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5,371 results for “Flow”
Datasets : Unprecedented Aqueous Solubility of TEMPO and its Application as High Capacity Catholyte for Aqueous Organic Redox Flow Batteries
<p>Dataset of publication DOI: 10.1002/aenm.202301929 published in Advanced Energy Materials journal</p> <p>Despite the excellent electrochemical properties of non-functionalized 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO), its use in aqueous organic redox flow battery (AORFB) is hindered to date due to its insolubility in water. However, in this study, an unprecedented solubility of 5.6 M is demonstrated in an aqueous solution of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), which is 80 times higher than in water (0.07 M). A computational study reveals that the unique interaction between TEMPO and TFSI is essential to achieve this record solubility. TEMPO catholytes are tested in symmetric flow cells, demonstrating high capacity (23.85 AhL<sup>-1</sup>), high material utilization (89%), and robust reversible performance with long-term stability (low capacity fading of 0.082%/day). When paired with sulfonated viologen anolyte ((SPr2)V), an AORFB with low capacity fading over cycling (0.60%/day, 0.048%/cycle) is achieved, constituting the first example of a non-functionalized TEMPO catholyte for AORFB. Notably, this solubilization strategy could be applied to other unexplored chemistries in aqueous electrolytes, leading to the development of new AORFBs</p>
Data for figures in "Next-generation ice nucleating particle sampling on aircraft: Characterization of the High-volume flow aERosol particle filter sAmpler (HERA)"
<p>Atmospheric ice nucleating particle (INP) concentration data from the free troposphere are sparse, but urgently needed to understand vertical transport processes of INPs and their influence on cloud formation and properties. Here, we introduce the new High-volume flow aERosol particle filter sAmpler (HERA) which was specially developed for installation on research aircraft and subsequent offline INP analysis. HERA is a modular system constisting of a sampling unit and a powerful pump unit and has several features which were integrated specifically for INP sampling. Firstly, the pump unit enables sampling at flow rates exceeding 100 L min<sup>−1</sup>, which is well above typical flow rates of aircraft INP sampling systems described in the literature (~10 L min<sup>−1</sup>). Consequently, required sampling times to capture rare, high-temperature INPs (≥-15 °C) are reduced in comparison to other systems and potential source regions of INPs can be confined more precisely. Secondly, the sampling unit is designed as a seven-way valve, enabling switching between six filter holders and a bypass with one filter being sampled at a time. In contrast to other aircraft INP sampling systems, the valve position is controlled remotely via software so that manual filter changes in-flight are eliminated and the potential for sample contamination is decreased. This design is compatible with a high degree of automation, i.e., triggering filter changes depending on parameters like flight altitude, geographical location, temperature, or time. In addition to the design and principle of operation of HERA, this paper presents laboratory characterization experiments with size-selected test substances, i.e., SNOMAX® and Arizona Test Dust. The particles were sampled on filters with HERA, varying either particle diameter (300 nm to 800 nm) or flow rate (10 L min<sup>−1</sup> to 100 L min<sup>−1</sup>) between experiments. The subsequent offline INP analysis showed good agreement with literature data and comparable sampling efficiencies for all investigated particle sizes and flow rates. Furthermore, the deposition efficiency of atmospheric INPs in HERA was compared to a straightforward filter sampler and good agreement was found. Finally, results from the first campaign of HERA on the High Altitude and LOng range research aircraft (HALO) demonstrate the functionality of the new system in the context of aircraft application.</p> <p>The given csv files contain the data for reproducing the figures in the publication. The data structure of the csv files is explained in the README file.</p>
FarmConners Wind Farm Flow Control Benchmark: Blind Test with CL-WINDCON Wind Tunnel Data
<p>This is the dataset used for running the fourth Blind Test of the FarmConners Wind Farm Flow Control Benchmark. The Blind Test was performed with an extensive dataset gathered while testing a cluster of three scaled wind turbines within a large boundary layer wind tunnel. The experimental dataset has been compared against the predictions provided by 5 different control-oriented wind farm flow models. The resulting comparison is described in the paper "FarmConners Wind Farm Flow Control Benchmark: Blind Test Results, Part 2", by Campagnolo et al, (2023). The dataset consists of:</p> <ol> <li>measurements of the flow within the wake shed by one or two machines, as well as measurements of the power, loads (on the rotating shaft and at tower base), and pitch/yaw/torque actuators states of the three scaled machines. The measurements have been performed under a wide range of inflow and machines operating conditions. The time series of the measured data are provided in the format of Matlab structures saved in .mat files.</li> <li>Predictions provided by the models used by the Blind Test participants</li> <li>Matlab scripts used for comparing the experimental dataset and the numerical predictions provided by the Blind Test participants</li> <li>Additional data provided to the Blind Test participants. This includes a FAST model of the scaled wind turbine and the mapping of the inflow of the empty wind tunnel. </li> </ol>
Annex of D1.1 - Nutrient flow analysis and transfer model
<p>The annex of deliverable D1.1 includes all the detailed information used in D1.1: First the assessment of Nitrogen and Phosphorus releases from urban and industrial wastewater using 2 different data sources, the E-PRTR and the WaterBase, and then the evaluation of crop nutrient needs for different crop categories at NUTS2 level for the countries involved in the project.</p>
Shovi flows
<p>shapefile of the Shovi flows</p>
Datasets and Trained Models of the paper: The NFLikelihood: an unsupervised DNNLikelihood from Normalizing Flows
<p><strong>Training Data and Trained models corresponding to the publication: 'The NFLikelihood: an unsupervised DNNLikelihood from Normalizing Flows' (<a href="https://arxiv.org/abs/2309.09743">arXiv:2309.09743</a>).</strong></p> <p>The files cointain the relevant resources for 3 trained Likelihood functions: The Toy-Likelihood, the EW-Likelihood and the Flavor-Likelihood. In each corresponding directory, the training data is found in \data. The trained model and generated samples are found in \NFmodel.</p> <p>To reproduce the published results, git clone https://github.com/NF4HEP/NFLikelihoods, and plug in the provided resources in the corresponding directories of the code.</p> <p> </p> <p> </p>
Global flows of insect transport and establishment: the role of biogeography, trade, and regulations
<p><strong><span>Aim</span></strong><span>:</span><span> Non-native species are part of almost every biological community worldwide, yet numbers of species establishments have an uneven global distribution. Asymmetrical exchanges of species between regions are likely influenced by a range of mechanisms, including propagule pressure, native species pools, environmental conditions, and biosecurity. While the importance of different mechanisms is likely to vary among invasion stages, </span><span>those occurring prior to establishment are difficult to account for. We used records of unintentional insect introductions </span><span>to test 1) whether insects from some biogeographic regions are more likely to be successful invaders, 2) whether the intensity of trade flows between regions determines how many species are intercepted and how many successfully establish, and 3) whether the variables driving invasion success differ pre- and post-introduction.</span></p> <p><strong><span>Location</span></strong><span>: </span><span>Canada, mainland USA, Hawaii, Japan, Australia, New Zealand, Great Britain, South Korea, South Africa.</span></p> <p><strong><span>Methods</span></strong><span>:</span> <span>To </span><span>disentangle processes occurring during the transport and establishment stages</span><span>, we analysed border interceptions of 8,199 insect species as a proxy for transported species flows, and lists of 2,076 established non-native insect species in eight areas.</span></p> <p><strong><span>Results</span></strong><span>: </span><span>During transport, the largest species flows generally originated from the Nearctic, Panamanian and Neotropical regions. Insects native to eight of twelve biogeographic regions were able to establish, with the largest flows of established species on average coming from the Western Palearctic, Neotropical, and Australasian/Oceanian regions.</span><span> Both the </span><span>biogeographic region of origin and trade intensity significantly influenced the size of species flows between regions during transport and establishment. The transported species richness increased with Gross National Income in the source country and decreased with geographic distance. More species were able to establish when introduced within their native biogeographic region.</span></p> <p><strong><span>Main conclusions</span></strong><span>: </span><span>Our results suggest that accounting for processes occurring prior to establishment is crucial for understanding invasion asymmetry in insects, and quantifying regional biosecurity risks.</span></p>
Dataset: Impact of lateral gap on flow distribution, backwater rise, and turbulence generated by a logjam
<p>This dataset includes flow measurements and wood accumulation characteristics of flume experiments conducted at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.</p>
Simulated datasets for detector and particle flow reconstruction: CLIC detector, hit-based data, machine learning format
<p>Derived from https://zenodo.org/record/8260741, prepared in a machine-learning friendly TFDS format, ready to be used with https://zenodo.org/record/8397954.</p> <ul> <li>clic_edm_ttbar_hits_pf10k.tar: ee -> ttbar, center of mass energy at 380 GeV, 10k events</li> <li>clic_edm_qq_hits_pf10k.tar: ee -> Z* -> qqbar, center of mass energy at 380 GeV, 10k events</li> </ul> <p><strong>Contents</strong></p> <p>Each .tar file contains the dataset in the <a href="https://github.com/tensorflow/datasets">tensorflow-datasets</a> (minimum version v4.9.1), <a href="https://github.com/google/array_record">array_record</a> format.</p> <p><strong>Dataset semantics</strong></p> <p>Each dataset consists of events that can be iterated over using the tensorflow-datasets library in either tensorflow or pytorch. Each event has the following information available:</p> <ul> <li>X: the reconstruction input features, i.e. tracks and calorimeter hits</li> <li>ygen: the ground truth particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle</li> <li>ycand: the baseline Pandora PF particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle</li> </ul> <p>The full semantics, including the list of features for X, are available at https://github.com/jpata/particleflow/blob/v1.6/mlpf/heptfds/clic_pf_edm4hep_hits/utils_edm.py.</p>
CyTOF and Flow Cytometry dataset assocaited with "Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females"
<p>This dataset contains all the raw mass cytometry (CyTOF) and flow cytometry fcs files associated with Capelle <i>et al</i>. '<i>Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females',</i> <i><strong>Nature Communications</strong>, <strong>2023</strong>,</i> In Press.</p><p>The dataset contains the following information:</p><p>1, The folder " CoPImmunoPD Flow Zenodo V2.zip " contains all the raw fcs files of flow cytometry analysis and the excel table with marker information of five staining panels in the initial discovery analysis using fresh blood samples. The folder also includes the fcs files of analyzing cytotoxicity potential within CD8 T cells and of validation analyses using cryopreserved samples. Single-color/fluorochrome staining files have also been provided for the relevant experiments in the given subfolders for compensation.</p><p>2, The folder "<a href="https://zenodo.org/api/files/75c910aa-3615-4eff-a201-9d2d46e33ea0/CoPImmunoPD_CyTOF_Zenodo.zip">CoPImmunoPD_CyTOF_Zenodo.zip</a>" contains all the raw fcs files generated from the CyTOF measurements in the initial discovery analysis.</p><p><strong>To reproduce our published Figures, please be assure to first read all the accompanied readme/excel information annotation files deposited in the corresponding folders within the zip files, all the Source Data files of different main and supplementary Figure subpanels, Methods and/or any other relevant sections in our manuscript.</strong></p>
Higher-order Mobility Flow Data
<p>This dataset is a collection of higher-order mobility datasets, primarily aimed at trajectory data mining applications. These datasets have been created using the Point2Hex tool, allowing us to transform traditional GPS-based geolocations and check-in data into sequences of higher-order geometric elements, particularly hexagons. This transformation has various advantages, including reduced sparsity, analysis at different levels of granularity, improved compatibility with common machine learning architectures, enhanced generalization and overfitting reduction, and efficient visualization.</p> <p>Seven popular mobility datasets, typically utilized in various trajectory-related tasks and technical problems, were subjected to this transformation process. These include applications like trajectory prediction, classification, clustering, imputation, and anomaly detection, among others.</p> <p>To foster the culture of reusability and reproducibility, we are providing not only the transformed higher-order mobility flow datasets but also the source code for the Point2Hex tool and comprehensive documentation. This offering aims to streamline the generation process, ensuring that users have clear guidance on how to reproduce curated or customized versions of these datasets. The material is stored in publicly accessible repositories, ensuring its widespread accessibility.</p>
Data and scripts for the colour analysis from: Gene flow throughout the evolutionary history of a colour polymorphic and generalist clownfish
<p>Even seemingly homogeneous on the surface, the oceans display high environmental heterogeneity across space and time. Indeed, different soft barriers structure the marine environment, which offers an appealing opportunity to study various evolutionary processes such as population differentiation and speciation. Here, we focus on <em>Amphiprion clarkii </em>(Actinopterygii; Perciformes), the most widespread of clownfishes that exhibits the highest colour polymorphism. Clownfishes can only disperse during a short pelagic larval phase before their sedentary adult lifestyle, which might limit connectivity among populations, thus facilitating speciation events. Consequently, the taxonomic status of <em>A. clarkii</em> has been under debate. We used whole-genome resequencing data of 67 <em>A. clarkii</em> specimens spread across the Indian and Pacific Oceans to characterise the species' population structure, demographic history, and colour polymorphism. We found that <em>A. clarkii</em> spread from the Indo-Pacific Ocean to the Pacific and Indian Oceans following a stepping-stone dispersal and that gene flow was pervasive throughout its demographic history. Interestingly, colour patterns differed noticeably among the Indonesian populations and the two populations at the extreme of the sampling distribution (i.e. Maldives and New Caledonia), which exhibited more comparable colour patterns despite their geographic and genetic distances. Our study emphasises how whole-genome studies can uncover the intricate evolutionary past of wide-ranging species with diverse phenotypes, shedding light on the complex nature of the species concept paradigm.</p>
Evaluation of Implementing FLOW
ClinicalTrials.gov study NCT04193033. IPD Sharing: NO. Countries: 1. Publications: 2.
Data for: Mimicking functional elements of the natural flow regime promotes native fish recovery in a regulated river
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Metabolically-driven flows enable exponential growth in macroscopic multicellular yeast
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Supplementary material for: PhyloCoalSimulations: A simulator for network multispecies coalescent models, including a new extension for the inheritance of gene flow
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Supplementary data for: Comparison of optical flow derivation techniques for retrieving tropospheric winds from satellite image sequences
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Tracing evolutionary trajectories in the presence of gene flow in South American temperate lizards (Squamata: Liolaemus kingii group)
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Data from: Performance characteristics and bluff-body modeling of high-blockage cross-flow turbine arrays with varying rotor geometry
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Data from: Energy harvesting in a flow-induced vibrating flapper with biomimetic gaits
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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.