Find research datasets worth reusing

Literature review on the main existing structures and systematic/academic initiatives for surveillance in the EU for zoonoses in the environment and the methods for surveillance of pathogens in the environment

The report to which this datasets refer to is based on two literature reviews <ol> <li>on the main existing structures and systematic/academic initiatives for surveillance in the EU for zoonoses in the environment, and</li> <li>on the methods for pathogen surveillance in the environment.</li> </ol> Concerning (i), the purpose of this literature review was to collect published information regarding surveillance in Europe that focuses on health hazards where environmental sampling is involved. It includes a review of study design and methodological approaches, including types of environmental samples, and methods to detect animal pathogens in the environment. Documents describing systematic, structured, or academic surveillance systems targeting zoonotic pathogens in the environment in Member States and neighbouring countries were searched. A list of target zoonotic pathogens has already been produced by EFSA and was included in the search strings in literature browsers. The publication search was done in the following databases: Biomedical databases (Embase) and Science databases (ISI web of Science, Pubmed). In addition to references retrieved directly from scientific browsers the literature cited to identify missing references was examined. A standardised data model was used to extract key information to characterise the surveillance systems (Annex 1), which is presented as an excel document, including the list of references and the vocabulary. Concerning (ii), the purpose of this literature review was to assess the published information on the methods applied to survey zoonotic pathogens or diseases using environmental protocols, i.e., non-invasive environmental samples. To achieve this goal, scientific databases such as Scopus, Pubmed and Web of Science (WOS) were used. The search method was limited to documents published between 2017 to 2022. Thereafter, inclusion/exclusion criteria were applied. A standardised data model was similarly used to extract key information from each document: target pathogen; type of samples collected (faecal, object surface…) and if it is an invasive or non-invasive collection method; sample collection methods; pre-analytical treatments; pathogen identification methods, and existence of quality controls. Data were collected at the assay level. The full text of all selected papers was read, and relevant information was extracted, summarised, and schematically outlined in tables in the form of one or multiple single-entry assays per reference. The standardized data model is presented in Annex 2, and it was divided into 6 parts: PART 1 – Target pathogen; PART 2 – Type of samples collected (faecal, object surface…) and whether it is an invasive or non-invasive collection method; PART 3 – Sample collection methods; PART 4 – Pre-analytical treatments; PART 5 – Pathogen identification methods; PART 6 – Quality controls. This annex is presented as an excel document, including the list of references.

Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis

Raw data set for npj Bioflims and Microbiome article: “Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis”

opencc-by-4.0Nov 2022View details →

Neutron Bragg edge imaging for strain characterization in powder bed additive manufacturing environments

The paper describes an approach to disentangle the recorded transmission spectrum obtained from Bragg edge imaging. The transmission spectrum of the samples embedded in their corresponding powder was successfully extracted, proven by the coinciding strain maps produced. The horizontal profiles from the maps were plotted together with neutron diffraction results and they agree very well. The uploaded data were the raw data obtained from Bragg edge imaging and neutron diffraction experiments used to construct the strain maps and plots shown in the paper.

opencc-zeroDec 2022View details →

Smart5Grid solutions for enhanced TSO grid observability and manageability in massive RES penetration environment

This work focuses on two Use Cases (UCs) of the Smart5Grid project (UC3 and UC4) and reports the raw data of their corresponding Network Applications: Run Time Energy Production Monitoring Predictive Maintenance (Enabler) for UC3 as well as virtual Phasor Data Concentrator (vPDC), Wide Area Monitoring (WAM), and Advisory (Enabler) for UC4. These Network Applications are developed by means of Grid Protection Alliance (GPA) open source software and GSF open source library. Another two GPA open source projects used for both UCs development are openPDC and openHistorian. Microsoft Visual Studio 2022 is the coding environment while C# и JavaScript are the programming languages engaged in the Use Cases 3&4 NetApp development process. Correspondingly, the services for both UCs are placed in Docker images that are used in Helm charts. These Helm charts are used to install the services in Kubernetes cluster, which runs Docker containers of the services in its cluster. Detailed video demonstrations of both use cases' services are referred to in the results section of the associated manuscript. Two reproducible and reusable raw data timeseries are shared: (1) realtime photovoltaic production monitoring using the UC3 NetApps (demo of distributed renewable resources monitoring), and (2) realtime virtual Phasor Data Concentrator as UC4 demonstrator(of Wide Area Monitoring of an interconnected power system via 400 kV tie line between Bulgaria and Greece). Both demostrators run on an innovative Smart5Grid Open Experimentation Platform building on 5G PPP and detailed in the associated article.

SIMCor - R-Statistical Environment embedded in the SIMCor Virtual Research Environment

Using RStudio, the capabilities of running statistical evaluations in a standardised manner directly on the SIMCor Virtual Research Environment (VRE) has been realised. Via a web frontend, scripts written in the R programming language can be directly evaluated on the data, such as the virtual cohorts, available at the VRE.

Learning Analytics for Personalized Learning Environments: Visualizing Journal Publication Trends

Data collected from Scopus database for the "Learning Analytics for Personalized Learning Environments: Visualizing Journal Publication Trends" entitled research.

opencc-zeroDec 2022View details →

Active and low-cost hyperspectral imaging for spectral analysis in low lighting environment

Hyperspectral imaging can capture information beyond conventional RGB cameras; thus, it has many applications, such as material identification and spectral analysis. However, like many camera systems, most of the existing hyperspectral cameras are still passive imaging systems: they require external light sources to illuminate the objects to capture the spectral intensity. As a result, the collected images highly depend on the environment lighting, and the imaging system cannot function in a dark or low-lighting environment. This work develops a prototype system for active hyperspectral imaging, which actively emits different single-wavelength lights at different frequencies when imaging. This concept has several advantages: first, using the controlled lighting, the magnitude of the individual bands is normalized to extract reflectance information; second, the system is capable of collecting information at the desired spectral range by tailoring the light sources; third, an active system is mechanically easier to make, since it does not require complex band filters as used in passive systems; last, such a system may work under low light or dark environments, which greatly facilitate underground/subsurface sensing applications such as borehole based mining exploration. This prototype is achieved by using an array of low-cost and single-wavelength LED (Light Emitting Diode) lights, a remote control module controlling the LED illuminator, and the shutter of a full spectrum camera. We demonstrate that such design is feasible and could yield informative hyperspectral images for spectral analysis and machine learning-based object identification in low light or dark environments, having great potential to benefit both the academic and industry such as in geochemistry, earth science, subsurface energy, and mining.

Switchgrass sward establishment selection is across multiple environments and fertilization levels

Background: Strong selection can occur during switchgrass sward establishment. Differences in establishment selection due to environment or management could provide information on genotype‐by‐environment variation and could influence strategies for breeding perennial grasses. Methods: Leaf samples were collected before sward establishment and from 3‐year‐old swards for two breeding groups (lowland and hybrid) at three locations. Within two locations, samples were collected from paired fertilized (110 kg ha-1 N) and unfertilized plots. Allele frequencies from pooled DNA samples were studied through multivariate analysis of variance, genomewide trait predictions (heading date and winter survivorship), and genomically estimated breeding values (GEBVs) for individual sward survival within an independent data set. Results: This study found only minor variations in selection due to location or management. Predicted heading dates of the hybrid population had significant changes due to fertilization and location. There were strong correlations among sward establishment survival GEBVs between growing environments (hybrid r = 0.77; gulf r = 0.97). Interestingly, this study found a small number of genotypes that were over‐represented in established swards across all growing environments. Conclusions: This study reinforces a prior report of selection during sward establishment and indicates that only a small degree of establishment selection is location‐specific within these diverse growing conditions.

IDE Interactions of Novices Transitioning Between Programming Environments

Novices in introductory programming courses typically learn the fundamentals of programming using one of a wide of programming environments. These vary greatly in terms of the mechanisms they employ to assist programmers, including their approaches to compilation and error message presentation. It is yet to be established which, if any, of these mechanisms are more beneficial for learning. In this study, we utilize Java programming process data to investigate the interaction between novices and two different versions of the BlueJ pedagogical IDE, which differ substantially in terms of compilation mechanism and error message presentation. Specifically, we compare novices that used both BlueJ 3 and BlueJ 4 with those who exclusively used either and the effects of the order in which they transition between BlueJ versions. We find substantial differences between different cohorts in terms of error messages and compilation which provides evidence that programming environments play an important part in influencing the programming practices of novices. This work supports the hypothesis that the choice of programming environment significantly affects user behavior with respect to specific programming interactions and therefore it is reasonable to expect a difference in how these environments affect learning.

Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback

Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here we integrate whole-genome-sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome-wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP-based heritability of all measured traits was high (h2 = 0.42 – 0.65), indicating adaptive potential for all traits. Whilst environment-association analyses identified thousands of loci putatively involved in selection, related to genes linked to neuron development and protein phosphorylation, only loci linked to pelvic spine length were concurrently linked to environmental variation (water depth) – supporting the conclusion that divergence in pelvic spine length occurred in face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.

Conservation measures or hotspots of disease transmission? Agri-environment schemes can reduce disease prevalence in pollinator communities

Insects are under pressure from agricultural intensification. To protect pollinators, conservation measures such as the EU agri-environment schemes (AES) promote planting wildflowers along fields. However, this can potentially alter disease ecology by serving as transmission hubs or by diluting infections. We tested this by measuring plant-pollinator interactions and virus infections (DWV-A, DWV-B and ABPV) across pollinator communities in agricultural landscapes over a year. AES had a direct effect on DWV-B, reducing prevalence and load in honeybees, with a tentative general dilution effect on load in early summer. DWV-A prevalence was reduced both under AES and with increasing niche overlap between competent hosts, likely via a dilution effect. In contrast, AES had no impact on ABPV; its prevalence was driven by the proportion of bumblebees in the community. Epidemiological differences were also reflected in the virus phylogenies, with DWV-B showing recent rapid expansion, while DWV-A and ABPV showed slower growth rates and geographic population structure. Phylogenies indicate that all three viruses freely circulate across their host populations. Our study illustrates how complex interactions between environmental, ecological and evolutionary factors may influence wildlife disease dynamics. Supporting pollinator nutrition can mitigate the transmission of important bee diseases, providing an unexpected boost to pollinator conservation.

Influence of sedimentary environment evolution on fingerprint characteristics of methane isotopes: A case study from Hangzhou Bay

To better understand the depositional constraints on the fingerprint characteristics of methane isotopes, we present a set of carbon/hydrogen isotopic data for CH4, CO2, pore water, carbonates, and total organic carbon (TOC) along a 70-m sedimentary core from Hangzhou Bay, China. The sedimentary facies (Units I, II, and III from upper to bottom) suggested depositional environments of the present estuary, shallow marine, and floodplain-estuary. The values of δDCH4 displayed similar trends with those of δDH2O and Cl- concentrations along the depth profiles. The values of δ13CCH4 generally synchronously changed with those of δ13CCO2. The variation trends of δ13CCH4 and δ13CCO2 were the same with δ13Ccarbonate from 10 m to 70 m depth but decoupled above 10 m. Calculations suggested that about 86% of methane was produced through the CO2 reduction pathway. In this pathway, the hydrogen in CH4 is from ambient water, while the carbon is from dissolved inorganic carbon. In our study, the low δDCH4 below 44.5 m corresponded to low δDH2O and low salinity during the cold and low-sea-level period. The values of δ13CCH4 in Units II and III were correlated with the δ13Ccarbonates, which is related to the sedimentary processes. But decoupling of low values of δ13CCH4 and δ13CCO2 from δ13Ccarbonates in Unit I may be related to preferential microbial consumption of labile compounds with light carbon isotopic compositions, such as lipids. In short, the variations of the stable carbon and hydrogen isotopic compositions of CH4 were largely related to sedimentary processes.

opencc-zeroDec 2022View details →

On the fast track: Hybrids adapt more rapidly than parental populations in a novel environment

Rates of hybridization are predicted to increase due to climate change and human activity that cause redistribution of species and bring previously isolated populations into contact. At the same time, climate change leads to rapid changes in the environment, requiring populations to adapt rapidly in order to survive. A few empirical cases suggest hybridization can facilitate adaptation despite its potential for incompatibilities and deleterious fitness consequences. Here we use simulations and Fisher's Geometric model to evaluate the conditions and time frame of adaptation via hybridization in both diploids and haplodiploids. We find that hybrids adapt faster to new environments compared to parental populations in nearly all simulated scenarios, generating a fitness advantage that can offset intrinsic incompatibilities and last for tens of generations, regardless of whether the population was diploid or haplodiploid. Our results highlight the creative role of hybridization and suggest that hybridization may help contemporary populations adapt to the changing climate. However, adaptation by hybrids may well happen at the cost of reduced biodiversity, if previously isolated lineages collapse into one.

Reproducing during Heat Waves: Influence of Juvenile and Adult Environment on Fecundity of a Pest Mite and its Predator

Dataset of the results in the article: Reproducing during Heat Waves: Influence of Juvenile and Adult Environment on Fecundity of a Pest Mite and its Predator This research was funded by the Austrian Science Fund (FWF).

Internal exposure of Flemish teenagers to environmental pollutants: results of the Flemish Environment and Health Study

Supplementary Information of manuscript "Internal exposure of Flemish teenagers to environmental pollutants: results of the Flemish Environment and Health Study 2017-2018 (FLEHS IV) "

opencc-by-4.0Feb 2023View details →

Data from: How science communications can help build societal perceptions of invasive alien species and their impacts on the environment

In this study, we investigated the reported beneficial aspects of the invasive alien plant species (IAPS) and argued that, over time and space, the detrimental impacts of the IAS might endanger sustainable livelihoods. The data set contains the following files: Data_S1.xlsx: The file contains details of 154 literature reports. From each paper, we extracted IAPS names (both as reported and standardized), taxonomic information (family and taxon rank), year, country, the scale of observation, and reported beneficial impacts. The beneficial impacts were further categorized into 13 use categories at TDWG (Taxonomic Databases Working Group) Level-1 states (in binary format - 1 indicates the IAPS use and 0 indicates not in use for the individual category). The Metadata_S1.pdf file contains detailed information on preparing literature records for data extraction, the data extraction process, and data organization.

opencc-by-4.0Feb 2023View details →

data set for Design of architectural environment integration of cyber-physical systems based on image segmentation and retrieval technology

This data set is used to implement the project  Design of architectural environment integration of cyber-physical systems based on image segmentation and retrieval technology

Handling Dynamic Environment Changes for Behavior-Based User Authentication

Description: This environment-independent user authentication dataset is from our MASS 2020 paper: Towards Environment-independent Behavior-based User Authentication Using WiFi. This dataset contains the physiological characteristics captured by WiFi from 10 participants for 10 different activities. Each participant performs 20 rounds for each activity. The experiments are conducted in two different environments, the campus office, and the home apartment. The system performance is tested on the cross-environment scenarios (training in one environment and testing in another environment). Note: The MASS 2020 paper is based on our MobiHoc 2017 paper, Smart User Authentication through Actuation of Daily Activities Leveraging WiFi-enabled IoT. The MobiHoc 2017 work focused on user authentication using CSI extracted from human activity while the MASS 2020 work focused on the domain adaptation of user authentication using activity CSI. The dataset of our MobiHoc 2017 work is also published: <a href="https://zenodo.org/record/7750976#.ZBfTZ3bMKUk">https://zenodo.org/record/7750976#.ZBfTZ3bMKUk</a>   Format: .dat format Section 1: Device Configuration <ul> <li>Two commercial laptops, Dell E6430, as transmitter and receiver. Run with a Linux 14.04 operating system with 4.2.0 kernel. Equipped with 3 MINI PCI-E internal antennas. </li> <li>Intel 5300 network interface card (NIC) for CSI collection. The detail information regarding the CSI tool can be found at <a href="https://dhalperi.github.io/linux-80211n-csitool/faq.html">https://dhalperi.github.io/linux-80211n-csitool/faq.html</a>.</li> <li>WiFi packet transmission is set to 1000 pkts/s</li> </ul> Section 2: Data Format We provide raw data received by the CSI tool. The data files are saved in the dat format. The details are shown in the following: <ol> <li>10 participants are included in two different experiments.</li> <li>Each participant performed 20 rounds for each activity.</li> <li>The dataset file name is presented as "User_Day_Action_Location". The detailed information as: <ul> <li>User: The participants that CSI was collected from.</li> <li>Day: The date this data was collected. </li> <li>Action: The specific activity performed.</li> <li>Location: The specific location the experiment was conducted.</li> </ul> </li> </ol> Section 3: Experimental Setups There are two experiment setups for our data collection. An image of the experimental setup and the illustration of activities from two different environments is included in the dataset. Each activity was performed in a designated location. In each activity location, the specific activity was conducted in 4 different proximate locations at least one foot away from each other.  <ol> <li>Residential Apartment <ul> <li>Environment: The experiments are conducted in a residential apartment with a size 33ft × 17ft.</li> <li>Participant: 10 users are students from Rutgers University (aged from 20 to 30).</li> <li>Activity: 7 activities were performed. <table> <caption>Detailed Activities Performed in Apartment</caption> <tbody> <tr> <td>Code</td> <td>Activity</td> </tr> <tr> <td>      A→B</td> <td>Walking (trajectory 1)</td> </tr> <tr> <td>      B→C</td> <td>Walking (trajectory 2)</td> </tr> <tr> <td>         B</td> <td>Picking up a remote control</td> </tr> <tr> <td>         C</td> <td>Sitting in a chair </td> </tr> <tr> <td>         D</td> <td>Exercising</td> </tr> <tr> <td>         E</td> <td>Operating on the oven</td> </tr> <tr> <td>         F</td> <td>Using the stove</td> </tr> </tbody> </table>   </li> </ul> </li> <li>Office  <ul> <li>Environment: The experiments are conducted in an office with a size 21ft × 12ft.</li> <li>Participant: 5 users are students from Rutgers University (aged from 20 to 30).</li> <li>Activity: 3 activities were performed. <table> <caption>Detailed Activities Performed in Office</caption> <tbody> <tr> <td>Code</td> <td>Activity</td> </tr> <tr> <td>      G</td> <td>Sitting in a seat</td> </tr> <tr> <td>      H</td> <td>Stretching the body</td> </tr> <tr> <td>       I</td> <td>Typing on a keyboard</td> </tr> </tbody> </table> </li> </ul> </li> </ol>   Section 4: Data Description We separate our raw data into different folders based on different environment types. In each environment type, data are further distributed in terms of date. Each file includes all data from three internal antennas. All data files are in .dat format. We also provide Matlab scripts for CSI analysis and visualization. The following variables can be revealed from the codes: <ol> <li>CSI: This is the Channel State Information (CSI) received from one receiver antenna. It describes the signal propagation from the transmitter to the receiver, and it is very sensitive to the impact of environmental changes. Each data reveals CSI from 30 subcarriers. </li> <li>Relative Phase: Relative Phase is a measurement to describe the degree of synchronization between data received from different antennas. It can be used to determine the phase offset for further signal preprocessing.</li> <li>Time: This is the time interval in which the data file contains. It measures time by the number of seconds. It can be used to determine how long the signal has been received.</li> </ol> Section 5: Codes <ul> <li>analysis_spectrogram.m: load a .dat file and extract all data by Data description(I.e, CSI, and Relative Phase).</li> </ul> Section 6: Citations If your paper is related to our works, please cite our papers as follows. <a href="https://ieeexplore.ieee.org/document/9356038">https://ieeexplore.ieee.org/document/9356038</a> C. Shi, J. Liu, N. Borodinov, B. Leao and Y. Chen, "Towards Environment-independent Behavior-based User Authentication Using WiFi," 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Delhi, India, 2020, pp. 666-674, doi: 10.1109/MASS50613.2020.00086 Bibtex: @INPROCEEDINGS{9356038,   author={Shi, Cong and Liu, Jian and Borodinov, Nick and Leao, Bruno and Chen, Yingying},   booktitle={2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)},    title={Towards Environment-independent Behavior-based User Authentication Using WiFi},    year={2020},   volume={},   number={},   pages={666-674},   doi={10.1109/MASS50613.2020.00086}}   The current version of the dataset is shrunk due to its size. If you wish to acquire the full version or you have any questions regarding the dataset, contact us by email:  cl1361@scarletmail.rutgers.edu.

opencc-zeroFeb 2023View details →

Data for: Local adaptation of switchgrass drives trait relations to yield and differential responses to climate and soil environments

Switchgrass, a potential biofuel crop, is a genetically diverse species with phenotypic plasticity enabling it to grow in a range of environments. Two primary divergent ecotypes, uplands and lowlands, exhibit trait combinations representative of acquisitive and conservative growth allocation strategies, respectively. Whether these ecotypes respond differently to various types of environmental drivers remains unclear but is crucial to understanding how switchgrass varieties will respond to climate change. We grew two upland, two lowland, and two intermediate/hybrid cultivars of switchgrass at three sites along a latitudinal gradient in the central United States. Over a 4-year period, we measured plant functional traits and biomass yields and evaluated genotype-by-environment (G´E) interaction effects by analyzing switchgrass responses to soil and climate variables. We found substantial evidence of G´E interactions on biomass yield, primarily due to deviations in the response of the southern lowland cultivar Alamo, which produced more biomass in hotter and drier environments relative to other cultivars. While lowland cultivars had the highest potential for yield, their yields were more variable year-to-year compared to other cultivars, suggesting greater sensitivity to environmental perturbations. Models comparing soil and climate principal components as explanatory variables revealed soil properties, especially nutrients, to be most effective at predicting switchgrass biomass yield. Also, conservative plant traits such as high stem mass and tiller height became increasingly positively associated with biomass yield at lower latitudes where the climate is hotter and drier, regardless of ecotype. Lowland cultivars, however, showed a greater predisposition to exhibit these conservative traits. These results suggest switchgrass trait allocation trade-offs that prioritize aboveground biomass production are more tightly associated in hot, dry environments and that lowland cultivars may exhibit a more specialist life strategy relative to other cultivars. Altogether, this research provides essential knowledge for improving the viability of switchgrass as a biofuel crop.