to determine that time of day and ambient temperature (but not wind speed or body size) strongly influenced seal external skin temperature. In other words, RGB and Thermal cameras have different strengths and weaknesses that should be carefully considered when designing research studies. Our study highlights the promising integration of drones, thermal imaging, and machine learning for wildlife research, contributing to faster, safer, cheaper, less disruptive, and more accurate wildlife monitoring and conservation efforts.</p>
Dataset for article "Performance and Efficiency Evaluation of Technology-Based Business Incubators: A Systematic Literature Review"
<p>Dataset for article entitled "<strong>Performance and Efficiency Evaluation of Technology-Based Business Incubators: A Systematic Literature Review"</strong></p>
Data for Tekran Model 3425 performance evaluation report for elemental mercury
<p>During the SI-Hg performance evaluation of elemental mercury gas generators on the market three generators were tested, e.g., PSA 10.536 elemental Hg generator, bell-jar and Tekran Model 3425. Key characteristics were determined e.g.; the stabilisation period, short-term drift, precision, i.e., reproducibility and repeatability of the concentration generated, linearity, bias, sensitivity to sample gas pressure, sensitivity to surrounding temperature and sensitivity to electrical voltage. All three generators could be tested according to the calibration protocol developed within the project. The results obtained with the different gas generator clearly shows the importance of a metrological calibration. All three candidate generators show a different bias for the setpoint compared to the calibrated output. </p><p>The data obtained during the performance evaluation of the Tekran Model 3425 is published in this repository. The files of the following experiments can be found here:</p><ul><li>m1<ul><li>Calibration Tekran mercury gas generator m1 20230612</li><li>Calibration_Tekran_m1</li></ul></li><li>m2<ul><li>Calibration Tekran mercury gas generator m2 20230619</li><li>Calibration_Tekran_m2</li></ul></li><li>m3<ul><li>Calibration Tekran mercury gas generator m3 20230626</li><li>Calibration_Tekran_m3</li></ul></li><li>m4<ul><li>Calibration Tekran mercury gas generator m4 20230629</li><li>Calibration_Tekran_m4</li></ul></li><li>short-term drift<ul><li>m2<ul><li>Calibration Tekran mercury gas generator short term drift m2</li><li>Tekran_Short_Term_M2</li></ul></li><li>m3<ul><li>Calibration Tekran mercury gas generator short term drift m3</li><li>Tekran_Short_Term_M3</li></ul></li><li>m4<ul><li>Calibration Tekran mercury gas generator short term drift m4</li><li>Tekran_Short_Term_M4</li></ul></li><li>m5<ul><li>Calibration Tekran mercury gas generator short term drift m5</li><li>Tekran_Short_Term_M5</li></ul></li></ul></li><li>stability<ul><li>Calibration Tekran mercury gas generator 20230609 stability</li></ul></li></ul>
Data for SI-Hg D2 validation report for the calibration of elemental mercury gas generators including information on repeatability, reproducibility and uncertainty evaluation at emission and ambient levels extended to the sub ng/m3 level
<p>In deliverable 2 of the SI-Hg project the first validation results of the SI-Hg calibration protocol are reported. Within the SI-Hg project a protocol for the metrological calibration of elemental mercury gas generators used in the field was developed. For the validation the output of two different mercury gas generators was calibrated according to the protocol. As metrological reference standard the primary mercury gas standard from the Van Swinden Laboratory (VSL) was used. The measurements described in the protocol could be performed during the validation and the data was processed using a script to determine the output of the candidate generator and the uncertainty of the mercury concentration. Based on the validation measurements and data processing several improvements for the calibration protocol were identified and were used to improve the calibration protocol. </p><p>In this repository data obtained during the validation is published. The files of the following comparisons between reference generator and candidate generator can be found in this repository:</p><ul><li>VSL vs VSL<ul><li>m1<ul><li>09022022 calibration mercury gas generator VSL vs VSL m1</li><li>VSL_vs_VSL_m1</li></ul></li><li>m2 <ul><li>05072022 calibration mercury gas generator VSL vs VSL m2</li><li>VSL_vs_VSL_m2</li></ul></li><li>m3<ul><li>07072022 calibration mercury gas generator VSL vs VSL m3</li><li>VSL_vs_VSL_m3</li></ul></li></ul></li><li>VSL vs PSA before modification<ul><li>m1<ul><li>15032022 calibration mercury gas generator VSL vs PSA fixed m1</li><li>single_point_VSL_vs_PSA_fixed_m1_4</li><li>single_point_VSL_vs_PSA_fixed_m1_6</li><li>single_point_VSL_vs_PSA_fixed_m1_8</li><li>single_point_VSL_vs_PSA_fixed_m1_12</li></ul></li><li>m2<ul><li>28032022 calibration mercury gas generator VSL vs PSA fixed m2</li><li>single_point_VSL_vs_PSA_fixed_m2_4</li><li>single_point_VSL_vs_PSA_fixed_m2_6</li><li>single_point_VSL_vs_PSA_fixed_m2_8</li><li>single_point_VSL_vs_PSA_fixed_m2_12</li></ul></li><li>m3 <ul><li>06042022 calibration mercury gas generator VSL vs PSA fixed m3</li><li>single_point_VSL_vs_PSA_fixed_m3_4</li><li>single_point_VSL_vs_PSA_fixed_m3_6</li><li>single_point_VSL_vs_PSA_fixed_m3_8</li><li>single_point_VSL_vs_PSA_fixed_m3_12</li></ul></li><li>m4 <ul><li>12042022 calibration mercury gas generator VSL vs PSA fixed m4</li><li>single_point_VSL_vs_PSA_fixed_m4_4</li><li>single_point_VSL_vs_PSA_fixed_m4_6</li><li>single_point_VSL_vs_PSA_fixed_m4_8</li><li>single_point_VSL_vs_PSA_fixed_m4_12</li></ul></li><li>less tubing <ul><li>14042022 calibration mercury gas generator VSL vs PSA fixed less tubing</li><li>single_point_VSL_vs_PSA_fixed_less_tubing</li></ul></li><li>less tubing and air as complementary gas <ul><li>19042022 calibration mercury gas generator VSL vs PSA fixed less tubing in air</li><li>single_point_VSL_vs_PSA_fixed_less_tubing_air</li></ul></li></ul></li><li>VSL vs PSA after modification<ul><li>m1 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m1 20230324</li><li>PSA_fixed_air_m1_9</li><li>PSA_fixed_air_m1_11</li><li>PSA_fixed_air_m1_14</li></ul></li><li>m2 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m2 20230327</li><li>PSA_fixed_air_m2_9</li><li>PSA_fixed_air_m2_11</li><li>PSA_fixed_air_m2_14</li></ul></li><li>m3 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m3 20230329</li><li>PSA_fixed_air_m3_9</li><li>PSA_fixed_air_m3_11</li><li>PSA_fixed_air_m3_14</li></ul></li><li>m4 air as complementary gas <ul><li>Calibration PSA fixed mercury gas generator air m4 20230907</li><li>PSA_fixed_air_m4_9</li><li>PSA_fixed_air_m4_11</li><li>PSA_fixed_air_m4_14</li></ul></li><li>m5 air as complemantary gas <ul><li>Calibration PSA fixed mercury gas generator air m5 20230911</li><li>PSA_fixed_air_m5_9</li><li>PSA_fixed_air_m5_11</li><li>PSA_fixed_air_m5_14</li></ul></li><li>m1 nitrogen (N2) as complementary gas<ul><li>Calibration PSA fixed mercury gas generator nitrogen m1 20230330</li><li>PSA_fixed_N2_m1_9</li><li>PSA_fixed_N2_m1_11</li><li>PSA_fixed_N2_m1_14</li></ul></li><li>m2 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m2 20230331</li><li>PSA_fixed_N2_m2_9</li><li>PSA_fixed_N2_m2_11</li><li>PSA_fixed_N2_m2_14</li></ul></li><li>m3 N2 as complementary gas <ul><li>Calibration PSA fixed mercury gas generator nitrogen m3 20230405</li><li>PSA_fixed_N2_m3_9</li><li>PSA_fixed_N2_m3_11</li><li>PSA_fixed_N2_m3_14</li></ul></li><li>measurement at TUV<ul><li>PSA_Fixed_at_TUV</li></ul></li></ul></li></ul>
Data for PSA 10.536 Elemental Hg generator performance evaluation report
<p>During the SI-Hg performance evaluation of elemental mercury gas generators on the market three generators were tested, e.g., PSA 10.536 elemental Hg generator, bell-jar and Tekran Model 3425. Key characteristics were determined e.g.; the stabilisation period, short-term drift, precision, i.e., reproducibility and repeatability of the concentration generated, linearity, bias, sensitivity to sample gas pressure, sensitivity to surrounding temperature and sensitivity to electrical voltage. All three generators could be tested according to the calibration protocol developed within the project. The results obtained with the different gas generator clearly shows the importance of a metrological calibration. All three candidate generators show a different bias for the setpoint compared to the calibrated output. </p><p>The data obtained during the performance evaluation of the PSA 10.536 elemental Hg generator is published in this repository. The files of the following experiments can be found here:</p><ul><li>range1 m1<ul><li>Calibration_PSA_range1_m1_20221130</li><li>multi_point_calibration_PSA_range1_m1</li></ul></li><li>range1 m2<ul><li>Calibration_PSA_range1_m2_20221209</li><li>multi_point_calibration_PSA_range1_m2</li></ul></li><li>range1 m3<ul><li>Calibration_PSA_range1_m3_20221214</li><li>multi_point_calibration_PSA_range1_m3</li></ul></li><li>range1 m4<ul><li>Calibration_PSA_range1_m4_20230915</li><li>multi_point_calibration_PSA_range1_m4</li></ul></li><li>range1 m5<ul><li>Calibration_PSA_range1_m5_20230919</li><li>multi_point_calibration_PSA_range1_m5</li></ul></li><li>range2 m1<ul><li>Calibration_PSA_range2 m1 20221006</li><li>multi_point_calibration_PSA_range2_m1</li></ul></li><li>range2 m2<ul><li>Calibration_PSA_range2 m2 20221011</li><li>multi_point_calibration_PSA_range2_m2</li></ul></li><li>range2 m3<ul><li>Calibration_PSA_range2 m3 20221012</li><li>multi_point_calibration_PSA_range2_m3</li></ul></li><li>short-term drift<ul><li>m1<ul><li>Calibration mercury gas generator range1 short term drift 20221012 deel 1</li><li>PSA_short_term_drift_M1</li></ul></li><li>m2<ul><li>Calibration mercury gas generator range1 short term drift 20221012 deel 2</li><li>PSA_short_term_drift_M2</li></ul></li><li>m3<ul><li>Calibration mercury gas generator range1 short term drift 20221012 deel 3</li><li>PSA_short_term_drift_M3</li></ul></li><li>m4<ul><li>Calibration mercury gas generator range1 short term drift 20221012 deel 4</li><li>PSA_short_term_drift_M4</li></ul></li></ul></li><li>stability<ul><li>Calibration mercury gas generator range2 stability 20220811</li><li>Calibration mercury gas generator stability 20221018</li></ul></li></ul>
Figure 1. A in Evaluate the efficiency of releasing two predatory species at their optimal temperature for controlling Tetranychus urticae (Acari: Tetranychidae) in a croton greenhouse
Figure 1. A timeline representing the release of predatory species P. persimilis and S. punctillum to control the twospotted mite T. urticae in a croton greenhouse.
Figure 3 in Evaluate the efficiency of releasing two predatory species at their optimal temperature for controlling Tetranychus urticae (Acari: Tetranychidae) in a croton greenhouse
Figure 3. The comparison between the population of T. urticae in predators' greenhouse and control greenhouse.
Figure 7 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 7. Simplified phylogeny of Eptesicus, Cnephaeus, Histiotus, and Neoeptesicus, modified from Yi and Latch (2022). Authorship of Eptesicus image: Dr. Burton Lim.
Figure 4 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 4. Plot of multivariate individual scores of New World Eptesicus (red), Old World Eptesicus (blue), and Histiotus (black) in the first two canonical variates: (A) canonical variates considering the effect of size; (B) "size-free" canonical variate using Mosimann shape variables. Analyses were performed using 16 cranial measurements.
Figure 3 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 3. (A) Plot of multivariate individual scores of New World Eptesicus (Red), Old World Eptesicus (Blue), and Histiotus (Black) in the first two principal components. Analysis was performed using 16 cranial measurements. (B) Vector correlations of craniometric characters with the first two principal components eigenvectors. See Table 1 for abbreviations.
Figure 5 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 5. Vector correlations of craniometric characters with the first two eigenvectors of the canonical variates: (A) canonical variate considering the effect of size; (B) "size-free" canonical variate using Mosimann shape variables. See Table 1 for abbreviations.
Figure 2 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 2. Lateral, dorsal, and ventral views of the skull of representatives of the type species of Histiotus (H. velatus [MACN 16808]; A, B, C), the type species of Eptesicus (E. fuscus [MACN 13407]; D, E, F), the first described Old World species of Eptesicus (E. serotinus [MACN 35.178]; G, H, I), and a representative of small Neotropical Eptesicus (E. andinus [AMNH 33807, holotype]; J, K, L). Arrows 1 and 4 indicate the auditory bullae; arrow 2 indicates the postorbital process of the jugal bone; arrow 3 indicates the frontal slope. Scale bars: 5 mm.
Figure 1 in Taxonomic re-evaluation of New World Eptesicus and Histiotus (Chiroptera: Vespertilionidae), with the description of a new genus
Figure 1. Representatives of New World Eptesicus: (A) Eptesicus taddeii and (B) Eptesicus fuscus; Histiotus: (C) Histiotus velatus; and Old World Eptesicus: (D) Eptesicus serotinus. Authorship of images: (B) Dr. Burton Lim and (D) Adrià López-Baucells, http://www.batmonitoring.org.
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.