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Prospective Life Cycle Inventory Datasets for conventional and hybrid electric aircraft technologies
<p><strong><em>Supplementary Material - Filled LCI data collection schemes </em></strong>from the publication <em><strong>"Prospective Life Cycle Inventory Datasets for conventional and hybrid electric aircraft technologies"</strong></em>. This repository includes LCI data for three time horizons; short-term, medium-term, and long-term.</p> <p>In the <strong>short-term time horizon</strong>, LCI data for the following technologies distinguished according to two different configurations (conventional and GT-bat) are covered in this repository:</p> <ul> <li>Airframe conventional (GENESIS_LCI_airframe_short-term_conventional_v01.xlsx)</li> <li>Airframe GT-bat (GENESIS_LCI_airframe_short-term_GT-bat_v01.xlsx)</li> <li>Airport (GENESIS_LCI_airport_short-term_v01.xlsx)</li> <li>Battery EOL (GENESIS_LCI_battery_EoL_Li-ion_short-term_GT-bat_v01.xlsx)</li> <li>Battery Li-ion (GENESIS_LCI_battery_Li-ion_short-term_GT-bat_v01.xlsx)</li> <li>Battery charging station (GENESIS_LCI_battery-charging-station_short-term_v01.xlsx)</li> <li>Power electronics and drives (GENESIS_LCI_power_elec_drives_short-term_v01.xlsx)</li> <li>Powerplant conventional (GENESIS_LCI_powerplant_short-term_conventional_v01.xlsx)</li> <li>Powerplant GT-bat (GENESIS_LCI_powerplant_short-term_GT-bat_v01.xlsx)</li> <li>SAF (GENESIS_LCI_SAF_short-term_v01.xlsx)</li> </ul> <p>In the <strong>medium-term time horizon</strong>, LCI data for the following technologies distinguished according to three different configurations (conventional, GT-bat, and PEMFC-bat) are covered in this repository:</p> <ul> <li>Airframe conventional (GENESIS_LCI_airframe_medium-term_conventional_v01.xlsx)</li> <li>Airframe GT-bat (GENESIS_LCI_airframe_medium-term_conventional_v01.xlsx)</li> <li>Airframe PEMFC-bat (GENESIS_LCI_airframe_medium-term_PEMFC-bat_v01.xlsx)</li> <li>Airport (GENESIS_LCI_airport_medium-term_v01.xlsx)</li> <li>Battery EOL Li-S GT-bat (GENESIS_LCI_battery_EoL_Li-S_medium-term_GT-bat_v01.xlsx)</li> <li>Battery EOL Li-S PEMFC-bat (GENESIS_LCI_battery_EoL_Li-S_medium-term_PEMFC-bat_v01.xlsx)</li> <li>Battery Li-S GT-bat (GENESIS_LCI_battery_Li-S_medium-term_GT-bat_v01.xlsx)</li> <li>Battery Li-S PEMFC-bat (GENESIS_LCI_battery_Li-S_medium-term_PEMFC-bat_v01.xlsx)</li> <li>Battery charging station (GENESIS_LCI_battery-charging-station_medium-term_v01.xlsx)</li> <li>Fuel cell PEM (GENESIS_LCI_fuel cell_PEM_medium-term_PEMFC-bat_v01.xlsx)</li> <li>H<sub>2</sub> onboard storage (GENESIS_LCI_H2_onboard_storage_medium-term_PEMFC_v01.xlsx)</li> <li>Power electronics and drives GT-bat (GENESIS_LCI_power_elec_drives_medium-term_GT-bat_v01.xlsx)</li> <li>Power electronics and drives PEMFC-bat (GENESIS_LCI_power_elec_drives_medium-term_PEMFC-bat_v01.xlsx)</li> <li>Powerplant conventional (GENESIS_LCI_powerplant_medium-term_conventional_v01.xlsx)</li> <li>Powerplant GT-bat (GENESIS_LCI_powerplant_medium-term_GT-bat_v01.xlsx)</li> <li>Powerplant PEMFC-bat (GENESIS_LCI_powerplant_medium-term_PEMFC-bat_v01.xlsx)</li> </ul> <p>In the <strong>long-term time horizon</strong>, LCI data for the following technologies distinguished according to three different configurations (conventional, PEMFC-bat, and SOFC-bat) are covered in this repository:</p> <ul> <li>Airframe conventional (GENESIS_LCI_airframe_long-term_conventional_v01.xlsx)</li> <li>Airframe PEMFC-bat (GENESIS_LCI_airframe_long-term_PEMFC-bat_v01.xlsx)</li> <li>Airframe SOFC-bat (GENESIS_LCI_airframe_long-term_SOFC-bat_v01.xlsx)</li> <li>Airport (GENESIS_LCI_airport_long-term_v01.xlsx)</li> <li>Battery EOL Li-Air PEMFC-bat (GENESIS_LCI_battery_EoL_Li-air_long-term_PEMFC-bat_v01.xlsx)</li> <li>Battery EOL Li-Air SOFC-bat (GENESIS_LCI_battery_EoL_Li-air_long-term_SOFC-bat_v01.xlsx)</li> <li>Battery Li-Air PEMFC-bat (GENESIS_LCI_battery_Li-air_long-term_PEMFC-bat_v01.xlsx)</li> <li>Battery Li-Air SOFC-bat (GENESIS_LCI_battery_Li-air_long-term_SOFC-bat_v01.xlsx)</li> <li>Battery charging station (GENESIS_LCI_battery-charging-station_long-term_v01.xlsx)</li> <li>Fuel cell PEM (GENESIS_LCI_fuel cell_PEM_long-term_PEMFC-bat_v01.xlsx)</li> <li>Fuel cell SO (GENESIS_LCI_fuel cell_SO_long-term_SOFC-bat_v01.xlsx)</li> <li>H<sub>2</sub> onboard storage PEMFC-bat (GENESIS_LCI_H2_onboard_storage_long-term_PEMFC-bat_v01.xlsx)</li> <li>H<sub>2</sub> onboard storage SOFC-bat (GENESIS_LCI_H2_onboard_storage_long-term_SOFC-bat_v01.xlsx)</li> <li>Power electronics and drives PEMFC-bat (GENESIS_LCI_power_elec_drives_long-term_PEMFC-bat_v01.xlsx)</li> <li>Power electronics and drives SOFC-bat (GENESIS_LCI_power_elec_drives_long-term_SOFC-bat_v01.xlsx)</li> <li>Powerplant conventional (GENESIS_LCI_powerplant_long-term_conventional_v01.xlsx)</li> <li>Powerplant PEMFC-bat (GENESIS_LCI_powerplant_long-term_PEMFC-bat_v01.xlsx)</li> <li>Powerplant SOFC-bat (GENESIS_LCI_powerplant_long-term_SOFC-bat_v01.xlsx)</li> </ul> <p>Additionally, the following file is used for <strong>all time horizons</strong>:</p> <ul> <li>H<sub>2</sub> production and supply (GENESIS_LCI_H2_production_&_supply_v01.xlsx)</li> </ul>
Data Repository Accompanying "Controllable single Cooper pair splitting in hybrid quantum dot systems"
<p>Code and datasets associated with the manuscript " Controllable single Cooper pair splitting in hybrid quantum dot systems". With the code and data included here, all necessary fits and analysis can be conducted to produce the figures given in the manuscript and its supplementary material. The only exception is that we include the results of the quantum dot stability diagram simulation, however this simulation involves no new physics and the procedure is described in detail in the manuscript's supplementary information.</p>
EnergyPROSPECTS Energy Citizenship Factsheet Series, Part 5: Aspects of ENCI I.: Hybridity, private/public, passive/active forms
<p>This document is Part 5 of the EnergyPROSPECTS Factsheet Series. We have created the Series to publish the results of a mapping of energy citizenship in Europe, along with the first stage of our analysis of the respective data. The EnergyPROSPECTS consortium mapped 596 cases of energy citizenship (ENCI) between November 2020 and May 2021 using desk research, collecting data on many aspects of the cases. Although the analysis is a work in progress, we believe it is important to share our data and, through doing this, contribute to the understanding of energy citizenship in Europe.</p> <p>EnergyPROSPECTS (PROactive Strategies and Policies for Energy Citizenship Transformation), a H2020 project between 2021-2024, works with a critical understanding of energy citizenship that is grounded in state-of-the-art social sciences and humanities (SSH) insights.</p>
Predictive nano-QSAR modeling of the cytotoxicity using epithelial cells obtained from Chinese hamster ovary (CHO-K1 cell line) for hybrid TiO2-based nanomaterials
<p>Results obtained from developed model indicated that the cytotoxicity of hybrid TiO2-based nanomaterials is related to additive electronegativity (χmix) of studied nanomaterials that are indirectly related to the electron generation and ROS formation. ROS production is the most common toxicity cause as discussed in the literature in the case of nanoparticles. The high efficiency of surface modified TiO2-based semiconductors can be attributed to the involvement of TiO2 band gap (Eg) excitation and absence of noble metals at the TiO2 surface. It can be expected that noble metals (i.e. Pd/Pt) may trap holes (h+), at the same time photo-generated electrons can be then transferred from the valence band to the conduction band of TiO2 and to its surface where redox processes were initiated. Thus, observed reduction of the electron–hole pair recombination influences the reactive oxygen species (ROS) formation and the photocatalytic redox process initiation.</p> <p>Since the electronegativity was positively correlated with the cytotoxicity it can be expected that some ions are released from the TiO2 surface easier than others.</p>
Data from: Genomic analysis reveals limited hybridization among three giraffe species in Kenya
<p>The data deposited here was generated by and reported in Coimbra <em>et al.</em> (2023).</p> <p><em>SNP calling and linkage pruning</em></p> <ul> <li><strong>snp_calling_per_species.tar.gz:</strong> includes a genotype likelihoods (GL) file estimated with ANGSD for each giraffe species.</li> <li><strong>sampled_ld.tar.gz:</strong> contains a random sample of estimated pairwise <em>r<sup>2</sup></em> values for each species used to fit linkage disequilibrium (LD) decay curves.</li> <li><strong>ld_pruned_snps.tar.gz:</strong> contains an LD-pruned ANGSD GL file per species.</li> <li><strong>snp_calling_combined.tar.gz:</strong> includes a single LD-pruned ANGSD GL file comprising all sampled individuals of the three giraffe species analyzed in this study.</li> </ul> <p><em>Relatedness</em></p> <ul> <li><strong>relatedness.tar.gz:</strong> contains the input and output files used with NGSremix to estimate relatedness among giraffe in the dataset.</li> <li><strong>snp_calling_combined_unrelated.tar.gz:</strong> includes a single LD-pruned ANGSD GL file comprising all unrelated individuals of the three giraffe species analyzed in this study.</li> </ul> <p><em>Population structure and admixture</em></p> <ul> <li><strong>pcangsd.tar.gz:</strong> contains the covariance matrix generated by PCAngsd.</li> <li><strong>ngsadmix.tar.gz:</strong> includes run likelihood lists for each K value ranging from 1 to 11, as well as the admixture proportions (stored in '.qopt' files) inferred from the run with the highest log-likelihood for each K in NGSadmix.</li> <li><strong>evaladmix.tar.gz:</strong> contains the pairwise correlation of residuals between individuals estimated with evalAdmix for the NGSadmix runs with the highest log-likelihood run for each K.</li> </ul> <p><em>SNP-based phylogenomic inference</em></p> <ul> <li><strong>snp_phylogeny.tar.gz:</strong> contains the input PHYLIP file and the IQ-TREE output tree and log files.</li> </ul> <p><em>Phylogeny of mitochondrial genomes</em></p> <ul> <li><strong>mtdna_phylogeny.tar.gz:</strong> includes the 13 mitochondrial protein-coding gene alignments, the partitions file, and the IQ-TREE output tree and log files.</li> </ul> <p><em>Inference of migration events</em></p> <ul> <li><strong>admixture_graphs.tar.gz:</strong> contains the TreeMix / OrientAGraph input file ('treemix.frq.strat.gz'), the output files for all TreeMix and OrientAGraph runs, and the OptM summary table of TreeMix runs ('optm.tsv').</li> </ul> <p><em>Test for introgression</em></p> <ul> <li><strong>dsuite_introgression.tar.gz:</strong> includes the input VCF, the admixture graph topology reconstructed by OrientAGraph, and the Dsuite output files for the estimation of Patterson's D, f4-ratio, and f-branch statistics.</li> </ul> <p><em>Contemporary migration rates</em></p> <ul> <li><strong>ba3-snps.tar.gz:</strong> contains the input and output files for the BA3-SNPs-autotune and BA3-SNPs runs.</li> </ul> <p><em>Demographic reconstruction</em></p> <ul> <li><strong>demographic_inference.tar.gz:</strong> includes the SFS files generated with ANGSD and realSFS and the StairwayPlot2 blueprint and output files.</li> </ul> <p>Other:</p> <ul> <li><strong>metadata.csv:</strong> a companion file containing sample information used in conjunction with R scripts to plot the figures in the paper.</li> </ul>
Plethodon hybrid zone capture-mark-recapture survey plots at the Coweeta Hyrdologic Laboratory, Otto, NC.
A major goal of the Coweeta LTER is to understand the interactions between climate and land use on the ecology of southern Appalachia biota. Southern Appalachia is the global hotspot for salamander diversity, with most of that diversity situated at mid and upper elevations of mountains where species are functionally trapped by their dependence of a narrow, cool climatic zone. The ranges of the two terrestrial salamander species, Plethodon teyahalee (southern Appalachian salamander) and Plethodon shermani (red-legged salamander) meet at a unique hybrid zone at the Coweeta LTER in Macon County, NC. The hybrid zone is unique because it appears to be shifting up in elevation, possibly due to climate change. This research will be situated in the hybrid zone of these two species to assess the differential effects of climate change and land use on both species. To evaluate the effects of climate on the local ecology of salamanders, we will conduct an intensive mark-recapture study to measure surface activity on 6 plots distributed in pairs at 3 elevations that provide a range of warmer to cooler climates. Every two weeks, each plot is searched for 30 min by two investigators using head lamps. Animals are hand captured, identified to species, scored for color and patterning, measured, and marked using a unique combination of visible implant elastomers (VIE). This will enable us to estimate individual capture probabilities and rates of temporary surface emigration (an indication of avoidance of climatically unsuitable conditions).
"Planning Hybrid Driving-Stepping Locomotion for Ground Robots in Challenging Environments" video material
<p>"Planning Hybrid Driving-Stepping Locomotion for Ground Robots in Challenging Environments" video material</p>
Influence of He$^{++}$ and shock geometry on interplanetary shocks in the solar wind: 2D Hybrid simulations
<p>After protons, alpha particles (He$^{++}$) are the most important ion species in the solar wind, constituting typically about 5\% of the total ion number density. Due to their different charge-to-mass ratio protons and He$^{++}$ particles are accelerated differently when they cross the electrostatic potential in a collisionless shock. This behavior can produce changes in the velocity distribution function (VDF) for both species generating anisotropy in the temperature which is considered to be the energy source for various phenomena such as ion cyclotron and mirror mode waves. How these changes in temperature anisotropy and shock structure depend on the percentage of He$^{++}$ particles and the geometry of the shock is not completely understood. In this paper we have performed various 2D local hybrid simulations (particle ions, massless fluid electrons) with similar characteristics (e.g., Mach number) to interplanetary shocks for both quasi-parallel and quasi-perpendicular geometries self-consistently including different percentages of He$^{++}$ particles. We have found changes in the shock transition behavior as well as in the temperature anisotropy as functions of both the shock geometry and He$^{++}$ particle abundance: The change of the initial $\theta_{Bn}$ leads to variations of the efficiency with which particles can escape to the upstream region facilitating or not the formation of compressive structures in the magnetic field that will produce increments in perpendicular temperature. The regions where both temperature anisotropy and compressive fluctuations appear tend to be more extended and reach higher values as the He$^{++}$ content in the simulations increases.</p> <p> </p>
Ascorbic Acid Hydrolysate of Kappaphycus alvarezii as an Effective Biostimulant for Growth and Crop Yield Improvement of Hybrid Maize in Vietnam
<p>The study<strong> </strong>researches on plant production with particular attention to the environment. It first mentions the usage of ascorbic acid for depolymerization of carrageenans from dry <em>K. alvarezii</em> biomass, its hydrolysate’ characteristics, and its positive influence on the hybrid maize crop in Vietnam. The study is one of the very fewer studies evaluating the plant-growth promoting activity of oligocarrageenans on maize crops. The results of the study introduce an oligocarrageenans-rich biostimulant prepared by acid hydrolysis of <em>K. alvarezii </em>seaweed in ascorbic acid, and positive impacts of foliar spraying of the hydrolysate (at different Mw of oligocarrageenans and concentrations) on the hybrid maize crop in Vietnam. The application of this product resulted in increases in efficiency of nutrient uptake by the plant, plant height (~20. 6%), and grain yield (by 21.3% over the control). Therefore, it is suitable for application on a large scale agriculture to reduce the chemical fertilizers used</p>
Experimental Results for the study "A Modular Hybridization of Particle Swarm Optimization and Differential Evolution"
<p>This repository contains the experiment results and R scripts to analyze the data for the study "A Modular Hybridization of Particle Swarm Optimization andDifferential Evolution", which is accepted in <em>The Genetic and Evolutionary Computation Conference</em> (GECCO) '20 conference: </p> <p>Rick Boks, Hao Wang, and Thomas Bäck. 2020. A Modular Hybridization of Particle Swarm Optimization and Differential Evolution. In <em>Genetic and Evolutionary Computation Conference Companion (GECCO ’20 Companion), July 8–12, 2020, Cancún, Mexico. </em>ACM, New York, NY, USA, 8 pages. <a href="http://https: //doi.org/10.1145/3377929.3398123">https: //doi.org/10.1145/3377929.3398123</a></p> <p>Bibtex:</p> <pre><code class="language-markdown">@inproceedings{BoksWB20, author = {Rick Boks and Hao Wang and Thomas B\"ack}, title = {{A Modular Hybridization of Particle Swarm Optimization and Differential Evolution}}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference, {GECCO} 2020, Canc\'un, Mexico, July 8-12, 2020}, publisher = {{ACM}}, year = {2020}, url = {https://doi.org/10.1145/3321707.3321816}, doi = {doi.org/10.1145/3377929.3398123, }</code></pre> <p><strong>Data description:</strong> we benchmarked <strong>800 </strong>different<strong> </strong>hybridizations of the Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms on a well-known continuous black-box problem set called <a href="https://coco.gforge.inria.fr/">COCO/BBOB</a>, which consists of 24 test functions. 30 independent runs are conducted for each algorithm on each problem.</p> <ul> <li>'ERT.csv': a data frame with columns DIM (5D or 20D), funcId (F1-24), algId (algorithm names), target (<span class="math-tex">\(10^{\{-8,-7, \ldots, 1\}}\)</span>), ERT (expected running time), and sd (standard deviation).</li> <li>'raw-data.csv': the running time recorded in each independent run. </li> <li>'analysis.R': the R script that generates ERT tables in the paper.</li> <li>'ecdf.R': the R script that renders the ECDF (empirical cumulative distribution function) plots in the paper.</li> </ul>
The Geometry and Genetics of Hybridization
<p>When divergent populations form hybrids, hybrid fitness can vary with genome composition, current environmental conditions, and the divergence history of the populations. We develop analytical predictions for hybrid fitness, which incorporate all three factors. The predictions are based on Fisher's geometric model, and apply to a wide range of population genetic parameter regimes and divergence conditions, including allopatry and parapatry, local adaptation and drift. Results show that hybrid fitness can be decomposed into intrinsic effects of admixture and heterozygosity, and extrinsic effects of the (local) adaptedness of the parental lines. Effect sizes are determined by a handful of geometric distances, which have a simple biological interpretation. These distances also reflect the mode and amount of divergence, such that there is convergence towards a characteristic pattern of intrinsic isolation. We next connect our results to the quantitative genetics of line crosses in variable or patchy environments. This means that the geometrical distances can be estimated from cross data, and provides a simple interpretation of the ``composite effects''. Finally, we develop extensions to the model, involving selectively-induced disequilibria, and variable phenotypic dominance. The geometry of fitness landscapes provides a unifying framework for understanding speciation, and wider patterns of hybrid fitness.</p>
A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines
<p>The dataset used for evaluating the hybrid feature location technique presented in the paper: "A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines". This enables reproducibility, evaluation, and comparison of our study.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Dataset" contains for each subject system used:</p> <p>(i) the artificial variants and their configurations;</p> <p>(ii) the ECCO repository containing the traces;</p> <p>(iii) the ground truth and composed variants;</p> <p>(iv) the metrics results.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Scenarios" contains for each subject system used:</p> <p>(i) the videos recorded from exercising features on GUI.</p>
Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics (Training Dataset)
<p>This dataset consists of multiple files which contain bug prediction training data.</p> <p>The entries in the dataset are JavaScript functions either being buggy or non-buggy. Bug related information was obtained from the project EsLint contained in BugsJS (https://github.com/BugsJS/eslint). The buggy instances were collected throughout the lifetime of the project, however we added non-buggy entries from the latest version which is tagged as fix (entries which were previously included as buggy were not included as non-buggy later on).</p> <p>The dataset is based on hybrid call graphs which are constructed by https://github.com/sed-szeged/hcg-js-framework. The result of this tool is a call graph where the edges are associated with a confidence level which shows how likely the given edge is a valid call edge.</p> <p>We used different threshold values from which we considered the edges to be valid. The following threshold values were used:</p> <ul> <li>0.00</li> <li>0.05</li> <li>0.20</li> <li>0.30</li> </ul> <p>The prefix in the dataset file names are coming from the used threshold. The the datasets include coupling metrics NII (Nubmer of Incoming Invocations) and NOI (Number of Outgoing Invocations) which were calculated by a static source code analyzer called SourceMeter. Hybrid counterparts of these metrics (HNII and HNOI) are based on the given threshold values.</p> <p>There are four variants for all of these datasets:</p> <ul> <li>Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics and information about the entries (file without any postfix). Column contained only in this dataset are: <ul> <li>ID</li> <li>Name</li> <li>Longname</li> <li>Parent ID</li> <li>Component ID</li> <li>Path</li> <li>Line</li> <li>Column</li> <li>EndLine</li> <li>EndColumn</li> </ul> </li> <li>Both static (NII, NOi) and hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h+s' postfix)</li> <li>Only static (NII, NOI) coupling metrics are included with additional static source code metrics (file with '_s' postfix)</li> <li>Only hybrid (HNII, HNOI) coupling metrics are included with additional static source code metrics (file with '_h' postfix)</li> </ul> <p>Static source code metrics which are contained in all dataset are the following:</p> <ul> <li>McCC - McCabe Cyclomatic Complexity</li> <li>NL - Nesting Level</li> <li>NLE - Nesting Level Else If</li> <li>CD - Comment Density</li> <li>CLOC - Comment Lines of Code</li> <li>DLOC - Documentation Lines of Code</li> <li>TCD - Total Comment Density (Comment Lines in an emedded function will be also considered)</li> <li>TCLOC - Total Comment Lines of Code (Comment Lines in an emedded function will be also considered)</li> <li>LLOC - Logical Lines of Code (Comment and empty lines not counted)</li> <li>LOC - Lines of Code (Comment and empty lines are counted)</li> <li>NOS - Number of Statements</li> <li>NUMPAR - Number of Parameters</li> <li>TLLOC - Logical Lines of Code (Lines in embedded functions are also counted)</li> <li>TLOC - Lines of Code (Lines in embedded functions are also counted)</li> <li>TNOS - Total Number of Statements (Statements in embedded functions are also counted)</li> </ul>
Files and plotting scripts for "Parallel tridiagonal matrix inversion with a hybrid multigrid--Thomas algorithm method"
<p>This archive contains the files required to reproduce the results and figures presented in <em>Parallel tridiagonal matrix inversion with a hybrid multigrid--Thomas algorithm method</em>, J. T. Parker, P. A. Hill, D. Dickinson and B. D. Dudson.</p> <p>Also available at the repository: https://gitlab.com/JosephThomasParker/files-and-plotting-scripts-for-parallel-tridiagonal-matrix-inversion-with-a-hybrid-multigrid-thomas-algorithm-method/</p> <p>Questions to joseph.parker@ukaea.uk.</p> <p>This version is before submission to journal.</p>
Data from: Genetic and morphological evidence of a geographically widespread hybrid zone between two crocodile species, Crocodylus acutus and Crocodylus moreletii
<p>Hybrid zones represent natural laboratories to study gene flow, divergence and the nature of species boundaries between closely related taxa. We evaluated the level and extent of hybridization between <em>Crocodylus moreletii </em>and<em> C. acutus </em>using genetic and morphological data on 300 crocodiles from 65 localities. To our knowledge, this is the first genetic study that includes the entire historic range and sympatric zone of the two species. Contrary to expectations, Bayesian admixture proportions and maximum likelihood estimates of hybrid indexes revealed that most sampled crocodiles were admixed and that the hybrid zone is geographically extensive, extending well beyond their historical region of sympatry. We identified a few geographically isolated, non-admixed populations of both parental species. Hybrids do not appear to be F<sub>1</sub>s or recent backcrosses, but rather are more likely later-generation hybrids, suggesting that hybridization has been going on for several to many generations and is mostly the result of natural processes. <em>C. moreletii </em>is not the sister species of <em>C. acutus,</em> suggesting that the hybrid zone formed from secondary contact rather than primary divergence. Non-admixed individuals from the two species were distinguishable based on morphological characters, whereas hybrids had a complex mosaic of morphological characters that hinders identification in the wild. Very few non-admixed <em>C. acutus</em> and <em>C. moreletii</em> populations exist in the wild. Consequently, the last non-admixed <em>C. moreletii</em> populations have become critically endangered. Indeed, not only the parental species but also the naturally occurring hybrids should be considered for their potential conservation value.</p>
Phylogeography of lionfishes (Pterois) indicate taxonomic over splitting and hybrid origin of the invasive Pterois volitans
The evolutionary consequences of hybridization are poorly understood, especially in the marine realm where hybridization was once thought to be a rare occurrence. Previous research indicated that the lionfishes Pterois volitans and P. miles are sister species, both of which have been detected in the recent invasion of the Atlantic. Anecdotal data from the invasive range indicates they may hybridize, but previous studies have not examined the potential for these species to hybridize in the native range, or how such hybridization affects the distribution of genetic diversity. Here we address evolutionary divergence and population structure using mtDNA COI and two nuclear introns from 214 lionfish including four putative sister species (36 P. miles, 90 P. volitans, 32 P. lunulata, and 56 P. russelii) collected at 10 locations. Genetic data are supplemented with a re-examination of key morphological characters: dorsal, anal and pectoral fin ray counts. These data reveal two lineages (d = 0.041 in COI) among the four putative species: an Indian Ocean lineage, represented by P. miles and a Pacific Ocean lineage represented by P. lunulata and P. russelii. Lionfish identified as P. volitans appear to be hybrids between the sister linages of P. miles and P. lunulata/russelii, a conclusion supported by both the genetic data and morphology. The degree and geographic extent of introgression indicates widespread hybridization, or the absence of valid species distinctions between all four species. These findings also indicate that the lionfish invading tropical Atlantic Ocean, usually labeled P. volitans, is a hybrid.
Data for Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications
<p>These data were generated for the Open-Acces Article :</p> <p>Kamerling, S.; Vuillerme, V.; Rodat, S. Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications. <em>Energies</em> <strong>2021</strong>, <em>14</em>, 3731. https://doi.org/10.3390/en14133731</p> <p>In these dataset, the data for the Case Study and the Sensitivity Analysis are available. Jupyter Notebooks for further process of these data are also available. The NoteBooks AnalyseHourlyValues, AnalyseDailyValues and AnalyseMonthlyValues allow for easy change of variable, whereas CaseStudyAnalysis is for one specific set of data. The AnalyseSets were created in order to analyse the influence of the optimization on the solar fraction of the different datasets.</p>
Transient Optoelectronic Analysis of the Impact of Material Energetics and Recombination Kinetics on the Open-Circuit Voltage of Hybrid Perovskite Solar Cells
<p>This is the data presented in the article 'Transient Optoelectronic Analysis of the Impact of Material Energetics and Recombination Kinetics on the Open-Circuit Voltage of Hybrid Perovskite Solar Cells' published in The Journal of Physical Chemistry C, DOI: 10.1021/acs.jpcc.7b02411.</p>
Exiobase HYBRID | Green steel version
<h2>Description</h2> <p>This repository contains all data and code to extend the <a href="../records/10148587" target="_blank" rel="noopener">hybrid-units version of EXIOBASE</a> to account for new innovative steelmaking routes envisaged to be deployed in the EU to meet decarbonization targets for the steel industry. The new model was built by adopting the <a href="https://doi.org/10.5334/jors.473">MARIO</a> open-source framework. </p> <p>The database is an improved version of the one described in the following open-access paper (DOI: <a href="https://doi.org/10.1088/1748-9326/ad5bf1">https://doi.org/10.1088/1748-9326/ad5bf1</a>)</p> <h2>What's new</h2> <ul> <li>The new technologies have been characterized for all regions, assuming each inventory to be the same in all regions but differentiated by regional import patterns of each commodity.</li> <li>A slight aggregation on electricity production activities and commodities have been also performed, to nowcast electricity production mixes to 2024 based on <a href="https://ember-climate.org/data/data-tools/data-explorer/">Ember data.</a> Data from Ember have been rearranged to calculate electricity mixes by year and Exiobase regions</li> <li>The list of steel production technologies have been extended. Full list in the table below</li> </ul> <p>The database implements in the EU the following new activities and commodities:</p> <table> <tbody> <tr> <td><strong>New activities</strong></td> <td><strong>New commodities</strong></td> </tr> <tr> <td>Manufacturing of steam reformer</td> <td>Steam reformer</td> </tr> <tr> <td>Manufacturing of electrolyser</td> <td>Electrolyser</td> </tr> <tr> <td>Hydrogen production with steam reforming</td> <td>Steam reforming hydrogen</td> </tr> <tr> <td>Hydrogen production with electrolysis</td> <td>Electrolysis hydrogen</td> </tr> <tr> <td>DRI-EAF-NG</td> <td> </td> </tr> <tr> <td>DRI-EAF-NG-CCS</td> <td> </td> </tr> <tr> <td>DRI-EAF-COAL</td> <td> </td> </tr> <tr> <td>DRI-EAF-COAL-CCS</td> <td> </td> </tr> <tr> <td>DRI-EAF-H2</td> <td> </td> </tr> <tr> <td>DRI-EAF-BECCS</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-NG</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-H2</td> <td> </td> </tr> <tr> <td>DRI-SAF-BOF-BECCS</td> <td> </td> </tr> <tr> <td>SR-BOF</td> <td> </td> </tr> <tr> <td>SR-BOF-CCS</td> <td> </td> </tr> <tr> <td>BF-BOF-CCS-73%</td> <td> </td> </tr> <tr> <td>BF-BOF-CCS-86%</td> <td> </td> </tr> <tr> <td>BF-BOF-BECCSmax</td> <td> </td> </tr> <tr> <td>BF-BOF-BECCSmin</td> <td> </td> </tr> <tr> <td>AEL-EAF</td> <td> </td> </tr> <tr> <td>MOE</td> <td> </td> </tr> </tbody> </table> <p> </p> <p>Extended documentation of database adjustment and extension methodology available among the files in this repository. </p> <h2> </h2> <h2>Instructions</h2> <p>To use the database, please install MARIO following the <a href="https://mario-suite.readthedocs.io/en/latest/intro.html#installation">instructions.</a> The database can be parsed by using the following command<br><br></p> <div> <div>db = mario.parse_from_txt(</div> <div> path='PATH/TO/THE/FOLDER/WHERE/DATA/FROM/THIS/REPOSITORY/ARE/STORED',</div> <div> mode='coefficients',</div> <div> table='SUT',</div> <div>)</div> </div> <p> </p>
TLS Z+F Imager 5010 point clouds of hybrid poplar trees from short-rotation crops after 5, 6, and 7 growing seasons
<p>The point clouds are obtained from hybrid poplar crops installed in NE Romania, managed in short rotation (SRWCs) between 5, 6, and 7 growing seasons. The crops were planted every spring, outside the growing season, at a depth of 0.6 m in the ground with two clones: AF8 and Pannonia. Rods (2-meter-long cuttings) were used as planting material at a density of 1667 trees per ha (3 x 2 m). The scanning of the sample areas (3 x 10 trees for each variant, about 6 x 10 m) was outside the growing seasons.</p><p>The 3D model was obtained using the Z+F Imager 5010 (Zoller and Fröhlich, Wangen, Germany), phase-shift type, providing a distance estimation accuracy of ±1 mm at 25 m and a nominal range of 187 m, and the tree individualization was done in CloudCompare v.2.12 (public license). A total of six station points and eight fixed targets or remarks (200 mm spheres) for co-registration were adopted for scanning. Trees included in the survey (without leaves) were marked with a ring of adhesive tape (black with yellow, 50 mm wide) at 1.4 m height on the tree spindle to adjust the results for calibration. Individually segmented trees can be sent on request, the database has a limit of 100 files. They can be converted into different formats via the CloudCompare application.</p><p>File code: clone type _ number of growing seasons _ plot number</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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