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54 results for “isolated trees”
Contrasting effects of host tree isolation on population connectedness in two tropical epiphytic bromeliads
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Data from: Edge-mediated compositional and functional decay of tree assemblages in Amazonian forest islands after 26 years of isolation
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Data from: Small but not isolated: a population genetic survey of the tropical tree Cariniana estrellensis (Lecythidaceae) in a highly fragmented habitat
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Data from: Local coexistence and genetic isolation of three pollinator species on the same fig tree species
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Data from: Waiving the extinction debt: can shade from coffee prevent extinctions of epiphytic plants from isolated trees?
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Data from: Current climate, isolation and history drive global patterns of tree phylogenetic endemism
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Data from: Landscape structure mediates zoochorous-dispersed seed rain under isolated pasture trees across distinct tropical regions
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Data from: Isolated trees support lower bird taxonomic richness than trees within habitat patches but similar functional diversity
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Data from: A unique ecological niche fosters hybridization of oak-tree and vineyard isolates of Saccharomyces cerevisiae.
Differential adaptation to distinct niches can restrict gene flow and promote population differentiation within a species. However, in some cases the distinction between niches can collapse, forming a hybrid niche with features of both environments. We previously reported that distinctions between vineyards and oak soil present an ecological barrier that restricts gene flow between lineages of Saccharomyces cerevisiae. Vineyard isolates are tolerant to stresses associated with grapes while North American oak strains are particularly tolerant to freeze-thaw cycles. Here, we report the isolation of Saccharomyces cerevisiae strains from Wisconsin cherry trees, which display features common to vineyards (e.g. high sugar concentrations) and frequent freeze-thaw cycles. Genome sequencing revealed that the isolated strains are highly heterozygous and represent recent hybrids of the oak x vineyard lineages. We found that the hybrid strains are phenotypically similar to vineyard strains for some traits, but are more similar to oak strains for other traits. The cherry strains were exceptionally good at growing in cherry juice, raising the possibility that they have adapted to this niche. We performed transcriptome profiling in cherry, oak, and vineyard strains and show that the cherry-tree hybrids display vineyard-like or oak-like expression, depending on the gene sets, and in some cases the expression patterns linked back to shared stress tolerances. Allele-specific expression in these natural hybrids suggested concerted cis-regulatory evolution at sets of functionally regulated genes. Our results raise the possibility that hybridization of the two lineages provides a genetic solution to the thriving in this unique niche.
Figure 9. A phylogenetic tree shows the genetic relationship between the C. sphaerospermum isolate 9 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 9. A phylogenetic tree shows the genetic relationship between the C. sphaerospermum isolate 9 investigated in this study as indicated by red dote (●), and the C. sphaerospermum isolates available in NCBI.
Data from: A unique ecological niche fosters hybridization of oak-tree and vineyard isolates of Saccharomyces cerevisiae.
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Core genome phylogenetic tree of two Campylobacter novaezeelandiae and four unclassified thermophilic Campylobacter isolates from Canadian agricultural surface water
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Expression profile of multipotent basal cells and basal-derived luminal cells isolated from the tip region (last 100µm) of the ductal tree of mouse prostate at P10-P13.
GEO Series GSE222786. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Using Decision Trees to Detect and Isolate Leaks in the J-2X
**Full title: Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine** Mark Schwabacher, NASA Ames Research Center Robert Aguilar, Pratt & Whitney Rocketdyne Fernando Figueroa, NASA Stennis Space Center **Abstract** The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically “learns” a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to “train” and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it “learned” a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location. **Introduction** The J-2X rocket engine will be tested on Test Stand A-1 at NASA Stennis Space Center (SSC) in Mississippi. A team including people from SSC, NASA Ames Research Center (ARC), and Pratt & Whitney Rocketdyne (PWR) is developing a prototype end-to-end integrated systems health management (ISHM) system that will be used to monitor the test stand and the engine while the engine is on the test stand[1]. The prototype will use several different methods for detecting and diagnosing faults in the test stand and the engine, including rule-based, model-based, and data-driven approaches. SSC is currently using the G2 tool [http://www.gensym.com](http://www.gensym.com) to develop rule-based and model-based fault detection and diagnosis capabilities for the A-1 test stand. This paper describes preliminary results in applying the data-driven approach to detecting and diagnosing faults in the J-2X engine. The conventional approach to detecting and diagnosing faults in complex engineered systems such as rocket engines and test stands is to use large numbers of human experts. Test controllers watch the data in near-real time during each engine test. Engineers study the data after each test. These experts are aided by limit checks that signal when a particular variable goes outside of a predetermined range. The conventional approach is very labor intensive. Also, humans may not be able to recognize faults that involve the relationships among large numbers of variables. Further, some potential faults could happen too quickly for humans to detect them and react before they become catastrophic. Automated fault detection and diagnosis is therefore needed. One approach to automation is to encode human knowledge into rules or models. Another approach is use data-driven methods to automatically learn models from historical data or simulated data. Our prototype will combine the data-driven approach with the model-based and rule-based appro
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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.