Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5,530
datasets available to search
ShareScore release 0.9.0
Dataset results
5,530 results for “informal”
Supporting data for: Topographic information improves simulated patterns of post-fire conifer regeneration in the Southwest U.S.
<p>The western U.S. is projected to experience more frequent and severe wildfires in the future due to drier and hotter climate conditions, exacerbating destructive wildfire impacts on forest ecosystems such as tree mortality and unsuccessful post-fire regeneration. While empirical studies have revealed strong relationships between topographical information and plant regeneration, ecological processes in ecosystem models have either not fully addressed topography-mediated effects on the probability of plant regeneration, or the probability is only controlled by climate-related factors, e.g., water and light stresses. In this study, we incorporated seedling survival data based on a planting experiment in the footprint of the 2011 Las Conchas Fire into the PnET extension of the LANDIS-II model by adding topographic and an additional climatic variable to the probability of regeneration. The modified algorithm included topographic parameters such as heat load index (HLI) and ground slope and spring precipitation. We ran simulations on the Las Conchas Fire landscape for 2012–2099 using observed and projected climate data (i.e., RCP 4.5 and 8.5). Our modification significantly reduced the number of regeneration events of three common southwestern conifer tree species (piñon, ponderosa pine and Douglas-fir), leading to decreases in aboveground biomass, regardless of climate scenario. The modified algorithm decreased regeneration at higher elevations and increased regeneration at lower elevations relative to the original algorithm. Regenerations of three species also decreased on eastern aspects. Our findings suggest that ecosystem models may overestimate post-fire regeneration events in the southwest U.S. To better represent regeneration processes following wildfire, ecosystem models need refinement to better account for the range of factors that influence tree seedling establishment. This will improve model utility for projecting the combined effects of climate and wildfire on tree species distributions.</p>
The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections
<p>These files are associated with the article "The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections". </p> <p>1. <a href="https://zenodo.org/api/files/1f7bc8d5-f9f5-4305-9c52-f6ebbf94c072/soil_hyper_albedo_RF_int.nc">soil_hyper_albedo_RF_int.nc</a> - hyperspectral soil albedo </p> <p>2. <a href="https://zenodo.org/api/files/1f7bc8d5-f9f5-4305-9c52-f6ebbf94c072/lai_hyper_albedo_RF_int.nc">lai_hyper_albedo_RF_int.nc</a> - hyperspectral surface albedo</p> <p>3. <a href="https://zenodo.org/api/files/1f7bc8d5-f9f5-4305-9c52-f6ebbf94c072/atmos_F2000climo_clm5sp.21_50-F2000climo_clm5sp_blue_diff_red_dir.21_50.tgz">atmos_F2000climo_clm5sp.21_50-F2000climo_clm5sp_bl ...</a> - diagnostic results of the atmospheric model CAM between broadband and hyperspectral simulations. </p> <p>4. <a href="https://zenodo.org/api/files/1f7bc8d5-f9f5-4305-9c52-f6ebbf94c072/F2000climo_clm5sp.21_50-F2000climo_clm5sp_blue_diff_red_dir.21_50.tgz">F2000climo_clm5sp.21_50-F2000climo_clm5sp_blue_dif ...</a> - diagnostic results of the land model CLM between broadband and hyperspectral simulations. </p>
Example meshes for 'Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation'
<p>Example meshes for 'Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation'</p> <p>The meshes contain DTI. To read the mesh to FEniCS, see e.g., <a href="https://github.com/bzapf/braintransport/blob/24ba4e37a3d6fadb37c249ca7f717a7355f48f30/optimal_velocity/postprocess_phi.py#L12">here </a>.</p> <p>Find the simulation codes for the manuscript here:</p> <p><a href="https://github.com/bzapf/braintransport">https://github.com/bzapf/braintransport</a></p>
Data for: Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management
<p><span>Extensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science-based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density-dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual-based model based on dynamic energy budget theory and full life history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual-level processes. We demonstrated the utility of the model framework by applying it </span><span>to an extensively enhanced species, Chinese prawn (<em>Fenneropenaeus chinensis</em></span><span>, Penaeidae</span><span>). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity, and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade-offs between the ecological and economic objectives, i.e., pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement program, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management.</span><span> </span></p>
Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.
<p>This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong></p> <p>The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.</p>
NewSOC, supplementary information to WT2.3 "Development of doped lanthanum chromite based fuel electrodes", WT2.5 "Electrochemical characterization of single cells"
<p>These are experimental data related to CERTH participation in NewSOC project (874577) regarding WT2.3 “Development of doped lanthanum chromite based fuel electrodes”, WT2.5 “Electrochemical characterization of single cells”. The data set includes:</p> <ul> <li>physicochemical characterization (ICP, BET, XRD and SEM) of the powders and electrodes or cells produced (SEM)</li> <li>electrochemical characterization (iV characteristics, impedance, stability tests)</li> </ul> <p> </p> <p><strong>LSCrF0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV, EIS and stability testing for button cells using different electrolyte substrates (formulation and thickness) and oxygen electrode materials operating under steam electrolysis, co-electrolysis of steam and carbon dioxide and reversible operation in steam or carbon dioxide cycle.</p> <p><strong>LSCrF0.5.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.5</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrNi0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Ni<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrNi0.5.rar:</strong> The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Ni<sub>0.5</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, and (B) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrMn0.1.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Mn<sub>0.1</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrF0.05Ti0.05.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.05</sub>Ti<sub>0.05</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrF0.05V0.05.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.9</sub>Fe<sub>0.05</sub>V<sub>0.05</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide.</p> <p><strong>LSCrF0.25Ti0.25.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.25</sub>Ti<sub>0.25</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide. </p> <p><strong>LSCrF0.25V0.25.rar</strong>: The zip folder contains data related to La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Fe<sub>0.25</sub>V<sub>0.25</sub>O<sub>3-δ</sub> material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p><strong>Ni-GDC.rar</strong>: The zip folder contains data related to button cell stability testing using a commercial Ni-GDC fuel electrode material operating under steam electrolysis. </p> <p><strong>LARGE CELLS.rar</strong>: Data set for large cells (5x5 cm2) including iV, EIS and short-term stability testing employing Keracell III cell, Ni-GDC and LSCrF0.1 fuel electrodes operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.</p> <p> </p> <p> </p> <p> </p>
Does social information affect the settlement decisions of resident birds in their second breeding attempt? A case study of the Japanese tit (Parus minor)
<p>Individuals may gather information about environmental conditions when deciding where to breed in order to maximize their lifetime fitness. Many studies have shown that birds can rely on social information to select their nest site. The location of active nests and the reproductive success of conspecifics and heterospecifics can provide accurate predictions about the quality of the breeding habitat. Some short-lived species can facultatively reproduce two and/or more times within a breeding season. However, few studies have focused on how multiple-brooding individuals select nest sites for their second breeding attempts. In this study, we use long-term data to test whether the Japanese tit (<em>Parus</em> <em>minor</em>) can use social information from conspecifics and/or heterospecifics to select a nest site for the second breeding attempt. Our results showed that the nest boxes occupied by tits on their second breeding attempt tended to be surrounded by more breeding conspecific nests, first-breeding successful conspecific nests, and fewer first-breeding failed conspecific nests than the nest boxes that remained unoccupied (the control group). However, the numbers of breeding heterospecific nests, successful heterospecific nests, and failed heterospecific nests did not differ between the nest boxes occupied by tits on their second breeding attempt and the unoccupied nest boxes. Furthermore, the tits with local successful breeding experience tended to choose areas with more first-breeding successful conspecific nests than those without successful breeding experience. Thus, we suggest that conspecifics' but not heterospecifics' social information within the same breeding season is the major factor influencing the nest site selection of Japanese tits during second breeding attempts.</p>
IWIN: The Isfjorden Weather Information Network (August 2021 - June 2023)
<p>The Isfjorden Weather Information Network provides standard meteorological near-surface measurements from the Isfjorden region in Svalbard. The network includes weather stations permanently installed on lighthouses around the fjord and onboard small tourist cruise ships trafficking the fjord from the spring to the autumn. A defined (fixed-end) data set covering the period August 2021 - June 2023 is available here, while new observations become available in near real-time via the data portals of MET Norway (https://doi.org/10.21343/ebrw-w846; https://thredds.met.no/thredds/unis-obs/unis-obs.html).</p>
Data from: Scoutknife: A naïve, whole genome informed phylogenetic robusticity metric
<p>The phylogenetic bootstrap, first proposed by Felsenstein in 1985, is a critically important statistical method in assessing the robusticity of phylogenetic datasets. Core to its concept was the use of pseudosampling - assessing the data by generating new replicates derived from the initial dataset that was used to generate the phylogeny. In this way, phylogenetic support metrics could overcome the lack of perfect, infinite data. With infinite data, however, it is possible to sample smaller replicates directly from the data to obtain both the phylogeny and its statistical robusticity in the same analysis. Due to the growth of whole genome sequencing, the depth and breadth of our datasets have greatly expanded and are set to only expand further. With genome-scale datasets comprising thousands of genes, we can now obtain a proxy for infinite data. Accordingly, we can potentially abandon the notion of pseudosampling and instead randomly sample small subsets of genes from the thousands of genes in our analyses. Here, we introduce Scoutknife, a jackknife-style subsampling implementation that generates 100 datasets by randomly sampling a small number of genes from an initial large-gene dataset to jointly establish both a phylogenetic hypothesis and assess its robusticity. Using 18 previously published datasets and 100 simulation studies, we show that Scoutknife is conservative and informative as to conflicts and incongruence across the whole genome, without the need for subsampling based on traditional model selection criteria.</p>
Grammaticus leidensis: supplementary information
<p>In ‘Of tortoise necks and dialects: a new edition of the Grammaticus Leidensis’ (forthcoming in <em>Byzantinische Zeitschrift</em>), we present a new edition of the Byzantine treatise on dialects known as the Grammaticus Leidensis. To allow readers to verify the manuscript stemma we present there, we here provide a copy of the text with a very full apparatus, recording the readings of all the manuscripts known to us. This version of the apparatus may also be useful to those interested in the reception of the text from the tenth century up to the Renaissance.</p>
Can we collect health-related quality of life information from anticoagulated atrial fibrillation participants who have recently experienced a bleed? An observational feasibility study in primary, and secondary care and through an online forum
<p>The purpose of the study was to evaluate the feasibility of recruiting participants diagnosed with atrial fibrillation (AF) taking oral anticoagulation therapies (OACs) and recently experiencing a bleed to collect health-related quality of life (HRQoL) information.</p> <p><strong>Design</strong></p> <p>Observational feasibility study. The study aimed to determine the feasibility of recruiting participants with minor and major bleeds, the most appropriate route for recruitment and the appropriateness of the Patient Reported Outcome Measures (PROMs) selected for collecting HRQoL information in AF patients, and the preferred format of the surveys.</p> <p><strong>Setting</strong></p> <p>Primary care, secondary care, and via an online patient forum.</p> <p><strong>Participants</strong></p> <p>The study population was adult patients (≥ 18) with Atrial Fibrillation (AF) taking oral anticoagulation therapies (OATs) who had experienced a recent major or minor bleed within the last four weeks.</p> <p><strong>Primary and Secondary outcome measures</strong></p> <p>Primary outcome:</p> <p>Patient reported outcome measures (PROMs): EuroQol 5 dimensions-5 levels (EQ-5D-5L); Perception of anticoagulant treatment questionnaire, part 2 only (PACT-Q, part 2); Atrial fibrillation effect on quality of life (AFEQT)</p> <p>Secondary outcomes:</p> <p>Location of bleed; bleed severity; current treatment; patient perceptions of HRQoLin relation to bleeding events.</p> <p><strong>Results</strong></p> <p>We received initial expressions of interest from 103 participants. We subsequently recruited 32 participants to the study- 14 from primary care and 18 through the AF forum. No participants were recruited through secondary care. Despite 32 participants consenting, only 26 initial surveys were completed. We received follow-up surveys from 11 participants (8 primary care and 3 AF forum). COVID-19 had a major impact on the study. </p> <p><strong>Conclusions</strong></p> <p>Primary care was the most successful route for recruitment. Most participants recruited to the study experienced a minor bleed. Further ways to recruit in secondary care should be explored, especially to capture more serious bleeds. </p> <p><strong>Registration</strong></p> <p>The study was adopted onto the NIHR Portfolio (I.D. #47771) and registered with www.ClinicalTrials.gov (#NCT04921176) in February 2021.</p> <p>Dataset contains all anonymised data for the participants who completed the survey including demographics, details of bleeds, co-morbidities and completed patient reported outcomes</p>
Additional information for QJRMS (QJ-23-0159) submission
<p>This file contains the following information:</p> <p>1. energy-spectrum: Energy spectrum for three components of velocity and turbulent kinetic energy.</p> <p>2. time-series: The time series of total kinetic energy.</p> <p>3. input-files: The settings and input topography as required by PALM simulation.</p>
Multi-Omics Visible Drug Activity Prediction with a Biologically Informed Neural Network Model
<p>Drug discovery is a challenging task, it takes several years for a drug to be introduced on the market, with most of<br> the studied drugs not even passing the first phase. The understanding of the mechanisms influencing response to drugs<br> can reduce failures and accelerate drug development. Virtual drug screening, based on Machine Learning models, is a<br> promising field for the prediction of the outcome of a treatment. However, the complex relationships between the features<br> learned by these models are still poorly understood and not easy to interpret.<br> We have designed a Neural Network model for drug sensitivity prediction that leverages a Visible Neural Network, an<br> easily interpretable model, due to its biologically informed nature. The trained model can be inspected to study which<br> biological processes were fundamental for the prediction and to identify the drug properties that affect sensitivity. It<br> combines multi-omics data from various types of tumor tissues and drug representations based on molecular descriptors.<br> The mechanisms learned from the network can also be exploited to find candidate drugs for synergy to predict the effect<br> of combined therapies. We consider the unbalanced nature of public drug screening datasets and show that our model<br> outperforms state-of-the-art visible machine learning models.</p>
BioRodDis project - Individual information on rodent samples - Jura (France) 2020/2022
<p>This xlxs file contains 190 rodent individuals for which the serological statut for the Puumala (PUUV) orthohantavirus was assessed by immunofluorescence assay (IFA) and enzyme-linked immunosorbent assay (ELISA). </p> <p>The table is organized with the sequencing code in row and the different individual variables in column:</p> <p>Corresponding abbreviations:</p> <p>- CodeID : the unique identifier of each individual</p> <p>- Species: the rodent species</p> <p>- Locality: the sampling locations: La Glacière=”FRFGLA”, Mignovillard=”FRFMIG”</p> <p>- Sex: the sex (F=female; M=male)</p> <p>- Season: the season of sampling</p> <p>- Year: the year of sampling</p> <p>- Period: the season and year of sampling</p> <p>- Weight: the weight (g)</p> <p>- Body_length: the body length (cm)</p> <p>- Tail_length: the tail lenght (cm)</p> <p>- Testes_position: the testes position status (0/1)</p> <p>- Testes_length: the testes lenght (mm)</p> <p>- Seminal_ves_dev: the seminal vesicles development status(0/1)</p> <p>- Vulva: the vulva opening status (0/1)</p> <p>- Lactation: the lactation status (0/1)</p> <p>- Placental_scars: presence of placental scars (0/1)</p> <p>- Uterus_dev: the uterus development status (0/1)</p> <p>- Gestation: the gestation status (0/1)</p> <p>- Sexual_Maturity: the sexual maturity (Mature or immature)</p> <p>- IFA_PUUV: the PUUV serological status by IFA (0= negative; 1= positive)</p> <p>- Serology: the PUUV serological status by ELISA (0= negative; 1= positive)</p>
Supporting Information from The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs)
<p>Supporting Information (Open Data) from The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs)</p>
Replication Package: An Expert Survey on the Use of Informal Models in the Automotive Industry
<p>This repository contains the replication package for the paper <em>An Expert Survey on the Use of Informal Models in the Automotive Industry</em> by <a href="https://orcid.org/0000-0001-6410-6769">Dominik Fuchß</a>, <a href="https://orcid.org/0000-0001-7312-2891">Thomas Kühn</a>, <a href="https://orcid.org/0000-0002-8953-1064">Jérôme Pfeiffer</a>, <a href="https://orcid.org/0000-0003-3534-253X">Andreas Wortmann</a>, and <a href="https://orcid.org/0000-0002-1593-3394">Anne Koziolek</a>. The paper has been accepted at the <a href="https://www.iese.fraunhofer.de/en/twinarch.html">TwinArch 2023: The 2nd International Workshop on Digital Twin Architecture</a> co-located with <a href="https://conf.researchr.org/home/ecsa-2023">ECSA 2023</a>.</p>
A new family of Asellota (Crustacea, Isopoda) from the deep sea of Zealandia: Supplementary Information
<p>Supplementary files for publication:</p> <p>A new family of Asellota (Crustacea, Isopoda) from the deep sea of Zealandia</p> <p>George D. F. Wilson, Saugatuck Natural History Laboratory, Michigan, USA</p> <p>Files from TNT 1.5-1.6 analyses of data of the Janiroidean Asellotans.</p> <ol> <li> <p>Janiroidea_taxon_list.odt - list of taxa used in analysis with authorities</p> </li> <li> <p>Janiroidea.prt - character names and states</p> </li> <li> <p>Janiroidea.tnt - TNT analysis file</p> </li> <li> <p>Janiroidea_simplified.nex - Simplified Nexus file used in the analysis, without character descriptions</p> </li> <li> <p>Janiroidea_unweighted_majority-rule_tree.pdf - consensus summary of branches that appear in all trees. The branch numbers indicate the percentage of times a branch appears in all trees with a value of 50% or above. 1 means that the branch appears in all trees.</p> </li> <li> <p>Janiroidea_unweighted_Jac33_tree.pdf - symmetric jackknife analysis where each branch had a 33% chance of being duplicated or deleted. The branch values are the percentage of trees that the branch was found and the percentage where branch was uncontradicted. The square brackets mean that the number was negative.</p> </li> <li> <p>Janiroidea_K24.355468_Jac33_tree.pdf - same as the unweighted analysis but the optimal concavity value (24.355468) was used in the implied weighted analysis.</p> </li> <li> <p>Janiroidea_K24-355468_Jac33_50collapsed_tree.pdf. Same as above but all branches with values of 50% or less were collapsed. Family names indicated on the right.</p> </li> <li> <p>Janiroidea_K3-30_majority-rule_tree.pdf. Consensus of analysis testing a range of k from 3 to 30. All trees found were used in the consensus. The branch numbers indicate the percentage of times a branch appears in all trees with a value of 50% or above. 1 means that the branch appears in all trees.</p> </li> <li> <p>Janiroidea_no-Janiroidea_no-Basoniscus_unweighted_Jac33_tree.pdf. Same as item 6 but without <em>Basoniscus</em> n.gen. in the taxon list.</p> </li> <li> <p>Janiroidea_no-Basoniscus_K23.876952_Jac33_tree.pdf. Same as item 7 but without <em>Basoniscus</em> n.gen. in the taxon list.</p> </li> </ol> <p> </p>
Supplementary data of article Integrating Data-Driven and Hydraulic Modelling with Acoustic Sensor Information for Improved Leak Location in Water Distribution Networks
<p>This dataset was generated within the research thesis of Axel Hutomo, under the supervision of Leonardo Alfonso and Ioana Popescu at IHE Delft, and it is published as supplementary data for the article <em>Integrating Data-Driven and Hydraulic Modelling with Acoustic Sensor Information for Improved Leak Location in Water Distribution Networks, </em>currently under review. </p> <p>The Excel sheet provides information about the datasets produced to integrate acoustic sensor data and hydraulic model output data, to be used by the Machine Learning model. The acoustic sensor data were obtained by extracting several features in time and frequency domains from each audio file coming from acoustic sensors, whereas hydraulic model data was obtained by modelling these leaks using a pressure-independent analysis.</p> <p>The Python code shows the building of the ANN for leakage modelling prediction, integrating the two datasets above, for different leak rates.</p>
agilIS - agile Information Systems
<p>AgilIS combines Information Systems (IS) Planning, Development, Operation, Management, and Governance macro activities in an integrated manner, based on agile principles.</p>
Fig. 1 in The highs and lows of serow (Capricornis sumatraensis): multi-scale habitat associations inform large mammal conservation strategies in the face of synergistic threats of deforestation, hunting, and climate change
Fig. 1. Camera-trap image of mainland serow (Capricornis sumatraensis) from the lowlands of the Pasoh Forest Reserve in Peninsular Malaysia at an elevation of ~100 m.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.