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6,569 results for “Long-term”
ARTEMIS project - Long-term field experiment (LTE) dataset for crop modelling
<p>The spreadsheets aim at collecting general information and specific data (e.g., crop yield, soil properties and weather) from long-term field experiments (LTE's) that are used to calibrate and validate ARMOSA model for ARTEMIS project - WP3 task 3.1 activity. Particularly, information reported will be useful for providing an overview of the distribution of agro-ecological systems, management strategies, field measures, and weather data available, useful to run ARMOSA model under current and future climate change scenarios.</p>
Long-term persistence of arbuscular mycorrhizal fungi in the rhizosphere and bulk soils of non-host Brassica napus and their networks of co-occurring microbes
<p>Arbuscular mycorrhizal fungi (AMF) are obligate plant symbionts that improve the nutrition and health of their host. Most, but not all crops form a symbiosis with AMF. It is the case for canola (<em>Brasica napus</em>), an important crop in the Canadian prairies that is known to not form this association. From 2008 to 2018, an experiment was replicated at three locations of the Canadian prairies and it was used to assess the impact of canola on the community of AMF naturally occurring in three cropping systems, canola monoculture, canola in a two rotation systems (two-years, canola-wheat and three-years barley-pea-canola). We sampled canola rhizosphere and bulk soils to (i) determine diversity and community structure of AMF, and (ii) assess how these AMF communities interact with other fungi and bacteria. We detected 49 AMF Amplicon Sequence Variant (ASV) in canola rhizosphere and bulk soils, confirming the persistence of a diversified AMF community in canola-planted soil, even after 10 years of canola monoculture, which was unexpected considering that canola is among non-mycorrhizal plants. Network analysis revealed a broad range of potential interactions between canola-associated AMF and some fungal and bacterial taxa. We report for the first time that two AMF, <em>Funneliformis mosseae</em> and <em>Rhizophagus iranicus,</em> shared their bacterial cohort almost entirely in bulk soil. Our results suggest the existence of non species-specific AMF-bacteria or AMF-fungi relationships that could benefit AMF in absence of host plants. The persistence of an AMF community in canola rhizosphere and bulk soils bring a new light on AMF ecology and lead to new perspectives for further studies about AMF and soil microbes interactions and AMF subsistence without mycotrophic host plants.</p>
Fig. 6 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 6. Relative abundance of the fish species in Lake Fenéki in the sampling years
Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care
<p>Minimal dataset to replicate findings and figures for the publication Groh et al., Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care.</p>
LEGACY DATASET: Reconstructed global long-term contiguous solar-induced fluorescence (LCSIF), MODIS period (2001-2021)
<p><strong>This is a legacy version of the dataset and is no longer recommended for use. Please access the latest version of LCSIF and LCREF with the following links:</strong></p> <ul> <li>LCSIF-AVHRR v3.1 (1982-2000): <a href="https://doi.org/10.5281/zenodo.13922371" target="_blank" rel="noopener">10.5281/zenodo.13922371</a></li> <li>LCSIF-AVHRR v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.13922367" target="_blank" rel="noopener">10.5281/zenodo.13922367</a></li> <li>LCSIF-MODIS v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.13922379" target="_blank" rel="noopener">10.5281/zenodo.13922379</a></li> <li>LCREF-AVHRR v3.1 (1982-2022): <a href="https://doi.org/10.5281/zenodo.11905960" target="_blank" rel="noopener">10.5281/zenodo.11905960</a></li> <li>LCREF-MODIS v3.1 (2001-2022): <a href="https://doi.org/10.5281/zenodo.11657459" target="_blank" rel="noopener">10.5281/zenodo.11657459</a></li> </ul> <p>Thanks a lot. Please feel free to reach out to Jianing Fang (<a href="mailto:jf3423@columbia.edu">jf3423@columbia.edu</a>) if you have any questions.</p>
SCORE D3.9 - Models for the long-term evolution of the coastline (package)
<p>SCORE project TD3.9 datasets and scripts:</p> <p>Modelling tools and local datasets produced in the SCORE Task 3.5, for the long-term evolution of the coastline and uncertainties, estimated by the study of local morphodynamic processes and climatic projections. It contains a hybrid 2D/3D modelling chain, for sediment transport processes connected to hydrodynamic models at the storm scale. </p>
Data used in "Revisiting the recent European droughts from a long-term perspective"
<p>Data used for evaluation on "Revisiting the recent European droughts from a long-term perspective".</p>
Idiosyncratic choice bias and feedback-induced bias differ in their long-term dynamics
<p>Overview<br>-------------------<br>This repository is associated with the paper "Idiosyncratic choice bias and feedback-induced bias differ in their long-term dynamics".</p> <p>All data and analyses required to reproduce our results are available in the stabilityFeedback folder.</p> <p>Data<br>-------------------<br>Response data and inter-session-delays are stored as sorted tables ("sortedTable_") and assign tables ("assignTable_"), respectively, by experiments (stabilityFeedback/stability folder and stabilityFeedback/feedback folder) and delay groups: <br>"stabilityFeedback/[EXPERIMENT_NAME]/[TABLES_TYPE]/[TABLE_TYPE]_[EXPERIMENT_NAME]_[DELAY_NAME].csv"</p> <p>Analysis<br>-------------------<br>The code required to reproduce all analyses and related figures is available in the stabilityFeedback/stabilityFeedbackICB.mlx MATLAB (R2023b) Live Editor file (also available as stabilityFeedbackICB.pdf).</p> <p>All figures are saved in the stabilityFeedback/figures folder in both MATLAB FIG and PDF formats. File names for the vertical task match those used in the paper, while file names for the horizontal task include " - appendix." at the end.</p> <p>For Binomial tests, we use the myBinomTest custom function, reference: Matthew Nelson (2015). https://www.mathworks.com/matlabcentral/fileexchange/24813-mybinomtest-s-n-p-sided MATLAB Central File Exchange. Retrieved February 9, 2016.</p> <p>Cite<br>-------------------<br>If you use code from this repository, please cite it using the Zenodo DOI: 10.5281/zenodo.13388598</p> <p>Contributors<br>-------------------<br>This code was authored by Lior Lebovich, 2024.</p>
Data from: Long-term evolution on complex fitness landscapes when mutation is weak
Understanding evolution on complex fitness landscapes is difficult both because of the large dimensionality of sequence space and the stochasticity inherent to population-genetic processes. Here I present an integrated suite of mathematical tools for understanding evolution on time-invariant fitness landscapes when mutations occur sufficiently rarely that the population is typically monomorphic and evolution can be modeled as a sequence of well-separated fixation events. The basic intuition behind this suite of tools is that surrounding any particular genotype lies a region of the fitness landscape that is easy to evolve to, while other pieces of the fitness landscape are difficult to evolve to (due to distance, being across a fitness valley, etc.). I propose a rigorous definition for this ``dynamical neighborhood' of a genotype which captures several aspects of the distribution of waiting times to evolve from one genotype to another. The neighborhood structure of the landscape as a whole can be summarized as a matrix, and I show how this matrix can be used to approximate the expected waiting time for certain evolutionary events to occur and to provide an intuitive interpretation to existing formal results on the index of dispersion of the molecular clock.
Data from: WMH and long-term outcomes in ischemic stroke: a systematic review and meta-analysis
OBJECTIVE: To investigate the relationship between baseline white matter hyperintensities (WMH) in patients with ischemic stroke and long-term risk of dementia, functional impairment, recurrent stroke, and mortality. METHODS: Following the MOOSE and PRISMA guidelines (PROSPERO protocol: CRD42018092857), we systematically searched Medline and Scopus for cohort studies of ischemic stroke patients examining whether MRI- or CT-assessed WMH at baseline are associated with dementia, functional impairment, recurrent stroke, and mortality at 3 months or later post-stroke. We extracted data and evaluated study quality with the Newcastle-Ottawa scale. We pooled relative risks (RR) for the presence and severity of WMH using random-effects models. RESULTS: We included 104 studies with 71,298 ischemic stroke patients. Moderate/severe WMH at baseline were associated with increased risk of dementia (RR: 2.17, 95%CI: 1.72-2.73), cognitive impairment (RR: 2.29, 95%CI: 1.48-3.54), functional impairment (RR: 2.21, 95%CI: 1.83-2.67), any recurrent stroke (RR: 1.65, 95%CI: 1.36-2.01), recurrent ischemic stroke (RR: 1.90, 95%CI: 1.26-2.88), all-cause mortality (RR: 1.72, 95%CI: 1.47-2.01), and cardiovascular mortality (RR: 2.02, 95%CI: 1.44-2.83). The associations followed dose-response patterns for WMH severity and were consistent for both MRI- and CT-defined WMH. The results remained stable in sensitivity analyses adjusting for age, stroke severity, and cardiovascular risk factors, in analyses of studies scoring high in quality, and in analyses adjusted for publication bias. CONCLUSIONS: Presence and severity of WMH are associated with substantially increased risk of dementia, functional impairment, stroke recurrence, and mortality after ischemic stroke. WMH may aid clinical prognostication and the planning of future clinical trials.
Data from: Long-term monitoring dataset of fish assemblages impinged at nuclear power plants in northern Taiwan
The long-term species diversity patterns in marine fish communities are garnering increasing attention from ecologists and conservation biologists. However, current databases on quantitative abundance information lack consistent long-term time series, which are particularly important in exploring the possible underlying mechanism of community changes and evaluating the effectiveness of biodiversity conservation measures. Here we describe an impinged fish assemblage dataset containing 1, 283, 707 individuals from 439 taxa. Once a month over 19 years (1987–1990 and 2000–2014), we systematically collected the fish killed by impingement upon cooling water intake screens at two nuclear power plants on the northern coast of Taiwan. Because impingement surveys have low sampling errors and can be carried out over many years, they serve as an ideal sampling tool for monitoring how fish diversity and community structure vary over an extended period of time.
Data from: Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data
Climate conditions, such as temperature or precipitation averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous U.S., and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability versus 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs.
FIG. 2 in A biotic survey and inventory of the dynastine scarab beetles of Mesoamerica, North America, and the West Indies: review of a long-term, multicountry project
FIG. 2. — The many forms and sizes of Dynastinae. Photo: M. L. Jameson.
Long-term Use of Takepron on the Prevention of Recurrence of Gastric/Duodenal Ulcer in Patients Receiving Non-steroidal Anti-inflammatory Drugs
ClinicalTrials.gov study NCT02099708. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Evaluation of the 24/7 EEG SubQ System for Ultra Long-Term Recording of Patients With Epilepsy Involving the Temporal Lobe Region.
ClinicalTrials.gov study NCT04526418. IPD Sharing: NO. Countries: 3. Publications: 0.
A Novel Online Calculator to Predict Long-term Survival and Recurrence Risk of Patients With Gastric Adenocarcinoma
ClinicalTrials.gov study NCT06337266. IPD Sharing: NO. Countries: 1. Publications: 0.
LOG-I - Impact Study of LOG-AFTER Software on Long-term Monitoring of Former Patients (LOG-I - LOG-Impact Study)
ClinicalTrials.gov study NCT06939322. IPD Sharing: NO. Countries: 1. Publications: 0.
Vascular Endothelial Inflammation and Dysfunction in Pediatric Long-term Cancer Survivors
ClinicalTrials.gov study NCT02032121. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Special Investigation (Long-term Investigation) in Patients With Crohn's Disease
ClinicalTrials.gov study NCT01464333. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Long-term Clinical Study of CN128 in Thalassemia Patients
ClinicalTrials.gov study NCT04614779. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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.