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FIGURE 15 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 15. Spectrogram (up) and oscillogram (bottom) of the advertisement calls of Scinax imbegue; January 07, 2019, 22:33h; Air temperature = 25.2°C, Air humidity = 89%; Water temperature = 31°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created with in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 13 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 13. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Scinax crospedospilus; October 18, 2018, 21:25h; Air temperature = 17.1°C, Air humidity = 100%; Water temperature = 24°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 12 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 12. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Dendropsophus nanus; December 17, 2018, 21:00h; Air temperature = 24.3°C, Air humidity = 75.8%; Water temperature = 30°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 9 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 9. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Dendropsophus berthalutzae; February 12, 2019, 20:24h; Air temperature = 23°C, Air humidity = 100%; Water temperature = 24.5°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 8 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 8. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Boana semilineata treefrog; February 14, 2019, 21:09h; Air temperature = 20.9°C, Air humidity = 100%; Water temperature = 23°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 4 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 4. Spectrogram (up) and oscillogram (bottom) of the advertisement ("A") and territorial ("B") calls of Boana bandeirantes treefrog; September 29, 2018, 18:59h; Air temperature = 17.4°C, Air humidity = 86%; Water temperature = 20°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 3 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 3. Spectrogram (up) and oscillogram (bottom) of advertisement calls of Boana albopunctata treefrog; December 27, 2018, 20:42h; Air temperature = 17.1°C, Air humidity = 96.2%; Water temperature = 22°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 7 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 7. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Boana prasina treefrog; March 08, 2019, 20:31h; Air temperature = 26°C, Air humidity = 75%; Water temperature = 23°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 6 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 6. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Boana pardalis treefrog; October 19, 2018, 18:33h; Air temperature = 16.4°C, Air humidity = 100%; Water temperature = 22°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 11 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 11. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Dendropsophus minutus; January 10, 2019, 22:17h; Air temperature = 20.5°C, Air humidity = 90.2%; Water temperature = 27°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 5 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 5. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Boana faber treefrog; January 09, 2019, 21:30h; Air temperature = 19.3°C, Air humidity = 92.7%; Water temperature = 27°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 2 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 2. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Boana albomarginata treefrog; February 12, 2019, 22:15h; Air temperature = 19.1°C, Air humidity = 100%; Water temperature = 22.5°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Maria Carolina R. Manzano.
FIGURE 10 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 10. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Dendropsophus elegans; January 15, 2019, 21:58h; Air temperature = 24.1°C, Air humidity = 94.5%; Water temperature = 29°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Michel de Aguiar Passos.
FIGURE 1 in Advertisement calls of 18 anuran species in the megadiverse Atlantic Forest in southeastern Brazil: review and update
FIGURE 1. Spectrogram (up) and oscillogram (bottom) of the advertisement call of Rhinella ornata; February 04, 2019, 21:02h; Air temperature = 18.3°C, Air humidity = 92.7%; Water temperature = 24°C. Spectrogram parameters: window size = 1024, overlap = 90%, window type = "Hann". Figure created in R package seewave (Sueur et al. 2008). Photo by Natália L. A. de Souza.
Variant Call File (VCF) for Genome-wide polymorphism and genic selection in feral and domesticated lineages of Cannabis sativa
<p>A comprehensive understanding of the degree to which genomic variation is maintained by selection versus drift and gene flow is lacking in many important species such as <em>Cannabis</em> <em>sativa </em>(<em>C. sativa</em>), one of the oldest known crops to be cultivated by humans worldwide. We generated whole genome resequencing data across diverse samples of feralized (escaped domesticated lineages) and domesticated lineages of <em>C. sativa</em>. We performed analyses to examine population structure, and genome wide scans for FST, balancing selection, and positive selection. Our analyses identified evidence for sub-population structure and further support the Asian origin hypothesis of this species. Feral plants sourced from the U.S. exhibited broad regions on chromosomes 4 and 10 with high <span>𝐹̅</span>ST which may indicate chromosomal inversions maintained at high frequency in this sub-population. Both our balancing and positive selection analyses identified loci that may reflect differential selection for traits favored by natural selection and artificial selection in feral versus domesticated sub-populations. In the U.S. feral sub-population, we found six loci related to stress response under balancing selection and one gene involved in disease resistance under positive selection, suggesting local adaptation to new climates and biotic interactions. In the marijuana sub-population, we identified the gene <em>SMALLER TRICHOMES</em> <em>WITH VARIABLE BRANCHES 2 </em>to be under positive selection which suggests artificial selection for increased tetrahydrocannabinol yield. Overall the data generated, and results obtained from our study help to form a better understanding of the evolutionary history in <em>C. sativa</em>.</p>
Policy compliance detection with system call traces
<p>This repository includes data and results in chapter 4 - Policy compliance detection with syscall profiling of Ph.D. thesis "A policy compliance detection architecture for data exchange infrastructures"</p>
Appendix for "Is JavaScript Call Graph Extraction Solved Yet? A Comparative Study of Static and Dynamic Tools"
<p><strong>Abstract</strong></p> <p>The popularity and wide adoption of JavaScript both at the client and server-side makes its code analysis more essential than ever before. Most of the algorithms for vulnerability analysis, coding issue detection, or type inference rely on the call graph representation of the underlying program. Luckily, there are quite a few tools to get this job done already. However, their performance in vitro and especially in vivo has not yet been extensively compared and evaluated.</p> <p>In this paper, we systematically compare five static and two dynamic approaches for building JavaScript call graphs on 26 WebKit SunSpider benchmark programs and two static and two dynamic methods on 12 real-world Node.js modules. The tools under examination using static techniques were <em>npm call graph</em>, <em>IBM WALA</em>, <em>Google Closure Compiler</em>, <em>Approximate Call Graph</em>, and <em>Type Analyzer for JavaScript</em>. We performed dynamic analyzes relying on the <em>nodejs-cg</em> tool (a customized Node.js runtime) and the <em>NodeProf </em>instrumentation and profiling framework.</p> <p>We provide a quantitative evaluation of the results, and a result quality analysis based on 941 manually validated call edges. On the SunSpider programs, which do not take any inputs, so dynamic extraction could be complete, all the static tools also performed well. For example, TAJS found 93% of all edges while having a 97% precision compared to the precise dynamic call graph. When it comes to real-world Node.js modules, our evaluation shows that static tools struggle with parsing the code and fail to detect a significant amount of call edges that dynamic approaches can capture. Nonetheless, a significant number of edges not detected by dynamic approaches are also reported. Among these, however, there are also edges that are real, but for some reason the unit tests did not execute the branches in which these calls were included.</p>
Introduction to our Funding Call - Dr Samantha Kanza (University of Reading, University of Southampton).
<p>This video is the second talk from our Landscape Report Funding Call Town Meeting that took place on the 03/02/2022.</p> <p>Introduction to our Funding Call - Dr Samantha Kanza (University of Reading, University of Southampton).</p> <p>Bio: Dr Samantha Kanza is an Enterprise Fellow at the University of Southampton. She completed her MEng in Computer Science at the University of Southampton and then worked for BAE Systems Applied Intelligence for a year before returning to do an iPhD in Web Science (in Computer Science and Chemistry), which focused on Semantic Tagging of Scientific Documents and Electronic Lab Notebooks. She was awarded her PhD in April 2018. Samantha works in the interdisciplinary research area of applying computer science techniques to the scientific domain, specifically through the use of semantic web technologies and artificial intelligence. Her research includes looking at electronic lab notebooks and smart laboratories, to improve the digitization and knowledge management of the scientific record using semantic web technologies; and using IoT devices in the laboratory. She has also worked on a number of interdisciplinary Semantic Web projects in different domains, including agriculture, chemistry and the social sciences.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/03-02-2021-future-blood-testing-network-landscape-report-funding-town-meeting/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/rhvlEi6P8Nk</p>
Supplementary material 1 from: Symes LB, Madhusudhana S, Martinson SJ, Kernan CE, Hodge KB, Salisbury DP, Klinck H, ter Hofstede H (2022) Estimation of katydid calling activity from soundscape recordings. Journal of Orthoptera Research 31(2): 173-180. https://doi.org/10.3897/jor.31.73373
Supplementary material 1 from: Symes LB, Madhusudhana S, Martinson SJ, Kernan CE, Hodge KB, Salisbury DP, Klinck H, ter Hofstede H (2022) Estimation of katydid calling activity from soundscape recordings. Journal of Orthoptera Research 31(2): 173-180. https://doi.org/10.3897/jor.31.73373
FIGURES 29–39. Aphrodes bicincta, male calling signals. 29, 34 in On the taxonomy and distribution of Aphrodes bicincta (Schrank, 1776) species group (Homoptera: Auchenorrhyncha: Cicadellidae: Aphrodinae) in Eastern Palaearctic
FIGURES 29–39. Aphrodes bicincta, male calling signals. 29, 34―male from Saratov Area, Dyakovka, 30, 35―male from Kazakhstan, South-eastern part of Syrdarya Karatau Mtn. Range, 31, 36―male from Kazakhstan, environs of Almaty, 32–33, 37–39―males from Kyrgyzstan, Lower Naryn River Valley, Kurpsay Gorge. 29–38―oscillograms, 39―oscillogram and sonogram at the same scale. Faster oscillograms of the parts of signals indicated as "34–38" are given under the same numbers.
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.