Find research datasets worth reusing

opencc-zeroDec 2018View details →

Data from: Increasing dependence of lowland populations on mountain water resources

Mountain areas provide disproportionally high runoff in many parts of the world, and here we quantify for the first time their importance for water resources and food production from the viewpoint of the lowland areas downstream. The dataset maps the degree to which lowland areas potentially depend on runoff contributions from mountain areas (39% of land mass) between the 1960s and the 2040s.

opencc-by-4.0Oct 2018View details →

Online Resource 2 - Radial displacement at the tunnel wall of a tunnel excavated with a single shield TBM at the state of equilibrium (comparison between different calculation methods)

The radial displacement at the tunnel wall at the state of equilibrium calculated with the various ConVergence-ConFinement (CV-CF) methods is compared with the results obtained with a 3D numerical model of a tunnel excavation. A sensibility analysis is performed in order to compare the performance of the CV-CF approaches. The choice of the values of the mechanical parameters of the ground and of the lining is carried out in an attempt to cover the large range of situations encountered within single shield TBM. The total set of results from the sensibility analysis is shown in this work. Results obtained from some empirical formula proposed by the authors are also included.

opencc-by-4.0Oct 2018View details →

Online Resource 1 – Maximal hoop stress developed in the lining of a tunnel excavated with a single shield TBM at the state of equilibrium (comparison between different calculation methods)

The maximal hoop stress developed in the lining of a tunnel at the state of equilibrium calculated with the various ConVergence-ConFinement (CV-CF) methods is compared with the results obtained with a 3D numerical model of a tunnel excavation. A sensibility analysis is performed in order to compare the performance of the CV-CF approaches. The choice of the values of the mechanical parameters of the ground and of the lining is carried out in an attempt to cover the large range of situations encountered within single shield TBM. The total set of results from the sensibility analysis is shown in this work. Results obtained from some empirical formula proposed by the authors are also included. A version 2 of the document with some minor corrections has been published.

Pre-trained models for Vietnamese Natural Resources and Environment Domain

Two Pre-trained models for Vietnamese Natural Resources and Environment Domain: - fastText - Word2vec

Vietnamese text datasets for domain of natural resources and environment

Two vietnamese text datasets have been crawlered and pre-processed for domain of natural resources and environment. These text datasets crawlered ( in domain of natural resources and environment) from: - Wikimedia. - Articles from 03 Journals - 19.666 legal documents - 2.637 scientific reports - 1.434 technical standard documents vnNREDataset2020 dataset: in CoNLL format (included Vietnamese NER labels using VnCoreNLP) vnNREsentences2020 dataset: 2.421.138 sentences (word segmented using VnCoreNLP)

GREEN-VARAN scores resources (GRCh37)

Processed non-coding prediction scores to be used with GREEN-VARAN This dataset contains the GRCh37 version for the following scores: <ul> <li>ReMM v0.3.1 (<a href="https://charite.github.io/software-remm-score.html">https://charite.github.io/software-remm-score.html</a>)</li> <li>NCBoost v.1 (<a href="https://github.com/RausellLab/NCBoost">https://github.com/RausellLab/NCBoost</a>)</li> <li>ExPECTO (<a href="https://hb.flatironinstitute.org/expecto/">https://hb.flatironinstitute.org/expecto/</a>)</li> <li>LinSight (<a href="https://github.com/CshlSiepelLab/LINSIGHT">https://github.com/CshlSiepelLab/LINSIGHT</a>)</li> <li>GWAVA v1.0 (<a href="https://www.sanger.ac.uk/sanger/StatGen_Gwava">https://www.sanger.ac.uk/sanger/StatGen_Gwava</a>)</li> </ul> If you use any of these score annotations with GREEN-VARAN please cite also the corresponding paper.

GREEN-VARAN AF resources

This dataset contains processed files from gnomAD that can be used with GREEN-VARAN. These files represent the genome-wide variants from gnomAD, but INFO fields have been subset to contain just essential AF annotations. <ul> <li>GRCh37 version is adapted from gnomAD v2.1.1 genome VCF</li> <li>GRCh38 version is adapted from gnomAD v3 genome VCF</li> </ul> See: <a href="https://gnomad.broadinstitute.org/">https://gnomad.broadinstitute.org/</a> If you use gnomAD AF annotations with GREEN-VARAN don't forget to cite also the original gnomAD paper as described in <a href="https://gnomad.broadinstitute.org/terms">https://gnomad.broadinstitute.org/terms</a>.

GREEN-VARAN scores resources (DANN GRCh38)

Processed DANN scores to be used with GREEN-VARAN This dataset contains the GRCh38 version for DANN. See: <a href="https://academic.oup.com/bioinformatics/article/31/5/761/2748191">https://academic.oup.com/bioinformatics/article/31/5/761/2748191</a> If you use DANN score annotations with GREEN-VARAN don't forget to cite also the original DANN paper.

GREEN-VARAN scores resources (FIRE GRCh38)

Processed FIRE scores to be used with GREEN-VARAN This dataset contains the GRCh38 version for FIRE. See: <a href="https://sites.google.com/site/fireregulatoryvariation/">https://sites.google.com/site/fireregulatoryvariation/</a> If you use FIRE score annotations with GREEN-VARAN don't forget to cite also the original FIRE paper.

GREEN-VARAN scores resources (GRCh38)

Processed non-coding prediction scores to be used with GREEN-VARAN This dataset contains the GRCh38 version for the following scores. When not available from the original source, the GRCh38 coordinates were obtained by liftover. <ul> <li>ReMM v0.3.1 (<a href="https://charite.github.io/software-remm-score.html">https://charite.github.io/software-remm-score.html</a>)</li> <li>NCBoost v.1 (<a href="https://github.com/RausellLab/NCBoost">https://github.com/RausellLab/NCBoost</a>)</li> <li>ExPECTO (<a href="https://hb.flatironinstitute.org/expecto/">https://hb.flatironinstitute.org/expecto/</a>)</li> <li>LinSight (<a href="https://github.com/CshlSiepelLab/LINSIGHT">https://github.com/CshlSiepelLab/LINSIGHT</a>)</li> <li>GWAVA v1.0 (<a href="https://www.sanger.ac.uk/sanger/StatGen_Gwava">https://www.sanger.ac.uk/sanger/StatGen_Gwava</a>)</li> </ul> If you use any of these score annotations with GREEN-VARAN please cite also the corresponding paper.

Resource Management - Cloud Continuum

Dataset and classification of articles and proceedings for Resource Management in the Edge-Fog and Cloud Continuum. Resource management aspects include data aggregation, offloading, P2P data sharing, scheduling (auto-scaling) and load-balancing.

Data from: Cold and hungry: combined effects of low temperature and resource scarcity on an edge-of-range temperate primate, the golden snub-nose monkey

Both biotic and abiotic factors play important roles in influencing ecological distributions and niche limits. Where biotic and abiotic stressors co-occur in space and time, homeostatic systems face a different category of challenge in which stressors compound to impose a challenge that is greater than the sum of the separate factors. We studied the homeostatic strategies of the golden snub-nosed monkey (Rhinopithecus roxellana), a species living in temperate deciduous forests at the edge of the global distribution range for folivorous primates, to cope with the co-occurrence of cold temperatures and resource scarcity during winter. We discovered that in winter the monkeys experience a dietary energy deficit of 101 kJ/mbm·day-1 compared with calculated needs, despite increased feeding. This is partly offset by behavioral changes (reduced locomotion and increased resting) and reducing skin temperature by an average of 3.2 oC through a cutaneous vasoconstriction to decrease heat loss. However, their major strategy is ingesting surplus energy and accumulating fat reserves when food was not limiting during summer and autumn. Their 14% of body mass lost over the winter represented an energy yield of 102 kJ/mbm·day-1, which closely matched the calculated winter energy deficit of 101 kJ/mbm·day-1. However, the latter value assumes that all the 75.41kJ/mbm·day-1 of protein ingested in winter was available for energy metabolism. This is almost certainly an over-estimate, suggesting that the study population was in negative energy balance over the study period. Our study therefore suggests that despite its suit of integrated homeostatic responses, the confluence of low temperatures and resource limitation during winter places this edge-of-range primate close the threshold of what is energetically viable. It also provides a framework for quantitative models predicting the vulnerability of temperate primates to global change.

Biocuration - mapping resources and needs - Underlying Data

A variety of teams and individuals are involved in biocuration worldwide. However, they may not self-identify as biocurators per se, as they may be unaware of biocuration as a career path or because biocuration is only part of their role. The lack of a clear, up-to-date profile of biocuration creates challenges for organisations like ELIXIR, the ISB and GOBLET to systematically support biocurators and for biocurators themselves to develop their own careers. Therefore, the ELIXIR Training Platform launched an Implementation Study in order to i) identify communities of biocurators, ii) map the type of curation work being done, iii) assess biocuration training, and iv) draw a picture of biocuration career development. To achieve the goals of the study we carried out a global survey about the nature of biocuration work, the tools and resources that are used, training that has been received and additional training needs. To examine these topics in more detail we ran workshop-based discussions at ISB Biocuration Conference 2019 and the ELIXIR All Hands Meeting 2019. We also had guided conversations with selected people from the EMBL-European Bioinformatics Institute. The following files represent the underlying data for this study: <ul> <li> Pilot survey questions.docx (questionnaire sent to staff of Wellcome Genome Campus) </li> <li> Questions to guide conversations with biocurators.docx (conversation guide outlines the type of questions to be asked) </li> <li> Global survey questions.docx (globally disseminated questionnaire revised on the basis of the pilot survey) </li> <li> Themed summary of the responses given in the guided conversations – deidentified.docx (de-identified outcomes of the guided conversations) <ul> <li> Information that may lead to the identification of respondents has been redacted. </li> </ul> </li> <li> Global_survey_deidentified.xlsx (de-identified responses to the global survey) <ul> <li> This file includes de-identified responses to the survey questions. Responses that may lead to the identification of respondents have been redacted. Free text responses to questions 6, 14 and 15 have been categorised into tasks, topics and skills, respectively.   </li> </ul> </li> <li> Bar graphs of global survey.xlsx (quantitative responses to multiple choice questions in the global survey. For some questions, respondents could choose more than one option) </li> <li> Tools and resources.xlsx (Tools and resources used for biocuration work and listed by the respondents of the global survey) </li> <li> Biocuration training course list.xlsx (formal training courses listed by respondents of the global survey) </li> </ul>

Datasets of the study: "Describing variability in pig genes involved in coronavirus infections: towards a One Health perspective in conservation of animal genetic resources"

Dataset description Sequencing data (*.bam files) of four pig genes (ACE2, ANPEP, DPP4 and TMPRSS2) that can serve as receptors or protease for priming the infection of coronaviruses. The datasets are related to 22 European pig breeds and wild boars (Alentejana, AL; Apulo-Calabrese, AC; Basque, BA; Bísara, BI; Black Slavonian, BS; Casertana, CA; Cinta Senese, CS; Gascon, GA; Kr&scaron;kopolje, KR; Lithuanian Indigenous Wattle, LIW; Lithuanian White Old Type, LWOT; Majorcan Black, MB; Mora Romagnola, MR; Moravka, MO; Nero Siciliano, NS; Sarda, SA; Schwäbisch-Hällisches Schwein, SHS; Swallow-Bellied Mangalitsa, SBMA; Turopolje, TU; Italian Duroc, IDU; Italian Large White, ILW; Italian Landrace, ILA; Wild Boar, WB). This work took advantage of a study design developed within the Horizon 2020 TREASURE project. Each folder contains *.bam files and the related indexes *.bai. The name of the investigated breed and gene is part of the file name (e.g. ILW.ACE2.bam identifies the sequencing data related to the ACE2 gene in the Italian Large White pig breed). Details of sequencing and the bioinformatic pipeline are below reported. Sequencing data A total of 22 DNA pools were constructed from the European pig breeds and one DNA pool was constructed from European wild boars, including in each pool 30 or 35 individual DNA samples pooled at equimolar concentration. For the 22 DNA pools, libraries were prepared and fed into an Illumina HiSeq X Ten sequencer for paired-end sequencing, obtaining 150 bp length reads. The wild boar DNA pool was sequenced from 250 bp fragment libraries, with 100 bp long paired-end reads, on the BGISeq 500 platform, following the provider’s procedures. Data processing Reads that were obtained from the sequenced libraries were cleaned by removing adapter sequences and filtering out sequences presenting more than 10% unknown bases (N) and/or containing low-quality bases (Q ≤ 5) over 50% of the total sequenced bases. Then, filtered high-quality reads were mapped on the latest version of the Sus scrofa reference genome (Sscrofa11.1; https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/003/025/GCF_000003025.6_Sscrofa11.1/GCF_000003025.6_Sscrofa11.1_genomic.fna.gz) using the BWA-MEM algorithm v.0.7.17 and the parameters for paired-end data. Picard v.2.1.1 (https://broadinstitute.github.io/picard/) was used to remove duplicated reads. Whole sequence data are available in the EMBL-EBI European Nucleotide Archive (ENA) repository (http://www.ebi.ac.uk/ena), under the study accession PRJEB36830.  Reads covering the four genes (ACE2: NC_010461.5:12094853-12156275; ANPEP: NC_010449.5:55346083-55378881; DPP4: NC_010457.5:68655849-68748818; TMPRSS2: NC_010455.5:204871561-204907561) were extracted with samtools v.1.7 and exported as aligned, sorted and indexed *.bam files. Gene length includes UTRs and flanking regions of 5 kbp upstream [flanking (5’-UTR)] and downstream [flanking (3’-UTR)].

Ruffed Grouse Resource Selection Function and Survival Datasets

For overwintering species, individuals' ability to find refugia from inclement weather and predators likely confers strong fitness benefits. How animals use their environment can be mediated by their personality (e.g., risk-taking), but does personality mediate how overwintering species select refugia? Snow cover is a dynamic winter characteristic that can influence crypsis or provide below-the-snow refugia. We explored how wintering ruffed grouse (Bonasa umbellus) selected snow roosting sites, a behavior that reduces stress and cold exposure. We linked selection for ~700 roosts with survival of 42 grouse, and showed that grouse generally selected deeper snow and warmer areas. Grouse found in shallow snow were less likely to survive winter. However, individuals with personalities for selecting deep snow improved their survival, suggesting that demographic consequences of selecting winter refugia are mediated by differences in personality. Our study provides a crucial, and seldom addressed, link between personality in resource selection and resulting demographic consequences.

Habitat deterioration relaxes resource competition and sexual selection in the threespine stickleback

The operation of sexual selection depends on ecological conditions. Thus, changes in environmental conditions because of human activities can alter the strength and direction of sexual selection, with implications for evolutionary trajectories and the viability of populations. We show that aquatic algal blooms can relax the operation of sexual selection by influencing which males are available to attract females. This is by influencing the ability of males to maintain a resource needed in mate attraction. When we exposed two competing threespine stickleback males (Gasterosteus aculeatus), whose attractiveness to females was known, to either clear or algal-turbid water, nest abandonment was more common in clear water, and it was usually the unattractive male that abandoned his nest. In turbid water, on the other hand, nest abandonments were less common and when they occurred, the probability increased that the attractive male abandoned his nest, and that the unattractive male subsequently occupied it. This change in the composition of nesting males increased the mating success of unattractive males. Thus, our results reveal a new mechanism through which habitat deterioration can influence sexual selection, by altering success in the competition for a resource critical in mate attraction, a territory with a nest in this case. This could be a common mechanism, considering the prevalence of resource competition in mate choice systems. On a broader level, our results emphasise the importance of considering the impact of environmental changes on the outcome of resource competition when investigating the influence that environmental disturbances have on the operation of sexual selection and thereby on evolutionary processes and population dynamics.

Movement rules determine nomadic species' responses to resource supplementation and degradation

1. In environments that vary unpredictably, many animals are nomadic, moving in an irregular pattern that differs from year to year. Exploring the mechanisms of nomadic movement is needed to understand how animals survive in highly variable environments, and to predict behavioral and population responses to environmental change. 2. We developed a network model to identify plausible mechanisms of nomadic animal movement by comparing the performance of multiple movement rules along a continuum from nomadism to residency. Using simulations and analytical results, we explored how different types of habitat modifications (that augment or decrease resource availability) might affect the abundance and movement rates of animals following each of these rules. 3. Movement rules for which departure from patches depended on either resource availability or competition performed almost equally well and better than residency or uninformed movement under most conditions, even though animals using each rule moved at substantially different rates. Habitat modifications that stabilized resources, either by resource supplementation or degradation, eroded the benefits of informed nomadic movements, particularly for movements based on resource availability alone. 4. These results suggest that simple movement rules can explain nomadic animal movements and determine species' responses to environmental change. In particular, landscape stabilization and supplementation might be useful strategies for promoting populations of resident animals, but would be less beneficial for managing highly mobile species, many of which are threatened by habitat disruption and changes in climate.

Data from: Drought affects the coordination of belowground and aboveground resource-related traits in Solidago canadensis in China

Quantifying patterns of variation and coordination of plant functional traits can help to understand the mechanisms underlying both invasiveness and adaptation of plants. Little is known about the coordinated variations of performance and functional traits of different organs in invasive plants, especially in response to their adaptation to environmental stressors. To identify the responses of the invasive species Solidago canadensis to drought, 180 individuals were randomly collected from 15 populations and 212 ramets were replanted in a greenhouse to investigate both the response and coordination between root and leaf functional traits. Drought significantly decreased plant growth and most of the root and leaf functional traits, i.e. root length, surface area, volume and leaf size, number, and mass fraction, except for the root length ratio and root mass fraction. Phenotypic plasticity was higher in root traits than in leaf traits in response to drought, and populations did not differ significantly. The plasticity of most root functional traits, i.e., root length (RL), root surface area (RSA), root volume (RV), and root mass fraction (RMF), were significantly positively correlated with biomass between control and drought. However, the opposite was found for leaf functional traits, i.e. specific leaf area (SLA), leaf area ratio (LAR), and leaf mass fraction (LMF). Drought enhanced the relationship between root and leaf, i.e., 26 pairwise root-leaf traits were significantly correlated under drought, while only 15 pairwise root-leaf traits were significantly correlated under control conditions. Significant correlations were found between biomass and all measured functional traits except for leaf size. RV, root length ratio, RMF, total area of leaves, and LMF responded differently to water availability. These responses enable S. canadensis to cope with drought conditions and may help to explain the reason of the vast ecological amplitude of this species.

Resource allocation is determined by both parents and offspring in a burying beetle

Parents and offspring have different optima for the level of parental resource allocation and the timing of nutritional independence. Theoretical models assume that either parents or offspring control the allocation of resources within a brood; however, control may also be mutual. Here we investigate whether the resolution of parent-offspring conflict is biased towards cues from either the parents' or the offspring's behaviour, or whether the conflict is under mutual control. Importantly, we considered potential shifts in the power continuum over the entire period of juvenile dependency. The burying beetle Nicrophorus vespilloides parents provision food for the larvae, and the larvae solicit food from their parents with conspicuous begging displays. Both parental and larval behaviours change as larvae age. We repeatedly manipulated the age of the brood females care for, thereby creating mismatch between the age of the foster brood and expected age of the brood from the female parent's perspective, over the period of dependency in juvenile development. We found that females adjusted the total amount of provisioning based on the actual age of the brood. However, both the parent and the offspring influenced the levels of food provisioning, which followed neither the expected age of the brood from the parent's perspective nor offspring age. Our results suggest that there is mutual control over parental care, thus contradicting the dichotomous view of control over parental care. We suggest that the mutual influence of both parents and the offspring should be taken into account in development of future theory, as well as empirical studies.

Data from RACE: Resource Aware Cost-Efficient Scheduler for Cloud Fog Environment

The quality of human life increases with increased usage of the Internet of Things (IoT). However, this massive use of IoT produces a large amount of data which creates a problem for data storage and analysis. Cloud computing is used to solve such issues like storage and processing requirements for data generated by IoT. However, several applications like traffic control, health observation, and games, etc., are time-sensitive and need a quick response. The delay created by sending data to the Cloud and then returning the Server response to the user of such programs has an unintended impact. To overwhelmed these limitations, the Fog computing concept was launched in 2012. Fog computing is an elongation of Cloud computing in which user services are extended to networking devices. In recent times the Fog computing is considered as a favorable approach to cope with the delay-sensitive applications. Moreover, Fog computing in combination with the Cloud computing model can also provide promising solutions to deal with compute-intensive applications. The scheduling challenges faced by the Fog service provider are to fulfill user requests with the maximum resource utilization of Fog devices while reducing the monetary cost of Cloud resource usage. In this research, a resource-aware scheduler has been proposed to distribute the incoming application modules to Fog devices that maximize resource utilization at the Fog layer, reduces the monetary cost of using Cloud resources with minimum execution time of applications, and minimum bandwidth usage. The proposed scheduler Resource Aware Cost-Efficient Scheduler (RACE) consists of two algorithms: ModuleScheduler: which categorizes the incoming application modules according to their computation and bandwidth requirements. The ModuleScheduler also creates a prioritized list considering the categories of application modules. Compare Module: Finds the suitable Fog device for modules execution in the prioritized list. The proposed scheduler (RACE) schedule the modules at the Fog layer based on their computation requirement and bandwidth requirement until the devices at the Fog layer have enough CPU capacity to accommodate the modules.