Find research datasets worth reusing

opencc-by-4.0May 2020View details →

Data citation for a forward stratigraphic-based porosity and permeability model developed for the Volve field, Norway.

The data, models, and script presented here are those used for developing a forward stratigraphic simulation. The data include: 24 suits of well logs, seismic data, forward stratigraphic simulation scenarios of the shallow marine depositional setting, synthetic wells derived from the stratigraphic model, and 3-D reservoir models in Eclipse and RMS formats. In addition, a short script from the property calculator tool in Petrel, which is was used to classify lithofacies-associations in the stratigraphic model is also provided. The Petrel software license and code used in GPM software to undertake these forward stratigraphic simulations cannot be provided, because Schlumberger, who are the developers of the software do not allow its code to be shared in any publication.

opencc-zeroAug 2020View details →

Lagrangian Atmospheric Model output for the Control, Onset and Development experiments

This dataset consists of model outputs from the Control, Onset and Development experiments. Each experiment has six ensembles which were integrated for three years. 6-hourly instantaneous surface (1000hPa) zonal and meridional wind speed (m/s) between 31°S-31°N is recorded in uv1000hPa_{Control, Onset, Development}_ens{1, 2, 3, 4, 5, 6}.dat. 6-hourly accumulated precipitation (mm) between 32°S-32°N is stored in precip_{ Control, Onset, Development}_ens{1, 2, 3, 4, 5, 6}.dat. Note the precip.*dat records accumulated rainfall for the past 6 hours. The missing data is recorded as nan.

opencc-zeroAug 2020View details →

Data from: Development of an adrenocortical cancer humanized mouse model to characterize anti-PD1 effects on tumor microenvironment

Context: While the development of immune checkpoint inhibitors has transformed treatment strategies of several human malignancies, research models to study immunotherapy in ACC are lacking. Objective: To explore the effect of anti-PD1 immunotherapy on the alteration of the immune milieu in ACC in a newly generated preclinical model and correlate with the response of the matched patient. Design, Setting and Intervention: To characterize the CU-ACC2-M2B patient-derived xenograft in a humanized mouse model, evaluate the effect of a PD-1 inhibitor therapy and compare to the CU-ACC2 patient with metastatic disease. Results: Characterization of the CU-ACC2-hu-CB-BRGS model confirmed ACC origin and match with the original human tumor. Treatment of the mice with pembrolizumab demonstrated significant tumor growth inhibition (TGI = 60%) compared to controls, which correlated with increased tumor infiltrating lymphocyte activity, with an increase of human CD8+ T cells (p<0.05), HLA-DR+ T cells (p<0.05) as well as Granzyme B+ CD8+ T cells (<0.001). In parallel, treatment of the CU-ACC2 patient, who had progressive disease, demonstrated a partial response with 79%-100% reduction in the size of target lesions, and no new sites of metastasis. Pre-treatment analysis of the patient's metastatic liver lesion demonstrated abundant intra-tumoral CD8+ T cells by immunohistochemistry. Conclusions: Our study reports the first humanized ACC PDX mouse model which may be useful to define mechanisms and biomarkers of response and resistance to immune-based therapies, to ultimately provide more personalized care for patients with ACC.

opencc-zeroAug 2020View details →

CESM1.2 simulation output for: The role of westerly wind bursts during different seasons versus ocean heat recharge in the development of extreme El Niño in a climate model

This is the subset of CESM1.2 model simulation output that was used for analysis and visualization of Yu and Fedorov [2020] (DOI:10.1029/2020GL088381). Please refer to README for details.

opencc-by-4.0Oct 2020View details →

Dataset for "Appreciating our 60 years of life": Developing a transactional model of narrative identity and relationships experienced within an individualized, technological intervention for dementia care

Interview transcripts and participant information for “Appreciating our 60 years of life”: Developing a transactional model of narrative identity and relationships experienced within an individualized, technological intervention for dementia care.  Collected as part of the SENSE-GARDEN Multisite Trial (https://sense-garden.eu/). This work was supported by AAL under Grant AAL/Call2016/054-b/2017, co-funded by the European Commission and National Funding Agencies of Norway, Belgium, Romania, and Portugal.

opencc-by-4.0Oct 2020View details →

Joint Autoregressive and Graph Models for Software and Developer Social Networks

This zip contains three CSV files and one folder. This dataset contains information for the recent ten distributions. <ul> <li>developer_attributes.csv: There are seven columns in this file.  "distro" (str) represents distribution name. "source" (str) denotes source package name. "person_id" (str) indicates developer identity. "closes" (int), "high" (int),  "medium" (int), "low" (int) are the features.</li> <li>source_bugs.csv: In this file, three columns are present. "distro" (str) represents the distribution name. "source" (str) represents the source package name. "bug_count" (int) denotes the number of bugs that source package has at a particular distribution.</li> <li>source_sizes.csv: In this file, three columns are present. "distro" (str) represents the distribution name. "source" (str) represents source package name. "size" (int) denotes the size of the package.</li> <li>Dependency folder: Within this folder, ten dependency lists are present. Each file contains two columns i.e "start" (str) and "target" (str). Both of them represent source packages. So, we read as the "start" source package depends on "target" source package. </li> </ul> Here is the arxiv version of our paper: <a href="https://arxiv.org/abs/2101.08729">https://arxiv.org/abs/2101.08729</a>.  Here is the portal link: <a href="https://sites.google.com/view/rima-hazra/swnet">https://sites.google.com/view/rima-hazra/swnet</a>

opencc-by-4.0Dec 2020View details →

Amory et al. (2021), Geoscientific Model Development : data, model outputs and source code

Data and model outputs for the replication of the analysis made in: (see the published version of this article in Geoscientific Model Development, 2021 - please cite this version if you use these data) C. Amory, C. Kittel, L. Le Toumelin, C. Agosta, A. Delhasse, V. Favier, and X. Fettweis: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adelie Land, East Antarctica, Geoscientific Model Development, accepted, 2021.  See README.txt for a full description of the dataset content Please contact me at amory.charles@live.fr if you need other half-hourly outputs or for more details on the dataset

opencc-zeroJan 2021View details →

Integrating stakeholders' perspectives and spatial modelling to develop scenarios of future land use and land cover change in northern Tanzania

Rapid rates of land use and land cover change (LULCC) in eastern Africa and limited instances of genuinely equal partnerships involving scientists, communities and decision makers challenge the development of robust pathways toward future environmental and socioeconomic sustainability. We use a participatory modelling tool, Kesho, to assess the biophysical, socioeconomic, cultural and governance factors that influenced past (1959-1999) and present (2000-2018) LULCC in northern Tanzania and to simulate four scenarios of land cover change to the year 2030. Simulations of the scenarios used spatial modelling to integrate stakeholders' perceptions of future environmental change with social and environmental data on recent trends in LULCC. From stakeholders' perspectives, between 1959 and 2018, LULCC was influenced by climate variability, availability of natural resources, agriculture expansion, urbanization, tourism growth, and legislation governing land access and natural resource management. Among other socio-environmental-political LULCC drivers, the stakeholders envisioned that from 2018 to 2030 LULCC will largely be influenced by land health, natural and economic capital, and political will in implementing land use plans and policies. The projected scenarios suggest that by 2030 agricultural land will have expanded by 8-20% under different scenarios and herbaceous vegetation and forest land cover will be reduced by 2.5-5% and 10-19% respectively. Stakeholder discussions further identified desirable futures in 2030 as those with improved infrastructure, restored degraded landscapes, effective wildlife conservation, and better farming techniques. The undesirable futures in 2030 were those characterized by land degradation, poverty, and cultural loss. Insights from our work identify the implications of future LULCC scenarios on wildlife and cultural conservation and in meeting the Sustainable Development Goals (SDGs) and targets by 2030. The Kesho approach capitalizes on knowledge exchanges among diverse stakeholders, and in the process promotes social learning, provides a sense of ownership of outputs generated, democratizes scientific understanding, and improves the quality and relevance of the outputs.

opencc-zeroDec 2017View details →

Data from: Development of a protocol for environmental impact studies using causal modelling

1- The global issue of water scarcity caused by climate change and human utilisation highlights the importance of an efficient assessment of water quality in freshwater systems. One of the challenges facing water management in environmental impact studies is the difficulty of inferring causality in complex systems. Traditional water assessment methods are inadequate because they are challenged to separate natural variation from the effect of human activities. 2- Knowing the causal structure of a complex ecosystem will enable managers to identify key anthropogenic, climate and flow drivers of water quality, and make informed decisions about interventions that improve water and environmental quality. In this study, I show how causal modelling can facilitate decision making for water treatment plant managers to improve their environmental management of this valuable resource. 3- Models built using causal modelling techniques, including structural equation modelling and the principles of Bayesian Networks, were utilised for management decision making purposes. The discharge load values were manipulated in the models to predict the effect of a potential intervention, e.g. treatment plant upgrade, on the values of the water quality variables in the creek. That is, water quality variables were predicted when an imaginary or counterfactual situation was imposed on the models. 4- This study showed that there would not be any observable effect of effluent on macroinvertebrate communities if the discharge loads of chlorophyll a, total organic carbon, total phosphorus, nitrate, and conductivity were reduced to 0.1 of observed values. The concentrations of environmental variables in the creek would return to their baseline levels when their corresponding discharge loads in the effluent were halved or divided by 10. 5- Based on the findings of this study, managers in the field of environmental impact studies can predict the response of a system in the presence of potential interventions under complex and uncertain conditions. The implementation of such techniques offers great promise in the wider field of environmental management where accounting for multiple factors structuring ecosystems in necessary to adequately represent causality.

opencc-zeroOct 2019View details →

Development and validation of a postoperative delirium prediction model for patients admitted to an intensive care unit in China: a prospective study

Objectives: We aimed to develop and validate a postoperative delirium (POD) prediction model for patients admitted to the intensive care unit (ICU). Design: A prospective study was conducted. Setting: The study was conducted in the surgical, cardiovascular surgical, and trauma surgical ICUs of an affiliated hospital of a medical university in Heilongjiang Province, China. Participants: This study included 400 patients (≥18 years old) admitted to the ICU after surgery. Primary and secondary outcome measures: The primary outcome measure was postoperative delirium assessment during ICU stay. Results: The model was developed using 300 consecutive ICU patients and was validated using 100 patients from the same ICUs. The model was based on five risk factors: Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity; acid-base disturbance; and history of coma, diabetes, or hypertension. The model had an area under the receiver operating characteristics curve of 0.852 (95% confidence interval: 0.802–0.902), Youden index of 0.5789, sensitivity of 70.73%, and specificity of 87.16%. The Hosmer-Lemeshow goodness of fit was 5.203 (P = 0.736). At a cut-off of 24.5%, the sensitivity and specificity were 71% and 69%, respectively. Conclusions: The model, which used readily available data, exhibited high predictive value regarding risk of intensive care unit postoperative delirium (ICU-POD) at admission. Use of this model may facilitate better implementation of preventive treatments and nursing measures.

Data from: A framework for developing ecosystem-specific nutrient criteria: integrating biological thresholds with predictive modeling

We present a novel ecosystem-specific framework for developing nutrient criteria from biological thresholds and predictive modeling (BTPM) and an application of this framework to lakes in Michigan, U.S. The four main components for the BTPM framework are: (1) to predict each ecosystem s expected nutrient concentration in the absence of human effects using a predictive model, (2) to identify important biological thresholds along a nutrient gradient (i.e., biological [BIO] benchmarks), (3) to determine each ecosystem s current nutrient concentration, and (4) to use the above information to derive a nutrient criterion for each ecosystem using the BTPM algorithm. The BTPM framework is extremely flexible in that it can be applied to any aquatic ecosystem type or nutrient and the four components can be implemented in a variety of ways. Our BTPM framework has two additional features: it recognizes that prior to human disturbance, ecosystems varied in their natural nutrient concentrations, and it incorporates risk into the decision-making process. In the simplest scheme, a nutrient criterion is set at a BIO benchmark greater than the expected nutrient concentration. However, to protect ecosystems more conservatively, a criterion is set at current lake nutrient concentrations if current is less than the BIO benchmark. In our application of the BTPM framework, we developed total phosphorus (TP) criteria for a diverse set of 374 lakes in MI. The expected lake TP concentrations in the absence of human effects ranged from 3 µg L-1 to 24 µg L-1, suggesting that a single criterion approach would not be appropriate.We found two predominant benchmarks in the biological data along the TP gradient, one for zooplankton metrics at 8 µg L-1, and one for phytoplankton metrics at 18 µg L-1. We present the sequence of analyses and decisions that could be used to apply this approach in a management context using Michigan lakes as an example.

opencc-zeroDec 2015View details →

Data from: Towards a common methodology for developing logistic tree mortality models based on ring-width data

Tree mortality is a key process shaping forest dynamics. Thus, there is a growing need for indicators of the likelihood of tree death. During the last decades, an increasing number of tree-ring based studies have aimed to derive growth–mortality functions, mostly using logistic models. The results of these studies, however, are difficult to compare and synthesize due to the diversity of approaches used for the sampling strategy (number and characteristics of alive and death observations), the type of explanatory growth variables included (level, trend, etc.), and the length of the time window (number of years preceding the alive/death observation) that maximized the discrimination ability of each growth variable. We assess the implications of key methodological decisions when developing tree-ring based growth–mortality relationships using logistic mixed-effects regression models. As examples, we use published tree-ring datasets from Abies alba (13 different sites), Nothofagus dombeyi (one site), and Quercus petraea (one site). Our approach is based on a constant sampling size and aims at (1) assessing the dependency of growth–mortality relationships on the statistical sampling scheme used, (2) determining the type of explanatory growth variables that should be considered, and (3) identifying the best length of the time window used to calculate them. The performance of tree-ring-based mortality models was reasonably high for all three species (area under the receiving operator characteristics curve, AUC > 0.7). Growth level variables were the most important predictors of mortality probability for two species (A. alba, N. dombeyi), while growth-trend variables need to be considered for Q. petraea. In addition, the length of the time window used to calculate each growth variable was highly uncertain and depended on the sampling scheme, as some growth–mortality relationships varied with tree age. The present study accounts for the main sampling-related biases to determine reliable species-specific growth–mortality relationships. Our results highlight the importance of using a sampling strategy that is consistent with the research question. Moving towards a common methodology for developing reliable growth–mortality relationships is an important step towards improving our understanding of tree mortality across species and its representation in dynamic vegetation models.

opencc-zeroDec 2014View details →

Data from: Assessing cumulative impacts of forest development on the distribution of furbearers using expert-based habitat modeling

Cumulative impacts of anthropogenic landscape change must be considered when managing and conserving wildlife habitat. Across the central-interior of British Columbia, Canada, industrial activities are altering the habitat of furbearer species. This region has witnessed unprecedented levels of anthropogenic landscape change following rapid development in a number of resource sectors, particularly forestry. Our objective was to create expert-based habitat models for three furbearer species: fisher (Pekania pennanti), Canada lynx (Lynx canadensis), and American marten (Martes americana) and quantify habitat change for those species. We recruited 10 biologist and 10 trapper experts and then used the analytical hierarchy process to elicit expert knowledge of habitat variables important to each species. We applied the models to reference landscapes (i.e., registered traplines) in two distinct study areas and then quantified the change in habitat availability from 1990 to 2013. There was strong agreement between expert groups in the choice of habitat variables and associated scores. Where anthropogenic impacts had increased considerably over the study period, the habitat models showed substantial declines in habitat availability for each focal species (78% decline in optimal fisher habitat, 83% decline in optimal lynx habitat, and 79% decline in optimal marten habitat). For those traplines with relatively little forest harvesting, the habitat models showed no substantial change in the availability of habitat over time. The results suggest that habitat for these three furbearer species declined significantly as a result of the cumulative impacts of forest harvesting. Results of this study illustrate the utility of expert knowledge for understanding large-scale patterns of habitat change over long time periods.

Data from: "Genome-wide microsatellite marker development from next-generation sequencing of two non-model bat species impacted by wind turbine mortality: Lasiurus borealis and L. cinereus (Vespertilionidae)" in Genomic Resources Notes accepted 1 October 2013 to 30 November 2013

Tree-roosting bats in the genus Lasiurus are widespread, migratory species that have not been well characterized for population genetic diversity and structure due to a lack of genetic resources. Generating genetic resources in Lasiurus is made pressing by the need for conservation genetic assessments of demographic trends in this genus, which comprise a large percentage of bat mortalities at wind turbine sites across North America. We report on marker development from whole-genome Illumina sequencing of the red bat (Lasirus borealis) and the hoary bat (L. cinereus). We generated paired-end libraries for a single individual of each species, sequenced on the Illumina HiSeq platform. We mapped a total of 46.6 million reads to the Myotis lucifigus reference genome, and used bioinformatics searches to identify tends of thousands of simple sequence repeats (SSRs) distributed across the bat genome. We selected 48 candidate microsatellite loci to develop cross-species primer sequences for Lasiurus, assembled these into multiplex combinations, and tested for amplification and polymorphism levels in a sample of 23 individuals from each of L. borealis and L. cinereus. In total, we identified 42 highly polymorphic loci that could be robustly amplified and scored, the majority of which (39) were also combinable into highly multiplexed assays of 4-8 loci each. The combination of new genomic sequence assemblies, a large set of highly polymorphic microsatellite loci, and the ability to efficiently multiplex represents a significant contribution to the genetic resources available for population and comparative genetic studies of bats.

Data from: Development and validation of an expert-based habitat suitability model to support boreal caribou conservation

The long-term persistence of boreal caribou (Rangifer tarandus caribou) is threatened by the negative impacts of human activities, including industrial development. The vast geographical distribution and behavioural variability of caribou warranted the development and validation of an appropriate conservation tool for managers in eastern Canada. We developed a habitat suitability model for boreal caribou in Québec by integrating expert knowledge into a hierarchical analysis. We elicited responses from 14 experts on caribou ecology to determine the best spatiotemporal scales of application, the relative importance of habitat variables, the zone of influence of human infrastructure, and the parameterization of the model. Based on this input, we built the model using 8 habitat categories and 3 human infrastructure variables. Experts identified mature conifer-dominated forests and open lichen woodlands as the most important vegetation categories for boreal caribou, whereas density of and proximity to paved roads, forest roads, and mines decreased habitat quality. We mapped the resulting model over the entire province of Québec (up to the northern forest allocation limit), and validated it using independent GPS telemetry datasets acquired in 3 distinct regions. Our model predicted that habitat suitability was highest in the northeastern part of our study area, where timber harvest activities and roads were virtually absent. Conversely, southern parts of Québec were generally unsuitable for boreal caribou. Our habitat suitability model is among the first tools for boreal caribou conservation available to wildlife and land managers in Québec.

Data from: Model-assisted analysis of sugar metabolism throughout tomato fruit development reveals enzyme and carrier properties in relation to vacuole expansion

A kinetic model combining enzyme activity measurements and subcellular compartmentation was parameterized to fit the sucrose, hexose, and glucose-6-P contents of pericarp throughout tomato (Solanum lycopersicum) fruit development. The model was further validated using independent data obtained from domesticated and wild tomato species and on transgenic lines. A hierarchical clustering analysis of the calculated fluxes and enzyme capacities together revealed stage-dependent features. Cell division was characterized by a high sucrolytic activity of the vacuole, whereas sucrose cleavage during expansion was sustained by both sucrose synthase and neutral invertase, associated with minimal futile cycling. Most importantly, a tight correlation between flux rate and enzyme capacity was found for fructokinase and PPi-dependent phosphofructokinase during cell division and for sucrose synthase, UDP-glucopyrophosphorylase, and phosphoglucomutase during expansion, thus suggesting an adaptation of enzyme abundance to metabolic needs. In contrast, for most enzymes, flux rates varied irrespectively of enzyme capacities, and most enzymes functioned at <5% of their maximal catalytic capacity. One of the major findings with the model was the high accumulation of soluble sugars within the vacuole together with organic acids, thus enabling the osmotic-driven vacuole expansion that was found during cell division.

opencc-zeroMar 2020View details →

Multilevel modeling of time-series cross-sectional data reveals the dynamic interaction between ecological threats and democratic development

What is the relationship between environment and democracy? The framework of cultural evolution suggests that societal development is an adaptation to ecological threats. Pertinent theories assume that democracy emerges as societies adapt to ecological factors such as higher economic wealth, lower pathogen threats, less demanding climates, and fewer natural disasters. However, previous research confused within-country processes with between-country processes and erroneously interpreted between-country findings as if they generalize to within-country mechanisms. In this article, we analyze a time-series cross-sectional dataset to study the dynamic relationship between environment and democracy (1949-2016), accounting for previous misconceptions in levels of analysis. By separating within-country processes from between-country processes, we find that the relationship between environment and democracy not only differs by countries but also depends on the level of analysis. Economic wealth predicts increasing levels of democracy in between-country comparisons, but within-country comparisons show that democracy declines as countries become wealthier over time. This relationship is only prevalent among historically wealthy countries but not among historically poor countries, whose wealth also increased over time. By contrast, pathogen prevalence predicts lower levels of democracy in both between-country and within-country comparisons. Our longitudinal analyses identifying temporal precedence reveal that not only reductions in pathogen prevalence drive future democracy, but also democracy reduces future pathogen prevalence and increases future wealth. These nuanced results contrast with previous analyses using narrow, cross-sectional data. As a whole, our findings illuminate the dynamic process by which environment and democracy shape each other.

opencc-zeroDec 2018View details →

Data from: Developing allometric models to predict the individual aboveground biomass of shrubs worldwide

Aim Existing global models to predict standing woody biomass are based on trees characterized by a single principal stem, well-developed in height. However, their use in open woodlands and shrublands, characterized by multistemmed species with substantial crown development, generates a high level of uncertainty in biomass estimates. This limitation led us to i) develop global predictive models of shrub individual aboveground biomass based on simple allometric variables; ii) to compare the fit of these models with existing global biomass models; and iii) to assess whether models fit change when bioclimatic variables are considered. Location Global. Time period Present. Major taxa studied 118 species. Methods We compile a database of 3243 individuals across 49 sites distributed worldwide. Including basal diameter, height and crown diameter as predictor variables, we built potential models and compared their fit using generalized least squares. We used mixed effects models to determine if bioclimatic variables improved the accuracy of biomass models. Results Although the most important variable in terms of predictive capacity was stem basal diameter, crown diameter significantly improved the models fit, followed by height. Four models were finally chosen, with the best model combining all these variables in the same equation (R2 = 0.930, RMSE = 0.476). Selected models performed as well as established global biomass models. Including the individual bioform significantly improved the models fit. Main conclusions Basal diameter, crown diameter and height measures could be combined to provide robust AGB estimates of individual shrub species. Our study supplements well-established models developed for trees, allowing more accurate biomass estimation of multistemmed woody individuals. We further provide tools for a methodological standardization of individual biomass quantification in these species. We expect these results contribute to improve the quality of biomass estimates across ecosystems, but also to generate methodological consensus on field biomass assessments in shrubs.

Data from: Ocean circulation model predicts high genetic structure in a long-lived pelagic developer

Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology, and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes, and may not capture present-day connectivity between populations. Here we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase, and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns which tend to retain passive larvae within 20 - 50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks.