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1,048 results for “unveil”
Fig. 19 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 19. Photographs of living specimens. a. Phalangodus anacosmetus Gervais, 1842, ♀. b. Phalangodus briareos sp. nov., ♂. Courtesy of S. Galvis (a) and J. Uribe (b).
Fig. 17 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 17. Penis glans and stylus, lateral view. a. Prostygnus sp., Cranaidae: Prostygninae (MZUSP 57274). b. Flirtea quinquilineata (Simon, 1879), Cosmetidae: Cosmetinae (ICN-AO 465).
Fig. 16 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 16. Stylar caps in some cranaids species. — a-e. Cranainae. a. Phalangodus anacosmetus Gervais, 1842 (ICN-AO 1000). b. Phareicranaus giganteus Mello-Leitão, 1940 (MNRJ 19263). c. Ventrifurca caffeinica Villarreal, Kury & Pinto-da-Rocha, 2015 (MNRJ 7038). d. Phareicranaus albilineatus author+year (MNRJ 7916). e. Phareicranaus duranti (González-Sponga, 1989) (MNRJ 7818). — f. Heterocranainae. Heterocranaus sp. (MNRJ 7634). — g. Stygnicranainae. Agathocranaus sp. (MNRJ 8437). a, c, f. Lateral view. b, g. Ventral view. d–e. Oblique view. Arrows indicate stylar caps.
Fig. 14 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 14. Phalangodus kuryi sp. nov. a–d. Holotype, ♂ (ICN-AO-1436). e–f. Paratype, ♀ (ICN- AO-1436.1). g. Paratype, ♂ (ICN-AO-1436.1). a. Habitus, dorsal view. b. Dorsal scutum, lateral view. c. Pedipalpal femur, ectal view. d. Right leg IV: femur, patela and tibia, dorsal view. e. Dorsal scutum, lateral view. f. Pedipalpal femur, ectal view. g. Pedipalpal femur, ectal view. Scale bars = 1 mm.
Fig. 15 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 15. Phalangodus kuryi sp. nov., holotype, ♂ (ICN-AO-1436). Penis, distal portion. a. Dorsodistal view. b. Ventral view. c. Detail of MS, lateral view. d. Stylar caps, ventral view. e. Lateral view. Abbreviations: MS = macrosetae.
Fig. 12 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 12. Phalangodus gyes sp. nov., paratype, ♂ (MNRJ 17907). Distal portion of the penis. a. Dorsal view. b. Ventral view. c. Lateral view. d. Stylar caps, lateral view.
Fig. 11 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 11. Phalangodus gyes sp. nov. a–b, d–e. Holotype, ♂ (MNRJ 8655). c. Paratype, ♀ (MNRJ 17907). a. Habitus, dorsal view. b. Left pedipalp femur, ectal view. c. Left pedipalp, femur, ectal view. d–e. Right leg IV. d. Patella and tibia, dorsal view. e. Femur, dorsal view. Scale bars = 1 mm.
Fig. 9 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 9. Phalangodus cottus sp. nov. a–b, d–h. Holotype, ♂ (MNRJ 8654). c. Paratype, ♀ (MNRJ 17942). a. Habitus, dorsal view. b. Left pedipalp trochanter and femur, ectal view. c. left pedipalpal femur, mesal view. d–e. Right femur II, proximal portion. d. Retrolateral view. e. Ventral view. f–h. Right leg IV. f. Femur, patella and tibia, prolateral view. g. Patella and tibia, dorsal view. h. Femur, dorsal view. Scale bars: a = 5 mm; b–h = 1 mm.
Fig. 8. — a–b in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 8. — a–b. Phalangodus cottus sp. nov., holotpye, ♂ (MNRJ 8654). a. Habitus, dorsal view. b. Habitus, lateral view. —c–d. Phalangodus gyes sp. nov., holotype, ♂ (MNRJ 8655). c. Habitus, dorsal view. d. Habitus, lateral view. Scale bars = 5 mm.
Fig. 6 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 6. Phalangodus briareos sp. nov., holotype, ♂ (MNRJ 2382), penis distal portion. a. Ventral view. b. Lateral view. c. Dorsal view. d. Stylar caps, dorsal view. e. Stylus, lateral view.
Fig. 5 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 5. Phalangodus briareos sp. nov., holotype, ♂ (MNRJ 2382). a. Habitus, dorsal view. b. Left pedipalpal femur, ectal view. c. Right femur IV, dorsal view. d. Right patella and tibia IV, dorsal view. e–f. Right femur II, proximal portion. e. Retrolateral view. f. Ventral view. Scale bars = 1 mm.
Fig. 10 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 10. Phalangodus cottus sp. nov., paratype, ♂ (MNRJ 17942), penis distal portion. a. Lateral view. b. Dorsal view. c. Ventral view. d. Stylar caps, ventrodistal view. e. Distal portion of the ventral plate and stylus, dorsolateral view.
Fig. 4 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 4. Phalangodus briareos sp. nov., ♂, holotype (MNRJ 2382). a. Habitus, dorsal view. b. Habitus, ventral view. c. Habitus, lateral view. Scale bars = 5 mm.
Fig. 3. Phalangodus anacosmetus Gervais, 1842 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 3. Phalangodus anacosmetus Gervais, 1842 (ICN-AO-1000), penis distal portion. a. Dorsal view. b. Lateral view. c. Ventral view. d. Detail of MS C, MS E and microsetae, lateral view. e. Stylar caps, ventrodistal view. Abbreviations: see Material and methods.
Fig. 2. Phalangodus anacosmetus Gervais, 1842 in Unveiling the diversity of Phalangodus Gervais, 1842 (Opiliones: Cranaidae): descriptions of four new species from Colombia
Fig. 2. Phalangodus anacosmetus Gervais, 1842 (syntypes of Allocranaus giganteus Mello-Leitão, 1940, MNRJ 00126). a–b. ♂, juvenile. a. Habitus, dorsal view. b. Habitus, lateral view. c–d. ♀. c. Habitus, dorsal view. d. Habitus, lateral view. Scale bars = 5 mm. Abbreviations: see Material and methods.
Unveiling the genetic networks: Exploring the dynamic interaction of photosynthetic phenotypes in woody plants across varied light gradients
<p><em>Background:</em></p> <p>Understanding the mechanisms by which genes control and regulate complex quantitative traits during periods of fluctuating resources remains a challenging and uncertain task in photosynthesis studies. Most studies have focused on the structure of photosynthesis, the photosynthetic response under stress, or the genetic mechanisms involved in photosynthetic effects and neglected the interactive genetic mechanism that governs various traits through significant quantitative trait loci (QTLs). Results In this study, we have developed a differential dynamic system that enables the identification of QTLs based on the photosynthetic phenotypic and genotypic data under varying levels of light intensity gradients. The framework not only allows for the assessment of the direct effects of QTLs on phenotypes but also captures how they influence interactions among phenotypes as light intensities change. We have analyzed the genetic effects and genetic variance, visualized the genetic network associated with photosynthesis interactions, and validated the effectiveness and stability of the DDS framework. Pivotal QTLs were identified individually to uncover the process and pattern of interaction. Through functional annotation, we made an intriguing discovery that seemingly unimportant QTLs can still have significant genetic effects on phenotypic changes through their regulation with other QTLs. Conclusions This finding emphasizes the significance of considering the interactive genetic architecture when seeking to understand the genetic interaction mechanism of photosynthesis in natural populations of woody plants. Moreover, our research provides a novel framework that can be extended to explore the interactive genetic architecture among organisms, contributing to a deeper understanding of stress resistance mechanisms in woody plants.</p>
Unveiling Hurdles in Software Engineering Education: The Role of Learning Management Systems
<p>Learning management systems (LMSs) are established tools in higher education, especially in the field of software engineering (SE). The onset of the COVID-19 pandemic further amplified the utilization of these systems, which necessitated their integration into educational curricula for both lecturers and students. However, adopting LMSs within SE education has presented distinctive challenges impeding their seamless incorporation into the courses. This paper aims to scrutinize the challenges and requirements encountered by professors, lecturers, and students in the domain of SE education when using LMSs. We conducted an empirical study that included (i) a survey with 47 professors/lecturers and 133 students, (ii) an analysis of the ensuing data, and (iii) 18 additional interviews conducted with professors and lecturers to delve into nuanced variations in viewpoints. The findings derived from our study reveal that the challenges and requirements pertaining to LMSs are rather specific depending on the scope and size of the respective courses. Nevertheless, many participants have a consensus on numerous challenges and requirements for improving certain features of LMSs in order to improve their usage in SE education. The findings are valuable for advancing research and development in the field of LMSs and provide guidance for lecturers in SE education.</p>
Unveiling the impacts of land use on the phylogeography of zoonotic New World Hantaviruses
<p>Billions of genomic sequences are stored in public repositories (NCBI) as well as records of species occurrence (GBIF). By implementing analytical tools from different scientific disciplines, data mining on these databases can be a source of information to aid in the global surveillance of zoonotic pathogens that circulate among wildlife. We illustrate this by investigating the hantavirus-rodent system in the Americas, i.e. New World Hantaviruses (NWH). First we draw the circulation of pathogenic NWH among rodents; by inferring the phylogenetic links among 278 genomic samples of the S segment (N protein) of NWH found in 55 species of Cricetidae rodents. Second, machine learning was used to assess the impact of land use on the probability of presence of the rodent species linked with reservoirs of pathogenic hantaviruses. Our results show that hosts are widely present across the Americas. Some hosts are present in the primary forest and agricultural land, but not in the secondary forest; whereas other hosts are present in secondary forest and agricultural land. The diversity of host species allows Hantavirus to circulate on a wide spectrum of habitats, in particular rural rather than urban. We highlight that Public repositories of genomic data and species occurrence are very useful resources for monitoring potential enzootic transmission and spillover of zoonotic viruses in relation with the changes that humans produce in the Biosphere.</p>
Data and code from: SIDERITE: Unveiling Hidden Siderophore Diversity in the Chemical Space Through Digital Exploration
<h1>TMAP of COCONUT database</h1> <p>The script and data used in SIDERITE paper to generate TMAP picture (Figure S3 in supplementart material).</p> <p>Requirement: tmap</p> <p>You can install tmap by conda.</p> <blockquote> <p>conda create -n tmap python=3.7</p> <p>conda activate tmap</p> <p>conda install -c tmap tmap</p> <p>pip install faerun</p> <p>pip install matplotlib</p> <p>conda install scipy</p> <p>conda install -c rdkit rdkit</p> <p>conda install -c conda-forge mhfp</p> </blockquote> <p> </p> <p>Usage: python plot_COCONUT.py</p> <p>Then it will use COCONUT.csv to generate index.html and index.js. Open index.html to see result.</p> <h1>Other large input files</h1> <p>Tanimoto_COCONUT_SIDERITE.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/Clustering_coconut.m">SIDERITE/predicted_new/Clustering_coconut.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>Sid_structure_output3.xlsx is used in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/statistics/Figure1.m" target="_blank" rel="noopener">SIDERITE/statistics/Figure1.m at main · RuolinHe/SIDERITE</a>, <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a> and <a href="https://github.com/RuolinHe/SIDERITE/blob/main/siderophore_process/Sid_process_code.m" target="_blank" rel="noopener">SIDERITE/siderophore_process/Sid_process_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT4MetFrag_Canonical.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT_r.txt is the output file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>. and the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/isSiderophore1.py" target="_blank" rel="noopener">SIDERITE/predicted_new/isSiderophore1.py at main · RuolinHe/SIDERITE.</a></p> <p> </p> <p>COCONUT4MetFrag.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/CheckSMILES2.py" target="_blank" rel="noopener">SIDERITE/TAMP/CheckSMILES2.py at main · RuolinHe/SIDERITE</a>.</p> <p> </p>
FIG. 20 in Unveiling a hidden diversity: descriptions of nine new species of Ctenorillo Verhoeff, 1942 (Isopoda, Armadillidae) discovered in Brazilian caves and their importance for conservation
FIG. 20. — Ctenorillo potiguar Cardoso & Ferreira, n. sp.: A, limestone outcrops at the Furna Feia National Park, with the entrance of the Furna Feia cave (yellow star); B, detail of the Furna Feia cave entrance; C, inner portion of the Furna Nova cave, where specimens are found; D, habitus in natural condition.
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.