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opencc-zeroMar 2022View details →

Turgor loss point predicts survival responses to experimental and natural drought in tropical tree seedlings

Identifying key traits that can serve as proxies for species drought resistance is crucial for predicting and mitigating effects of climate change in diverse plant communities. Turgor loss point (πtlp) is a recently emerged trait that has been linked to species distributions across gradients of water availability. However, a direct relationship between πtlp and species ability to survive drought has yet to be established for woody species. Using a manipulative field experiment to quantify species drought resistance (i.e. their survival response to drought), combined with measurements of πtlp for 16 tree species, we show a negative relationship between πtlp and seedling drought resistance. Using long-term forest plot data, we also show that πtlp predicts seedling survival responses to a severe El Niño-related drought, although additional factors are clearly also important. Our study demonstrates that species with lower πtlp exhibit higher survival under both experimental and natural drought. These results provide a missing cornerstone in the assessment of the traits underlying drought resistance in woody species and strengthen πtlp as a proxy for evaluating which species will lose or win under projections of exacerbating drought regimes.

opencc-by-4.0Mar 2022View details →

Flaky Test Prediction using GraphCode2Vec

<a href="https://zenodo.org/api/files/28bc0577-f62a-4ecc-9bd4-86e6036d7c72/Flakify_baseline.tar.gz">Flakify_baseline.tar.gz</a> is the baseline code from https://github.com/uOttawa-Nanda-Lab/Flakify , Please cite their work and it is not an official tar file. We put it here because we have to make sure they use the same dataset. They finetune CodeBERT 200 epochs in total <a href="https://zenodo.org/api/files/28bc0577-f62a-4ecc-9bd4-86e6036d7c72/data.tar.gz">data.tar.gz</a> is the dataset for GraphCode2Vec and please decompress it in the root folder of the project. <a href="https://zenodo.org/api/files/28bc0577-f62a-4ecc-9bd4-86e6036d7c72/results_grid_search.tar.gz">results_grid_search.tar.gz</a> is the grid search results. GraphCode2Vec for Flaky, <a href="https://github.com/Marvinmw/Flaky">https://github.com/Marvinmw/Flaky</a>

opencc-by-4.0Dec 2021View details →

Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks

Supplementary Tables - Version 2

opencc-zeroMar 2022View details →

Community leaf dry matter content predicts grassland production

Plant growth correlates with values of collinear (covarying) traits from the leaf economics spectrum. Environmental variation and differences in community composition may alter contributions of these traits to plant production and thereby limit the consistency of trait-based growth predictions among years and plant communities. We tested effects of interannual variation in precipitation and differences in grassland community composition (planted monoculture of switchgrass, Panicum virgatum, and mixture of perennial herbaceous species) on the utility of two traits from the leaf economics spectrum (leaf dry matter content [LDMC] and plant [N]) to predict aboveground net primary production (ANP) during spring of 6 years. Spatial and temporal variation in spring production correlated with community-scale (species-abundance weighted) values of both traits, but community LDMC explained 66% of the variance in production and accounted for ≥89% of the variance in ANP explained by the two traits combined. The ANP response to trait variation and the variance in ANP explained by trait values differed with precipitation and between communities. Greater precipitation increased the production response to trait variation by increasing slopes of ANP-trait regression relationships and increased the variance in ANP explained by trait values. Communities differed in response to precipitation variation and in the role of annual variation in the [N]-LDMC relationship in explaining variance in ANP. Results indicate that mean trends in grassland production can be predicted using community-scale values of LDMC. Trait-based predictions of grassland production could be improved, however, by accommodating precipitation and community effects on production-trait relationships.

FURIN promoter methylation predicts the risk of incident diabetes: A prospective analysis in the Gusu cohort

Background: Furin has been associated with diabetes but the underlying mechanisms are unclear. As a mediator linking fixed genome and dynamic environment, DNA methylation of its coding gene FURIN may be involved. Here, we aimed to examine the prospective association between DNA methylation in FURIN promoter and incident diabetes during 4 years of follow-up in Chinese adults. Methods: DNA methylation levels in FURIN promoter were quantified by target bisulfite sequencing using peripheral blood from 1836 participants in the Gusu cohort who were free of diabetes at baseline. To examine the association between DNA methylation levels in FURIN promoter and incident diabetes, we constructed a logistic regression model adjusting for the conventional factors. Multiple testing was controlled by adjusting for the total number of CpG sites assayed using the false-discovery rate approach. Results: Among the 1836 participants free of diabetes at baseline, 109 (5.94%) participants developed diabetes during the average of 4 years of follow-up. Hypermethylation at two of the eight CpG sites assayed in the FURIN promoter was associated with an increased risk of diabetes, after multivariable adjustment and multiple testing correction. Every 5% increment in methylation levels at CpG1 and CpG2 were associated with a 22% (OR=1.22, 95%CI: 1.05-1.43, P=0.009, q=0.038) and 39% (OR=1.39, 95%CI: 1.08-1.77, P=0.009, q=0.038) higher risk of incident diabetes, respectively. The gene-based association analysis revealed that DNA methylation at multiple CpG loci was jointly associated with incident diabetes (P<0.001). Using the average methylation level of the 8 CpG loci in FURIN promoter revealed a similar association (OR=1.28, 95% CI: 1.02–1.62, P=0.037). Conclusions: These results suggested that the hypermethylation levels in FURIN promoter were associated with an increased risk for incident diabetes in Chinese adults.

History and environment shape spatial genetic variation and predict climate maladaptation in a narrowly distributed serotinous pine, Pinus muricata

Understanding the distribution of genetic diversity and differentiation in species with disjunct and isolated populations is critical for assessing how environment shapes genetic variation and the potential response to climate change. In contrast to the large distributions and population sizes of most pine species, Pinus muricata (Bishop pine) occurs in a small number of isolated and disjunct populations occupying a narrow band of environmental conditions along the coast of western North America. We used genotyping by sequencing to generate population genomic data for trees sampled from nearly all existing populations of P. muricata (12 populations, 213 individuals, 7,828 loci) to describe the spatial arrangement of genetic differentiation and diversity. We used genetic-environment association (GEA) analyses to quantify the contribution of environmental variables to local adaptation and spatial genetic structure. Based on these results, we quantified relative levels of potential maladaptation given future climate projections at 2041 – 2060 and 2081 – 2100. Our analyses reveal pronounced spatial genetic structure across the distribution, with most populations forming genetically identifiable groups across a latitudinal gradient, and remarkable evidence for differentiation among three proximally distributed stands on Santa Cruz Island. Despite occurring in small, isolated populations, P. muricata do not exhibit strongly reduced diversity. GEA analyses suggested that specific soil and climate variables have contributed to local adaptation. Genomic offset analyses suggest geographic variation in potential maladaptation, with northern populations experiencing higher levels under projected climate change. Overall, our results suggest that isolation and local adaptation have shaped genetic variation among disjunct populations, and illustrate the consequences of this variation for P. muricata under projected climate change.

opencc-by-4.0Apr 2022View details →

Does Investor Sentiment Predict Bitcoin Return and Volatility? - A Quantile Regression Approach

This dataset was used in generating findings for the paper titled "Does Investor Sentiment Predict Bitcoin Return and Volatility? - A Quantile Regression Approach".

The role of aerosol-radiation interaction in the meteorology prediction at the weather scale

<a name="OLE_LINK53"></a>The current capabilities of the numerical weather prediction (NWP) model to simulate aerosol-radiation interaction (ARI) impacts on weather prediction are still rarely considered compared with climate models. Here, the NWP model GRAPES_CUACE is used to evaluate the role of the ARI in meteorology prediction at the weather scale in China. The results show that the online calculation of ARI in the model can <a name="OLE_LINK99"></a>extensively improve the meteorology prediction accuracy involving temperature, wind, and pressure at most vertical <a name="OLE_LINK12"></a>levels in relatively clean, light, and heavy pollution stages. This improvement significantly occurs in the meteorology factors below 950 hPa prediction such as temperature at 2 m, 1000, and 950 hPa, and mean sea level pressure, particularly in heavy pollution areas and stages. <a name="OLE_LINK13"></a>Unlike temperature, the improvement of ARI in the predicted wind <a name="OLE_LINK52"></a>at the height of the boundary layer is more significant than near-surface. However, this improvement declines when the low-cloud exists.

opencc-by-4.0Apr 2022View details →

Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography

I uploaded the database of the extracted features for each enrolled patient in the manuscript "Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography" to evaluate radiomic features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptor; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer.

Data from: Size, species, and fire behavior predict tree and liana mortality from experimental burns in the Brazilian Amazon

Anthropogenic understory fires have affected large areas of tropical forest in recent decades, particularly during severe droughts. Yet, the mechanisms that control fire-induced mortality of tropical trees and lianas remain ambiguous due to the challenges associated with documenting mortality given variation in fire behavior and forest heterogeneity. In a seasonally dry Amazon forest, we conducted a burn experiment to quantify how increasing understory fires alter patterns of stem mortality. From 2004 to 2007, tree and liana mortality was measured in adjacent 50-ha plots that were intact (B0 – control), burned once (B1), and burned annually for 3 years (B3). After 3 years, cumulative tree and liana mortality (≥1 cm dbh) in the B1 (5.8% yr−1) and B3 (7.0% yr−1) plots significantly exceeded mortality in the control (3.2% yr−1). However, these fire-induced mortality rates are substantially lower than those reported from more humid Amazonian forests. Small stems were highly vulnerable to fire-induced death, contrasting with drought-induced mortality (measured in other studies) that increases with tree size. For example, one low-intensity burn killed >50% of stems <10 cm within a year. Independent of stem size, species-specific mortality rates varied substantially from 0% to 17% yr−1 in the control, 0% to 26% yr−1 in B1, and 1% to 23% yr−1 in B3, with several species displaying high variation in their vulnerability to fire-induced mortality. Protium guianense (Burseraceae) exhibited the highest fire-induced mortality rates in B1 and B3, which were 10- and 9-fold greater than the baseline rate. In contrast, Aspidosperma excelsum (Apocynaceae), appeared relatively unaffected by fire (0.3% to 1.0% mortality yr−1 across plots), which may be explained by fenestration that protects the inner concave trunk portions from fire. For stems ≥10 cm, both char height (approximating fire intensity) and number of successive burns were significant predictors of fire-induced mortality, whereas only the number of consecutive annual burns was a strong predictor for stems <10 cm. Three years after the initial burn, 62 ± 26 Mg ha−1 (s.e.) of live biomass, predominantly stems <30 cm, was transferred to the dead biomass pool, compared with 8 ± 3 Mg ha−1 in the control. This biomass loss from fire represents ∼30% of this forest's aboveground live biomass (192 (±3) Mg ha−1; >1 cm DBH). Although forest transition to savanna has been predicted based on future climate scenarios, our results indicate that wildfires from agricultural expansion pose a more immediate threat to the current carbon stocks in Amazonian forests.

opencc-by-nc-nd-4.0Apr 2022View details →

Bird observation data for: Better together? Assessing different remote sensing products for predicting habitat suitability of wetland birds

This data repository contains the bird observation data used in Koma, Z., Seijmonsbergen, A.C., Grootes, M.W., Nattino, F., Groot, J., Sierdsema, H., Foppen, R. & Kissling, W.D. (2022): Better together? Assessing different remote sensing products for predicting habitat suitability of wetland birds. Diversity and Distributions 28: 685–699. The content of this directory is shared under Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND 4.0, see https://creativecommons.org/licenses/by-nc-nd/4.0/). For accessing the bird occurrence data for further use then reproducing this article you can contact with Henk Sierdsema (Henk.Sierdsema@sovon.nl) and Ruud Foppen (Ruud.Foppen@sovon.nl) for further information.

opencc-zeroMay 2022View details →

Personality and predictability in farmed calves using movement and space-use behaviours quantified by Ultra-wideband sensors

Individuals within a population often show consistent between individual differences in their average behavioral expression (personality), and consistent differences in their within-individual variability of behavior around the mean (predictability). Where correlations between different personality traits and/or the predictability of traits exist, these represent behavioral or predictability syndromes. In wild populations, behavioral syndromes have consequences for individual's survival and reproduction and affect the structure and functioning of groups and populations. The consequences of behavioral syndromes for farm animals is less well explored, partly due to the challenges in quantifying behavior of many individuals across time and context in a farm setting. Here, we use Ultra-Wideband location sensors to provide precise measures of movement and space use for 60 calves over 40-48 days. We find that individuals show consistent within and between individual variation in movement and space use and show correlations in personality and predictability, indicating the existence of "exploratory" and "active" personality types in farmed calves. We consider the consequences of such individual variability for cattle behavior and welfare and how such data may be used to inform management decision in farm animals.

opencc-by-4.0Apr 2022View details →

Code for Atmospheric Research publication - Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields

In this repository, we include the source codes for WRF namelist, figures, and height correction used in the Atmospheric Research publication "Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields" The namelist.wps and namelist.input in WRF namelist are using for making input and running simulation, and Fig scripts in Figure scripts are using for plotting the figures in the paper. hgt_corr in Height correction method is a code to correct the disparity of the 10-m height definition between the model and observation by applying the developed the height correction algorithm based on the Monin-Obukhov similarity theory.

opencc-by-4.0May 2022View details →

GBIF data for Marcer A., Chapman A., Wieczorek J.R., Picó F.X., Uribe F., Waller J. and Ariño A. (2022) "Uncertainty matters: ascertaining where specimens in natural history collections come from and its implications for predicting species distributions." Ecography.

This is the dataset used in the following publication: Marcer A., Chapman A., Wieczorek J.R., Picó F.X., Uribe F., Waller J. and Ariño A. (2022) "Uncertainty matters: ascertaining where specimens in natural history collections come from and its implications for predicting species distributions." Ecography. Code can be found at: https://github.com/arnaldmarcer/NHC-GeoUncertainty

opencc-zeroMay 2022View details →

Data for: Biogeographic history predicts bee community structure across floral resource gradients in southeast Australia

Aim: Plants populations are declining in their native ranges around the globe through the expansion of agriculture, urbanization, and plant invasions. We test the hypothesis that animal species that have spent more of their evolutionary history in a region are more dependent on native plants, particularly those plants that have spent more of their evolutionary history in the region, and are therefore more negatively impacted by native plant decline. Location: Yarra Valley landscapes, Australia Methods: We test the presence and pattern of phylogenetic signal in native bee community responses to local flower density of ancient Australian plant lineages and the amount of native vegetation in the surrounding landscape across farm and native vegetation sites. We also test phylogenetic signal in the frequency of bee visitation to flowers from ancient Australian plant lineages. We compare the patterns of phylogenetic signal to the current understanding of bee biogeographic histories to evaluate our hypothesis. Results: There was significant phylogenetic signal in responses to flower density of plants from ancient Australian lineages, and the frequency of visitation to these flowers, with most species from the ancient Australian bee clade being positively associated with these flowers. This is consistent with our hypothesis. Significant phylogenetic signal in response to native vegetation in the surrounding landscape was driven primarily by the more recently arrived bee linages, with ancient lineages able to persist on some farms where ancient Australian flowers were present (e.g. on roadsides). Main conclusions: Bee species that have spent more of their evolutionary history in Australia are more dependent on ancient Australian plant lineages and so most negatively impacted by the decline of these plants. This may be a broader phenomenon because phylogenetic conservatism in host plant use, the main assumption underlying our hypothesis, is common among herbivorous arthropods (~500,000 species).

opencc-by-4.0Mar 2017View details →

Airline Cancellation Prediction Dataset

The sample dataset attached shows some of the reasons that will predict the cancellation of a flight. You can use this for educational purposes.

opencc-by-4.0May 2022View details →

Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning: a SEER-based study

The data for this article: predicting diagnosis and survival of bone metastasis in breast cancer using machine learning: a SEER-based study.

opencc-zeroMay 2022View details →

Systematic prediction of EMS-induced mutations in a sorghum mutant population

Sorghum is a next-generation crop species with tremendous potential for discovering highly desirable agronomical traits. We described an improved method for the systematic detection of EMS-induced mutations in the previous sequencing of the M3 generation of 600 sorghum BTx623 mutants. We used both SAMtools and GATK-based variant-calling algorithms to demonstrate the general utility of the method. The approach also includes a clustering algorithm for detecting likely false-negative EMS-induced mutations. We detected 3,497,654 EMS-induced single nucleotide polymorphisms (SNPs) in 30,285 distinct sorghum genes, and cataloged 10,263 high impact and 136,639 moderate impact SNPs. We also implemented a light-weight web portal for searching the mutation database for the 600 sorghum mutants.

opencc-by-4.0May 2022View details →

Peripheral blood DNA methylation profiles predict future development of B-cell Non-Hodgkin Lymphoma

Lack of accurate methods for early lymphoma detection limits the ability to cure patients. Patients with Non-Hodgkin lymphomas (NHL) who present with advanced disease have worse outcomes. We developed a DNA methylation-based prediction tool for NHL, based on blood samples collected prospectively from 278 apparently healthy patients who were followed for up to 16 years to monitor for NHL development. A predictive score was developed using machine learning methods in a robust training/validation framework. Our predictive score incorporates CpG DNA methylation at 135 genomic positions, with higher scores predicting higher risk. It was 85% and 78% accurate for identifying patients at risk of developing future NHL, in patients with high or low epigenetic mitotic clock respectively, in a validation cohort. It was also sensitive at detecting active NHL (96.3% accuracy) and healthy status (95.6% accuracy) in additional independent cohorts. Scores optimized for specific NHL subtypes showed significant but lower accuracy for predicting other subtypes. Our score incorporates hyper-methylation of Polycomb and HOX genes, which have roles in NHL development, as well as PAX5 - a master transcriptional regulator of B-cell fate. Subjects with higher risk scores showed higher regulatory T-cells, memory B-cells, but lower naïve T helper lymphocytes fractions in the blood. A score based on DNA methylation in blood is accurate at predicting NHL development with lead time of up to 16 years. Future prospective studies will be required to confirm the utility of our signature for managing patients who are at high risk for developing future NHL.