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1,351 results for “intermediate”
Intermediate files accompanying manuscript "The genomic basis of reproductive and migratory behaviour in a polymorphic salmonid".
<p>Recent ecotypic differentiation provides unique opportunities to investigate the genomic basis and architecture of local adaptation, while offering insights into how species form and persist. Sockeye salmon (<em>Oncorhynchus nerka</em>) exhibit migratory and resident (‘kokanee’) ecotypes, which are further distinguished into shore-spawning and stream-spawning reproductive ecotypes. Here, we analysed 36 sockeye (stream-spawning) and kokanee (stream- and shore-spawning) genomes from a system where they co-occur and have a recent common ancestry (Okanagan Lake/River in British Columbia, Canada) to investigate the genomic basis of reproductive and migratory behaviour. Examination of the genomic landscape of differentiation, differences in allele frequencies, and genotype-phenotype associations revealed three main blocks of sequence differentiation on chromosomes 7, 12, and 20, associated with migratory behaviour, spawning location, and spawning timing. Several structural variants identified in these same areas suggest they could contribute to ecotypic differentiation directly as causal variants or via maintenance of their genomic architecture through recombination suppression mechanisms. Genes in these regions were related to spatial memory and swimming endurance (<em>SYNGAP</em>, <em>TPM3</em>), as well as eye and brain development (including <em>SIX6</em>), potentially associated with differences in migratory behaviour and visual habitats across spawning locations, respectively. Additional genes (<em>GREB1L</em>, <em>ROCK1</em>) identified have been associated with timing of migration in other salmonids and could explain variation in timing of spawning in our study. Together, these results based on the joint analysis of sequence and structural variation represent a significant advance in our understanding of the genomic landscape of ecotypic differentiation at different stages in the speciation continuum.</p>
LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species: Code and LiDAR data
<ol> <li>Visibility (viewshed) plays a significant and diverse role in animals' behavior and fitness. Understanding how visibility influences animal behavior requires the measurement of habitat visibility at spatial scales commensurate to individual animal choices. However, measuring habitat visibility at a fine spatial scale over a landscape is a challenge, particularly in highly heterogeneous landscapes (e.g., forests). As a result, our ability to model the influence of fine-scale visibility on animal behavior has been impeded or limited.</li> <li>In this study, we demonstrate the application of the concept of 3D cumulative viewshed in the study of animal spatial behavior at a landscape level. Specifically, we employed a newly described approach that combines terrestrial and airborne LiDAR to measure fine-scale habitat visibility (3D cumulative viewshed) on a continuous scale in forested landscapes. We applied the LiDAR-derived visibility to investigate how visibility in forests affects the summer habitat selection and the movement of 20 GPS-collared female red deer <em>Cervus</em> <em>elaphus</em> in a temperate forest in Germany. We used integrated step selection analysis to determine whether red deer show any preference for fine-scale habitat visibility and whether visibility is related to the rate of movement of red deer.</li> <li>We found that red deer selected intermediate habitat visibility. Their preferred level of visibility during the day was substantially lower than that of night and twilight, whereas the preference was not significantly different between night and twilight. In addition, red deer moved faster in high-visibility areas, possibly mainly to avoid predation and anthropogenic risk. Furthermore, red deer moved most rapidly between locations in the twilight.</li> <li>For the first time, the preference for intermediate habitat visibility and the adaption of movement rate to fine-scale visibility by a forest-dwelling ungulate species at a landscape scale was revealed. The LiDAR technique used in this study offers fine-scale habitat visibility at the landscape level in forest ecosystems, which would be of broader interest in the fields of animal ecology and behavior.</li> </ol>
LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species: Deer locational data
<ol> <li>Visibility (viewshed) plays a significant and diverse role in animals' behavior and fitness. Understanding how visibility influences animal behavior requires the measurement of habitat visibility at spatial scales commensurate to individual animal choices. However, measuring habitat visibility at a fine spatial scale over a landscape is a challenge, particularly in highly heterogeneous landscapes (e.g., forests). As a result, our ability to model the influence of fine-scale visibility on animal behavior has been impeded or limited.</li> <li>In this study, we demonstrate the application of the concept of 3D cumulative viewshed in the study of animal spatial behavior at a landscape level. Specifically, we employed a newly described approach that combines terrestrial and airborne LiDAR to measure fine-scale habitat visibility (3D cumulative viewshed) on a continuous scale in forested landscapes. We applied the LiDAR-derived visibility to investigate how visibility in forests affects the summer habitat selection and the movement of 20 GPS-collared female red deer <em>Cervus</em> <em>elaphus</em> in a temperate forest in Germany. We used integrated step selection analysis to determine whether red deer show any preference for fine-scale habitat visibility and whether visibility is related to the rate of movement of red deer.</li> <li>We found that red deer selected intermediate habitat visibility. Their preferred level of visibility during the day was substantially lower than that of night and twilight, whereas the preference was not significantly different between night and twilight. In addition, red deer moved faster in high-visibility areas, possibly mainly to avoid predation and anthropogenic risk. Furthermore, red deer moved most rapidly between locations in the twilight.</li> <li>For the first time, the preference for intermediate habitat visibility and the adaption of movement rate to fine-scale visibility by a forest-dwelling ungulate species at a landscape scale was revealed. The LiDAR technique used in this study offers fine-scale habitat visibility at the landscape level in forest ecosystems, which would be of broader interest in the fields of animal ecology and behavior.</li> </ol>
Data Set from the DMP survey and interviews - intermediate results
<p>This is the data set for a series of interviews in chemistry on data management (plans) and presents interim results. A more detailed analysis and description can be found in the paper "Road to a Chemistry-specific Data Management Plan" submitted to Data Science Journal (2022-12-15).<br> The interview series will continue in 2023 and final results will be published later in 2023.</p> <p>The aim of the conducted interview series is the enrichment of the online survey data from the RDA WG Discipline-specific Guidance for DMP and in a second step the development of a chemistry-specific data management plan template. For this purpose, the current status of data management as well as information about the workflows in the various chemical disciplines were requested in a personal interview with 22 participants so far.</p> <p>All the gathered information and examples will be used to develop a DMP template or guide in line with chemistry-specific requirements. The results provide a comprehensive outlook on the future developments of RDM in chemistry. Possible strategies for implementation are also discussed.</p>
Investigating the Use of AI-Generated Exercises for Beginner and Intermediate Programming Courses: A ChatGPT Case Study
<p>In recent years, artificial intelligence (AI) has been increasingly used in education and supports teachers in creating educational material and students in their learning progress. AI- driven learning support has recently been further strengthened by the release of ChatGPT, in which users can retrieve expla- nations for various concepts in a few minutes through chat. However, to what extent the use of AI models, such as ChatGPT, is suitable for the creation of didactically and content-wise good exercises for programming courses is not yet known. Therefore, in this paper, we investigate the use of AI-generated exercises for beginner and intermediate programming courses in higher education using ChatGPT. We created 12 exercise sheets with ChatGPT for a beginner to intermediate programming course focusing on the objects-first approach. We report our process, prompts, and experience using ChatGPT for this task and outline good practices we identified. The generated exercises are assessed and revised, primarily using ChatGPT, until they met the requirements of the programming course. We assessed the quality of these exercises by using them in our course as external teaching assignment at the University of Education Ludwigsburg and let the students evaluate them. Results indicate the quality of the generated exercises and the time-saving for creating them using ChatGPT. However, our experience showed that while it is fast to generate a good version of an exercise, almost every exercise requires minor manual changes to improve its quality.</p>
Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.
<p>This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong></p> <p>The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.</p>
Study of Efficacy and Safety of MBG453 in Combination With Azacitidine in Subjects With Intermediate, High or Very High Risk Myelodysplastic Syndrome (MDS) as Per IPSS-R, or Chronic Myelomonocytic Leu
ClinicalTrials.gov study NCT04266301. IPD Sharing: YES. Countries: 36. Publications: 1.
A Study of MBG453 in Combination With Hypomethylating Agents in Subjects With IPSS-R Intermediate, High or Very High Risk Myelodysplastic Syndrome (MDS).
ClinicalTrials.gov study NCT03946670. IPD Sharing: YES. Countries: 17. Publications: 1.
Data from: Changes in Invertebrate Food Web Structure Between High- and Low-productivity Environments are Driven by Intermediate but Not Top Predator Diet Shifts
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LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species: Deer locational data
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Comparative analysis of helminth infectivity: growth in intermediate hosts increases establishment rates in the next host
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Development of whole-genome prediction models to increase the rate of genetic gain in intermediate wheatgrass (Thinopyrum intermedium) breeding
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Sperm competition favours intermediate sperm size in a hermaphrodite
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Intermediate habitat fragmentation buffers droughts: How individual energy dynamics mediate mammal community response to stressors
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LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species: Code and LiDAR data
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Macaques preferentially attend to intermediately surprising information
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Coarse Woody Debris (CWD) biomass across a compositional gradient of intermediate-aged and mature forest stands within Interior Alaska collected 2008-2011.
This dataset includes coarse woody debris data for intermediate-aged and mature boreal forest stands across interior Alaska.
Fine Woody Debris (FWD) biomass across a compositional gradient of intermediate-aged and mature forest stands within Interior Alaska collected 2008-2011.
This dataset includes fine woody debris data for intermediate-aged and mature boreal forest stands across interior Alaska.
Foliage chemistry across a compositional gradient of intermediate-aged and mature forest stands within Interior Alaska collected 2008-2011.
This dataset includes foliage %C and %N data for intermediate-aged (20-59 yr old) and mature (60+ yr old) boreal forest stands across interior Alaska. Data have not been published.
Snag size and composition across a compositional gradient of intermediate-aged and mature forest stands within Interior Alaska collected 2008-2011.
This dataset includes snag biomass data for intermediate-aged and mature boreal forest stands across interior Alaska.
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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.